[This Transcript is Unedited]
National Center for Health Statistics
3311 Toledo Road
Hyattsville, Maryland
Proceedings by:
CASET Associates, Ltd.
Fairfax, Virginia 22030
Agenda Item: Introductions and Opening Remarks
DR. FRANCIS: I'm going to get us started, so if people can take their seats and be comfortable, and get happily on the line. The first thing that we need to do is to say that this is a workshop sponsored by the National Committee on Vital and Health Statistics. This part of the workshop is lead-sponsored by the Subcommittee on Privacy, Confidentiality and Security of NCVHS. There was a prior workshop in February where the Population Subcommittee of NCVHS took the lead in organizing.
The goal of these two workshops, and potentially even more, is to think through the questions of how to appropriately protect community trust, in light of the extraordinarily wonderful new ways that various forms of health data are being used, and not only health data, but also community data, everything from the weather to the grocery store. So what we did in February was hear from a number of groups about fantastic ways in which data are being used to empower communities.
And what we are planning to do today is to begin to brainstorm about best practices for making sure that people trust the ways in which data are being used, and do so legitimately, so that there aren't backlashes basically.
So with that quick introduction, the way we're going to start this out is we're going to go around and ask everybody who's here to identify themselves, and say if you're a member of the committee, and we'll take it from there.
I will start. I'm Leslie Francis. I Co-Chair the Privacy, Confidentiality and Security Subcommittee of NCVHS and I don't have any conflicts.
MS. MILAM: Sallie Milam with the West Virginia Healthcare Authority, Co-Chair of The Population Health Committee. And I, along with Dr. Larry Green, are really pleased that Populations could co-sponsor this workshop today, and felt like we learned a lot from everyone in February, and are very excited to hear the privacy end of the issue today.
MS. HORLICK: Good morning. I'm Gail Horlick. I'm from CDC in Atlanta and I am Staff to the Subcommittee on Privacy, Confidentiality and Security.
MS. GONZALEZ: Hello. I'm Natalie Gonzalez and I'm from CDC in Atlanta, but I'm not on the Subcommittee, but I'm glad to be here. Thanks.
DR. BOTKIN: I'm Jeff Botkin. I'm a guest today. I'm from the University of Utah and I'm a pediatrician. I do Bioethics and I'm the Associate VP for Research at the University.
MS. KAHN: I'm Hetty Kahn. I'm with CDC's National Center for Health Statistics. I'm Staff to the Subcommittee in Privacy, Confidentiality and Security.
MS. CHAPPER: I'm Amy Chapper. I'm from the Centers for Medicare and Medicaid Services, and I'm Staff to the Subcommittee.
MS. GREENBERG: Good morning and welcome to NCHS. I'm Marjorie Greenberg from NCHS CDC and Executive Secretary for the Committee.
MS. KANAAN: Susan Kanaan, Writer for the Committee.
MR. SUAREZ: Good morning, everyone. I'm Walter Suarez with Kaiser Permanente. I'm a member of the National Committee. I Co-Chair the Standard Subcommittee and I'm a member of both the Population Health, and the Privacy and Security Subcommittees. And no conflicts, thank you.
MS. BERNSTEIN: I'm Maya Bernstein. I'm the Privacy Advocate of the Department. I sit in the Office of the Assistant Secretary for Planning and Evaluation. I'm Lead Staff to the Subcommittee on Privacy, Confidentiality and Security.
DR. FRANCIS: I think we should go next to the phone, and then we'll go around the room. So Larry?
DR. GREEN: Dr. Larry Green, University of Colorado. Front Range passes are closed this morning because of a winter snow storm. Member of the Full Committee and no conflicts, just wishing the passes would open up.
DR. FRANCIS: And I think we also have Michelle Justus on the phone?
MS. JUSTUS: Yes. I'm Michelle Justus and I'm going to be presenting this morning. And I am the Director of the Arkansas Obesity Initiative at the Arkansas Center for Health Improvement.
DR. FRANCIS: Thank you.
MS. MAIN: Good morning. I'm Debbie Main. I'm from the University of Colorado. Larry, I made it out here because I didn't have to go through the passes. And I will be presenting this afternoon.
MS. JONES: Katherine Jones, NCHS and Staff to the Committee.
MS. JACKSON: Debbie Jackson, NCHS CDC Committee Staff.
MS. RHODES: Rosamond Rhodes, I'm a philosopher, bioethisist at Mt. Sinai School of Medicine, and at the Community Graduate School and at the Union Mt. Sinai Bioethics program.
Agenda Item – Panel I Engaging Communities
DR. FRANCIS: Okay, we're set to go. So the first panel is entitled "Engaging Communities." And we have Michelle Justus, who's here as the Director of the Arkansas Obesity Initiatives, and then we're going to hear from Jeff Botkin. So why don't we start with Michelle? We've structured this to make sure that we have plenty of time for discussion because our goals here are really to learn. So Michelle?
MS. BERNSTEIN: And also, I want to let you know, Michelle, someone is here to turn your slides for you in the room, so if you could let her know when you'd like to proceed, that'd be great.
MS. JUSTICE: Okay, great, thank you. First, let me apologize that I was not able to be there. I'm actually about eight months pregnant and not able to travel at this time. But again, I appreciate you guys having me.
MS. BERNSTEIN: We're very glad to have you any way we can have you.
MS. JUSTICE: Thank you. But I'd like to present today to you all about the Arkansas Body Mass Index Initiative that's been going on here in Arkansas since 2003. So if you can go to the slide that says BMI assessment, and that's for the first year, and then to the next slide that shows the timeline of events.
So in April of 2003, the Arkansas General Assembly passed what we call here Act 1220 and it's a multi-component act. But I guess the component that a lot of people have heard about and got a lot of media attention was the actual body mass index assessments in our schools. So this was actually an assesment that was state-mandated. It was an unfunded mandate, so there was not funding that was given to the schools to actually do these assessments.
So in June of 2003, the Arkansas Department of Education and Arkansas Department of Health, who in the actual Act were required to do this in our state, turned to our center, The Arkansas Center for Health Improvement, and asked us to help them and develop a standardized protocol for doing these assessments across our state, and help with the implementation of this initiative.
And so, we did not have a timeframe of, "Okay, well, let's take a year or two to take figure out how to do this, and then start implementing." We had to figure out how to actually do this, and then implement it all within one year, so it was a pretty chaotic and crazy first year. So we had to determine how to assess height and weight, and calculate body mass index on 450,000 students across our state in the public schools.
So in September of 2003, we worked with the University of Arkansas for Medical Sciences and Arkansas Children's Hospital to develop a standardized measurement protocol, so all of the schools across the state were using the same measurement protocol, so we developed that protocol. In October of 2003, we actually tested all different types of equipment, scales and stadiometers that measures height, to make sure. Actually, the main reason we wanted to test it was to see what type of equipment that we could get away with using.
So our schools, since it was an unfunded mandate, we didn't have enough funding to go out and buy research grade equipment. So we wanted to see if using a bathroom scale was sufficient or at what level did we need to use the equipment. So what we found was that we used somewhat of a size scale that wasn't necessarily the bathroom grade.
DR. FRANCIS: Sorry, we're having a little phone trouble.
MS. JUSTICE: Okay, that's fine. And so, then we actually built our own stadiumometer to measure height. So we wanted a stadiumometer that was portable, that schools could combine all of their equipment within a district, and have multiple stations if that's what they wanted to do.
So then in November of 2003, we actually, here in Arkansas, through our health department, have what we call "community health nurses," and they work directly in the educational cooperatives across our state. So they actually trained all of the school personnel on the standardized measurement protocol. So for the most part, school nurses or the school personnel that do the assessments, there are others in some cases that do it, but whoever does the assessment has to be trained in the standardized protocol.
Then in January of 2004, the actual assessments began statewide, so we piloted it in the fall, and began doing it statewide in January of 2004 and collecting the data. And then, in June of 2004, the individualized Child Health Reports were mailed to parents or guardians.
Next slide, please. And so, really quickly, the process of year one, we received a data file from the Department of Education, Arkansas Department of Education, with all of the demographic information. So we didn't have to have schools provide all the names and information that we needed to calculate body mass index. And so, once we received that data, in the first year, we had not had time to develop an electronic entry system, so we had to do the entire project paper-based, which if you can picture 450,000 sheets of paper, it's quite a lot, more than we ever imagined.
And so, what we did was we generated individualized bar coded forms, and we mailed these directly to the school for the data collection. So the demographic information was populated at the top of the form, and the schools completed the height and weight assessments, and then got those back to us. And how that worked, for confidentiality reasons was that, at the time, it just so happened that Kinko's and FedEx merged together to become one. And so, we actually had them make all of the photocopies for us, and ship them directly to the school through FedEx, so we had a mechanism to track the information and know where it was at all times. We also provided the schools with a FedEx return label prepaid, so they could FedEx it back to our center.
So the data was collected, using paper forms from the school, and returned to our center. And then, we actually had around the clock data entry personnel to enter the information and do validity checks on the data entry. And then, our center generated a Child Health Report for all of the approximately 422,000 students, and mailed those to the parents by the postal system. And then, the schools were actually given password-protected files so they could keep that for their records.
Next slide, please. So this is just an example of what the Child Health Report looks like. It still looks basically the same today. And the table that you can see or the little graphic that you can see actually is a visual for parents so they can see where their child actually falls and which classification category their child falls.
Next slide, please. So in the first year, we did have five types, and we still continue to have five types of Child Health Reports. We have one for children that are overweight, one for at risk for overweight, healthy weight, and actually these categories, as you know, have changed. This was in the first year. Now, we've changed them and updated them to use the current CDC classification category. And then, we had one for underweight, and then one if the child was not able to be assessed. We had a generic report that went home to the parent, just explaining what body mass index is and some healthy tips that they can use in their family.
And again, the first years of reports were mailed directly to the parents, using the address that was provided by the Department of Education, so we were ensured that we were receiving the correct parent or guardian's information, because we were somewhat concerned or we were concerned that, when you get into guardianship, and especially in divorcee cases, then who has the right to have it. So we got all that information from the Department of Education in Arkansas.
Next slide, so that was the first year. The second year, we realized very quickly when we started receiving all of these 450,000 sheets of paper in our office and we had to store them in a confidential manner, that this was not something that we could continue to do through every year. We had stacks and boxes of paper everywhere, under lock and key at all times, and it was a whole lot to manage.
Next slide, so the year two process, we decided that we really needed an electronic entry system that was web-based for the schools to enter this information into. So the majority of the students' information continued to be the same process that we had in year one, but we did have two different school districts participate in a web-based pilot system. One of the school districts actually recorded information on paper, and then entered it into the system at a later date. And then another district in our state had pocket PCs and this was before iPhones and all that type of thing. But they had pocket PCs that they could enter the information into and then upload it to their computer.
And so, then once they uploaded it, the data was stored in our secure web-based system. The Child Health Reports were generated by our center, and all of the schools had access to their Child Health Reports from the secured web-based system. All of the schools, each nurse, was given, or school personnel, was given a user name and password to pull the information from our website.
And the second year, the other thing that happened was that we actually outsourced the data entry to the University of Arkansas in Fayetteville, Arkansas, Survey Research Center who is a center that's used to dealing with this type of data. And they actually entered all of that into our system for us.
Next slide, in the second year, we also added a Spanish Child Health Report. So one of the pieces of information that we get from the Arkansas Department of Education is primary language spoken by the parent. And so, for those that their primary language is Spanish, we do provide them with a Spanish Child Health Report.
Next slide, so in year two, again, we had five types of individual Child Health Reports, and they were generated both in English and Spanish. Those that were generated in Spanish, we also had an English version for the schools to have for their file.
And then, in the second year, we did not receive funding. In the first year, our center received funding to mail the Child Health Reports to the parents. In the second year, we did not receive funding, so that became a responsibility of the schools. We highly encouraged them to get these reports to the parents in a confidential way, such as mailing. Some of them hand them out at parent-teacher conferences and different things like that. Since the schools have local control, we do not have a way to control how they send those to the parents, but we do provide examples and reasons why they should not hand them directly to the children.
And then, the College of Public Health at the University of Arkansas for Medical Sciences also does our evaluation of the entire Act 1220. And the way you can see when they ask the schools how they're actually getting the reports to the parents, those are the different types of ways that they are actually giving them to the parent. So the majority of them still continue to mail them. Some of them have sent them home and others gave them out at parent-teacher conference, and some of them let them pick them up at the school.
Next slide, so year three, get to the next slide, the year three process was still again, we had approximately 300,000 students continue with the paper-based process. And we included another option for those pilot schools that we had. We increased the pilots to 16 districts in the state, and we also had another option which was direct web access. So if they had laptops in their school and they could get on, or a computer where they could still do the assessments in a confidential way, they had access to the web system and they could directly enter the information at that time. And the schools did have access to the Child Health Reports by the website.
Next slide, so now to years four through seven, and we are currently in data collection of year eight, so year eight is the same as years four through seven. Next slide, and so now, beginning in year four, we went completely to the web-based system, and schools basically have two options of how they can enter this information. They can do direct web-based entry into the system, if they have access to a computer nearby where they're doing the assessment. Or they can actually write the information down and enter the information at a later date.
Next slide, so I don't want to spend a whole lot of time on the results because the information is on our website, but this is the most recent data that we've released. Next slide, and in the 2009-2010 school year, you can see here that this is the percent of students that their information was calculated, so 83 percent of the data that we received was valid for BMI, so we have BMIs on 83 percent of the information. Seventeen percent of the data was children that were not assessed for various reasons. They might have been absent. There is an option for parents or children to refuse, and there's a various list of reasons why they may not have been assessed.
And then, there was a very small percentage of data that a component of the data needed to calculate the BMI was not available, so it was not valid for calculation. Next slide, this is the results for the past few years. You can see that it's very consistent across the years. There's approximately 38 percent of our students in public schools here in Arkansas are either overweight or obese. Next slide, this is just a breakdown by classification and gender, and pretty equally distributed, females 38 percent, males 39 percent, either overweight or obese.
Next slide, this is broken down by ethnic group, and you can see that in our state, Hispanics have about 40 percent of Hispanic children that were assessed are either overweight or obese. Forty-two percent African-Americans, and then 39 percent Native-American, 36 white and 31 percent Asian. Next slide, the BMI classification by grade, you can see that pretty much in the middle school grades, there's a spike in BMIs and then it starts to head down again.
Next slide, this is BMI classification by gender and ethnic group. Again, the Hispanic males, 50 percent are overweight or obese. And then, the next highest group was female African-Americans, 45 percent, and the lowest was white females at 34 percent. Next slide, BMI classification by gender and grade. Again, you see the spike in the middle school years, and then it starts to trend down again.
Next slide, this slide is somewhat complicated if you look at it at first glance. It's classification by gender, ethnic group and grade, and it's consistent with the other results. And then next slide, this is a map of our state and the white lines are the county lines, the black lines are the school district lines, and it is pretty busy. But the point of this map is that, first, let me point out that there are a few white spots on the map and those white spots are the schools that did not actually participate. So where there's blue on the map, are all of the schools in the state that did participate. So you can see that we have a pretty high participation rate in our state, as should be expected since it is state law.
And then, the other really important thing about this map is that all of our schools in the state, no matter where they're located and what their population might look like, they all have an obesity problem. So even the lowest rates are 20 to 30 percent. So the lightest blue are 20 to 30 percent overweight or obese, so there's a problem in our entire state.
Next slide, and then this is just my contact information, if you all have questions after today, I'd be more than happy to answer them. I may not have addressed all of the questions. You may have questions and I'm more than happy to answer any of those questions. I did not get a lot into the confidentiality and security, but I'm more than happy to answer those questions, if I know the answer. If not, I can definitely find them out for you.
DR. FRANICS: Thank you very much. I think we will, in the discussion, I know we've got a considerable amount of time for discussion, so I suspect people will want to follow up on some of those questions, too. That was fantastically interesting, thank you. I want to take one second to let a new committee member who's come, introduce himself. Paul?
MR. TANG: Yes, hi, Paul Tang, Palo Alto Medical Foundation, Member of this Subcommittee and Committee, no conflict.
DR. FRANCIS: Yes, okay, thanks, Paul. And now, we've got Jeff Botkin, who's going to talk about public engagement in biobank research. Jeff's getting miked up. Can the people on the phone hear Jeff?
DR. BOTKIN: Testing, testing, can you hear me on the phone?
MS. JUSTUS: Yes.
DR. BOTKIN: Well, thanks, Leslie for the invitation to be here. And I'm going to talk a little bit about a couple of issues that I've become familiar with in recent years. I'm part of a group at the University of Utah that is engaged in developing biobank in a federated data set resource for the purposes of biomedical research. I've also been conducting in recent years a NIH-funded study looking at blood spot retention by state public health programs, and public attitudes related to that. And I've also been involved with, at the federal level, the Secretary's Advisory Committee for Human Research Protection that has also been focusing on some biobank-related activities.
Now, I'm going to be talking, for the most part, using terminology about biobanks. But I don't think, from my perspective, at least, there's often a significant distinction between biobanks and data repositories. And it may well be that distinction becomes increasingly blurred over time, as for example, we can efficiently sequence DNA for example. It may well be that, for certain types of research, you simply store the sequence rather than the sample itself.
So I've got a fair number of slides here and I'm going to keep an eye on Leslie, when she gives me the high sign to wrap it up. So this is just a reminder of what I think is evident to everybody, that there's an enormous amount of research that's developing, a lot of capabilities for combining sophisticated tissue analysis, linked with extensive health records. Folks are very excited about this form of research and digital technologies, making this increasingly possible.
Here's the key ethical issue, though, as far as I'm concerned. It's that the biobanks and data repositories permit the analysis of tissues and datas at times and places remote from the source. So traditionally, we're used to research context in which there's a fairly close relationship between the investigator and the research participant. Increasingly, though, with these sorts of analyses can be conducted remotely. So the key question then becomes, "How much control should sources have over research conducted with their samples or data?"
When is notification or consent required? What should be the scope and nature of informed consent for this type of work? And how should biobanks or data banks be governed in order to secure public trust. The question here is, can we move away from a traditional informed consent model, to allow this sort of research to go forward.
So part of the issue here is that there's no public knowledge or very little public knowledge of many sorts of biobanking and secondary use of biospecimens. Folks who are having their clinical specimens stored and used for research purposes simply aren't aware that this is a mode of research that's being conducted, and that's particularly true in this particular domain that I'll talk with newborn blood spots.
When informed, the data pretty clearly shows that there are significant public concerns about privacy for secondary uses of specimens. And again, I mean here specimens, as well as data. Risk to individuals, however, as far as I'm concerned, are really quite low, but risk to population groups exist, but this particular type of risk is poorly addressed, if at all by the current regulations.
So individual harms and wrongs, I think we're used to thinking about in this context. What are the risks of biobank and data depositories, breaches of confidentiality, leading potentially to stigma and discrimination, breaches of privacy that may cause potentially tangible harms or dignitary harms. And the psychological impact, usually from predictive information in these sorts of context. When you have an analysis of tissue sample for predictive, say genetic, information, then returning that information to the source could conceivably lead to psycho-social or psychological impacts.
But I would claim that such breaches are rare. The literature pretty clearly shows that, at least for individuals who participate in predictive, say genetic, research, the psychological impacts of that information are proving to be quite low. You see a spike in anxiety within the first weeks or months after disclosure of at-risk information, that then declines to below baseline by a year or so, and this is pretty consistent across a variety of research that's been conducted over the last 20 years in this domain. And of course, there are some predictive measures that are out there to begin to deal with things like genetic discrimination, genetic information on discrimination act that, as everybody here, I'm sure, knows that is in place, but is yet to be adequately tested.
This notion of group harms is important, but again not adequately covered by the regulations. This simply refers to a study that folks probably familiar with here, Arizona State University, where they have the Havasupai Indians, in which they were recruited for diabetes-related research, blood samples taken. Those samples were subsequently distributed to other institutions and research was conducted that was beyond the original consent agreement between the participants and the investigators. The tribe learned of this research and became appropriately upset and brought suit about that issue. Again, the allegation here wasn't so much that there were individuals who were harmed through the use of this information, but yet the group experienced harm or potential harm by the distribution of samples beyond what had been anticipated by many of the participants.
So what do we know about public attitudes about this issue in general? Institute of Medicine Report, 2009, this was on HIPAA privacy and so they had done a nice job, I think, of reviewing the literature. They talk here about a Harris poll, 63 percent of Americans would give general consent for use of medical records and research with privacy protections. So a majority certainly, but a substantial minority would not give such permission.
The majority of respondents in several studies expressed a desire to be consulted before information is used in research, including when data is de-identified. And I would just emphasize that this is such a consistent theme in the literature in this particular domain, and I'll show you some of our data about newborn blood spots. But the consistent theme is people want a choice. And if you ask them, they'll say "yes" for the most part, but they want to be asked. And again, what I'm presenting to you is what I see as a contemporary challenge in that domain, because it's increasingly hard to simply ask people their permission.
A little more information about general attitudes that Kathy Hudson published in 2009. A large US survey of over 4600 participants about biobank research. Forty-eight percent supported blanket consent for future research, meaning they would be willing to say, "Go ahead and do what is appropriate for pursuit of science in the future." However, 42 percent wanted consent for each project using their sample. Almost half then, 42 percent, wanted individual project-specific control over the use of their sample, and ten wanted categorical consent where they could say, "Okay to use it for cancer research, but not for other particular domains."
Another study, this was a focus group participants' opinions about providing study-specific consent. So participants were asked if they agreed or disagreed with these statements about how they would feel if they had to give permission for researchers to use their samples and information before each new research project. So here's the top category, I don't have a pointer here. "I would feel it was a waste of time and money." How many agreed with that? Twenty seven percent. Seventy three percent disagreed that they thought it would be a waste of time or money to contact them about each project.
"I would feel bothered." Well, 26 percent agreed with that, a large majority disagreed with that, that folks would not feel bothered or a waste of time to contact them. Conversely, "I would feel I have control," 75 percent agreed with that. "I would have more trust in the study," 75 percent agreed with that. "I would feel respected and involved," 81 percent agreed with that. So you can see the strength of public opinion, with this sample, at least, about how much people want to have that individual level of control over samples and biobank-related research.
So here's our project, and I'm going to give you just a little bit of information about the study we've been doing for the last three years. This gives you a graph of how state health programs are retaining residual newborn screening samples. Now, quick reminder, these are screening tests that are done under state mandate, in all states in the United States and around the world for most developed countries. Blood spots obtained within a day or two of birth, battery of 30 plus different conditions are assessed through that bloodspot, usually to state lab. And then, those results are promptly returned to clinicians when necessary to address the needs of the child.
So, typically rare conditions, but in almost all circumstances, there's residual blood left over on those filter papers. So what do you do with those? A lot of states will discard them, only retaining them for a month or two or three months, in order to make sure the tests are adequately completed. Sometimes retesting of the samples is necessary, so they'll keep them for a couple of months. Once you kept them for a year or longer, it's pretty clear you're keeping them for reasons other than the conduct of the screening tests themselves. Now, these are conducted under state mandate, parents are not asked their permission, although most states have an opt-out mechanism for philosophical or religious reasons.
However, the vast majority of parents aren't effectively informed that they have that option. It's in the brochure that's in the bottom of the bag that's given to folks when they have a new baby, so virtually nobody opts out.
So you can see the number of states store the specimens indefinitely, or for many years. California and New York, for example, are two states that store them indefinitely. So it's about half the babies in the United States, because a couple of the large states retain them indefinitely, have these specimens retained for decades.
It's not been without controversy. The article in Discover magazine now, a couple of years ago, newborn blood storage lost or fears of DNA warehouse. Help, the government has my DNA. That lady on the right doesn't seem to be concerned enough about that situation. And there have been at least two states that have now been sued for this practice. Minnesota, the suit was based on a claim that retention of the samples without consent was inconsistent with the state genetic privacy laws. The parents who brought that suit lost that case. The decision was made that newborn screening was not covered by the Genetic Privacy Act.
In Texas, a constitutional suit was brought, the claim being that this was unlawful search and seizure. Well, the state didn't want that suit to go forward. I think with some concern, perhaps, that if they were to lose that suit, there would be quite a bit of activity that was conducted in the biomedical arena that might fall under that general category of unlawful search and seizures, since we know data and specimens obtained clinically are used for research purposes, often without the explicit consent of the people involved.
So Texas came to an agreement with the parents, destroyed five million samples that had been retained for a number of years. It looked like it was going to be resolved, and then it became public knowledge that the state had shared about 800 samples with the Department of Defense that was interested in using these specimens to further refine their personal identification system that they had for remains. The allegation was that this information was being withheld or hidden. The state denies that, but at any rate, a new suit has been brought that is currently working its way through the courts.
A new suit has been brought in British Columbia, in Canada, so even Canadians are concerned about this kind of process. New Zealand is now experiencing significant controversy, so this is sort of a global phenomenon that has been occurring because this practice has been ongoing for a number of years, without adequate public engagement, in my opinion.
So we have a project that's a three-year project, "Methods for Promoting Public Dialogue on the Use of the Residual Newborn Screening Samples for Research." We have three specific games. This first one is to do a comprehensive assessment of health department policies and procedures. And we have a publication out just this last month to document results of that survey.
A key part for today's discussion is our outreach to the community, to ascertain public attitudes about this particular issue. We had three different methods; we surveyed the public, surveys, focus groups and then Knowledge Networks. Knowledge Networks is a company that has a pre-established panel of individuals, representative of the U.S. population across the U.S., who have technological support, computers basically, and they do electronic surveys for a variety of different purposes. So the question for us was whether Knowledge Networks was a less expensive and more efficient way to access public opinion, other than focus groups or traditional surveys. Third specific game was to conduct a working group to try to craft recommendations on policy in this domain.
So here's our assumptions, we've got the general public is not aware of this issue, and increasingly aware, given the lawsuits, but for the most part, the public doesn't know this is going on. And therefore, basic education on the issues was necessary to obtain informed opinions. We didn't think we could simply go out and ask people what they thought of this practice, without giving them some education about what the practice was.
So we prepared a 22-minute video that covered newborn screening, retention of samples, pros and cons, interviewed experts across the country, public health individuals, ethicists, attorneys and others, about this practice. And to some of our sample, gave them this educational intervention as a way of providing them with sufficient background to provide a more informed opinion than they would otherwise have. The survey instrument itself also had a little bit of information about this practice, typical for a lot of surveys that would give you a modest amount of information about the issues you're being asked to address.
So here's our groups. We had three percent in traditional focus groups, all of whom saw the movie. Surveys conducted by a company, Dan Jones, paper, telephone, about 37 percent, and then Knowledge Network's approach was 60 percent of our folks. About half saw the video, about half did not. Here's our responders, a pretty good diversity across our racial and ethnic groups, mothers of young children included. About 40 percent was outside the mountain states region, because we weren't certain whether mountain states might have some particular philosophical mince in this particular domain. A majority were women.
So a little bit of the results here. "Did you know that these tests were done?" These are the newborn screening tests themselves, and you can see that a little over half were aware that newborn screening was done. Pretty clear through the focus groups that folks didn't have much knowledge beyond that. You know, they might think this is the PKU test, for example, when in fact, it's a test for 30 or more different conditions, so a lot of folks were aware that babies did get tested.
So here's specifically about this retention issue. "How supportive are you of health departments doing these blood tests on all new babies?" I'm sorry, this is the newborn screening part itself, not the retention. "How supportive are you of newborn screening?" You can see between very supportive and somewhat supportive, we have pretty much everybody. People think newborn screening's a good idea. This isn't a hard sell. They like the general concept of newborn screening.
But do you think it's all right that these tests are done without the permission of parents? Now, here you see almost an exact 50-50 split, with the largest single category being definitely not okay to do newborn screening without the permission of parents. So the traditional approach that's been used in this domain of mandatory screening is okay by half, but not okay by another half.
DR. TANG: I'm just clarifying that these are the ones that are listed that they're going to do immediately, versus the ones that are done when they're retained.
DR. BOTKIN: That's correct. Yeah, these are for the clinical specimens themselves. And this has been a big deal within the field for a while, where the public health departments have consistently pushed back against a consent model because of the complexity and difficulties of obtaining that. Now, actually, Maryland is a state that, for many years, had an opt-in model where parents had to sign a form in order to have these tests done. But at least, anecdotally and by experience, it was never anything more detailed than "sign here, your baby is going to get a blood test." It really wasn't an informed piece to the informed consent, and within the last year, Maryland has abandoned that approach and now has an opt-out approach, as many other states do. So Maryland was sort of the one example out there for many years that was a little different.
How concerned would you be if health departments save the leftover blood samples from babies after the tests are done? And again, here you see again almost an exact, well, this isn't a 50-50. What you see is not at all concerned, 25 percent, only a little concerned, 20 percent, somewhat concerned, 24 percent, and then very concerned, about 28 percent. So again, while there's a full spectrum here, the single largest category is very concerned at about 28 percent or so.
So here's a quick vignette we gave them. Imagine that a health department has been saving leftover samples for the past ten years, without the permission from parents. Now, imagine that researchers want to use the samples for important health research. It may be difficult and costly to find many parents after several years. If parents cannot be contacted, what would be the best thing to do with their babies' leftover samples? "Allow use" was clearly the predominant choice here. So when push came to shove, can't contact parents, should we use them or not use them, majority saying allow use.
Another vignette, some health departments keep samples only if parents agree to this by signing a form. In other states, all samples are kept, unless the parents contact the health department and say they want their child's sample destroyed. What do you think is the best thing to do? Keep samples only if parents sign a form or keep samples unless parents contact the heath department to have them destroyed? So, an opt-in model versus the opt-out model. Clear predominance of parents want to have the option to sign it in. Okay, and they don't like the opt-out as much, even though probably 38 percent or so thought that the opt-out was okay.
So final question, we had a whole series of other questions that I don't have data for you today about. But final question here, after thinking about these questions for the last few minutes, we want your final opinion. Do you think it's all right to use these leftover blood samples for doing important research? Definitely all right, probably all right, clearly the predominant choice is here, probably not, definitely not all right, small minorities. And here, the idea was that we wanted to return to the basic question because we thought answering the survey itself would be educational for folks because it would give them an opportunity to think about some of the complexities and the different aspects of the issues.
So the public really is clearly quite supportive of the ability to do research in this particular area, but again, no question that they want an active role, or the majority do want an active role in having something to say about that. So we looked to various associations for what led different people to be more or less supportive, support for retention and use generally associate with the video viewing. This was the most consistent fact. People who had the educational video were more supportive.
Now, at the beginning, we weren't certain whether folks who knew more about this would be more supportive, or more upset or outraged about it, and it's clear that education about this leads folks to be more supportive. Female gender and more liberal political ideology were also more supportive. Support generally not associated with our mountain states region for race or ethnicity or for religion.
So conclusions from our particular study, strong support for newborn screening clinical services, general support for sample retention and research use, but a desire for choice over retention. More information is associated with greater support, so we think providing the public with greater education about this will benefit programs, rather than what's been the tradition for many years, which is programs trying to fly below the radar. They've been thinking, I think, that just not talking about it was the best way to go, and I think they're getting burned in Texas and Minnesota and elsewhere for a lack of transparency about this process.
And here's our research team. It's been a terrific group. My general conclusions about this whole area then. Biobank and data dependent research is going to continue to expand. This is really a very important and powerful mode. But appropriate authorization of the sample and data use is at least a key ethical issue here. I think the risks associated with this type of research are very low. I really think the loss of laptop phenomenon is probably one of the most common methods by which data are inappropriately lost. But I'm not aware of a track record of specific harms to individuals that have been documented through this type of research.
Public has substantial concerns about privacy and control, nonetheless, so I see a discrepancy here, again, from my perspective, between what the real risks are and what the public thinks the risks are. And so, in the absence of a consistent ability to engage people at the individual level about the variety of choices that might be available for this, potentially a governing structure should be fostered for these entities that will help promote public trust.
Having said that, we asked our participants in our study about, "Would you feel comfortable if there were a public representative of you to help make these sorts of decisions, rather than you personally?" And they frankly gave us blank stares, it was like, "What are you talking about? What do you mean a public group? What does that mean?" So they didn't really get the notion that there could be representatives who might try to protect their personal interests, they want to be asked. And I don't think we adequately reflected to these individuals the complexity of that request. It was consistently, "Just ask me and I'll say yes." But the whole notion of "Just ask me" is a complex and difficult, expensive prospect, and I don't think folks adequately understood what they were looking for in that respect.
So that's sort of the next hurdle for us to begin to look at some of these issues about what folks are comfortable with in certain forms of biobank research. So we'll have some focus groups in the upcoming months, throughout the state of Utah, about our initiative for biobank and data federated research, and see what our local public is comfortable with in this domain.
DR. FRANCIS: Thank you. We now have a little over half an hour for discussion, and I'm going to invite committee members and others to ask questions.
DR. GREEN: Leslie, my hand's up.
DR. FRANCIS: Okay. So Larry, since you're on the phone, and the phone folks sometimes have the hardest time to get a word in edgewise, go for it.
DR. GREEN: I want to first of all thank Michelle and Jeff both for being so useful and so on target, and I'm just very appreciative of what you've done this morning. I have one question for each of them, it's about harms and risks. For Michelle, my question was just if she could tell us of any adverse reports from the whole Arkansas exercise, related to complaints or concerns from parents or advisory groups, or legal actions or known breaches in the confidentiality policies that they adopted, or stigmatization by race and ethnicity groups, any adverse effects. And my question for Jeff was, I'd like to ask him to render his personal judgment and opinion about what would actually constitute adequate public engagement concerning the use of biobank data.
DR. FRANCIS: Michelle, you want to?
MS. JUSTUS: Sure, I'll go first. You know, obviously we've had some adverse effects. But the College of Public Health here in Arkansas does a very good job of evaluating this. And they've really found very little, if any, causes. I mean, one of the big concerns was that BMI assessments could cause eating disorders. And their evaluation report has not shown that at all, from the youth and the parents that they survey. Our data doesn't necessarily show that, although anorexia could probably be picked up in the underweight category increasing, but bulimia obviously doesn't necessarily mean a drop in weight.
But as far as confidentiality breaches, there have been some anecdotal reports that I've heard that schools have actually given the report to the child and not followed our strong recommendation. And there have been some cases of children being made fun of, due to that. So I think the schools have learned quickly to do this in a confidential manner and that it is important to get these reports to the parent in a confidential manner.
As far as the College of Public Health also does, like I said, a parent survey, as well as a survey with youth. And they have found that 75 percent of parents are not at all or only a little concerned about classmates finding out BMI measurements. So there is still a 25 percent of parents that are concerned about it. Our protocol at our center is that, if we do hear a complaint or receive concerns from parents or schools, we have that investigated. We find out what happened and try to address it with additional training to prevent it from happening again.
We also do have our community health nurses do spot checks with schools, to ensure that they're following protocol. But it is a serious situation and we do take it serious, and we obviously want this to be a helpful tool for parents, and not something that is harmful to children or to families. And I hope I addressed your questions.
DR. GREEN: You did very well. Has there been any adverse action taken against the State of Arkansas?
MS. JUSTUS: No.
DR. BOTKIN: Yes, great question, and I guess I would say the following certainly depends on the particular context. But I personally am comfortable with, in general, an opt-out system, despite what our own data showed about parents' desires in this particular context. I think an opt-out system adequately protects the interests of people, while allowing this sort of important research to go forward.
However, I think there has to be some clear notification of what people's options are. People have to be given an explicit opportunity to opt out. I don't think this is a circumstance in which it's appropriate to bury people's options in the paperwork, and have them call a phone tree at the hospital or health department, in order to have their sample or data excluded. So I think it has to be upfront and clearly stated in ways that people would understand.
I also think that an element of transparency here is essential, where there ought to be public reports, newspapers, television, opportunities to present to the public what's going on. There should not be any suggestion that this is being done in the basement behind closed doors. And so, I think engaging with the media about these sorts of activities is going to be important. I think that, in and of itself, will reassure people that there's nothing too nefarious going on.
So I do think there are challenges with figuring out how to do this in effective ways. Vanderbilt, with their BioVU program, I think has done a pretty good job with implementing an opt-out approach, and they're finding that 95 percent of folks are not opting out of their biobanking initiative, and I think they've done a nice job of community engagement, assessed public opinions about how they're approaching this and maintain public trust in Vanderbilt's efforts here. So I think it is possible to do this in the right way.
DR. GREEN: Thank you.
DR. FRANCIS: Thanks. So I've got Sallie and Paul and Walter and Marjorie.
MS. MILAM: Okay. I've got a few questions. I think I'll just ask a couple of general ones, and then hold the rest until everybody has a chance. I'm wondering if you could each speak to the different identifiers that were saved around the data in the databases. So were you saving name, address, birth date, SSN, that kind of thing? And then, a follow-up question for Michelle. We heard a lot about Jeff's process of educating and notifying the folks around the consent decision. But I was wondering if you could also speak to that process, if you had one, around the collection of obesity information.
MS. JUSTUS: Sure. First, the data component piece. We do get all of the demographic-type information from the Department of Education, which includes name, date of birth, gender, ethnicity. We get what's called "free and reduced lunch," which again is a proxy for socioeconomic status, and we do have all of that. A lot of it, we have to have in order to calculate BMI, but once we get the information out of our web-based system to store it and do analysis on it, we do de-identify that information. And we actually have IRB approval from the University, once the data's pulled from the web system, and so we have to adhere to all the IRB, the data security components of that.
Can you repeat the second part of the question? I want to make sure I answer it correctly.
MS. MILAM: Sure. I'm wondering, as the children were lined up at school to get weighed, was there any sort of discussion with the parents ahead of time, were there community meetings, was a letter sent out? How was the process explained to the parents around the consent decision?
MS. JUSTUS: That was really left up to the schools to decide how they wanted to handle that. Some of the schools do actually send out letters to parents, notifying them that this screening tool will be assessed, just like vision and hearing in the schools. They send out a generic letter about all the screens. Some of them put it in their handbook at the beginning of the year when parents registered. But because it is state law, there's not a required consent or they don't have to get permission from the parents.
In the initial years, the law was silent on if a parent could even refuse for their child to participate. Our center, I guess, interpreted it, or gave the school an out, because we didn't want any child forced on a scale. And so, what our center did was on our form, for a reason that the child couldn't be unable to be assessed, they actually had a place for the school to check that the parent refused or that the child actually refused. So they weren't put in an awkward position and forcing a child to be assessed.
Since the original act was passed, there's been some amendments to the law, one being that, now parents do have the option to opt-out. But it is the responsibility of the parent to write a letter to the school, and it is not the school's responsibility to notify the parent and to give the parents an option to opt out.
DR. BOTKIN: Quickly, with respect to the newborn screening samples, typically, of course, those differ somewhat by state, by they'll have name and identifying information for the family, address, birth date, the baby's weight and identification of primary care provider, to whom the results would go.
Now, typically, specimens that are being stored will be stored with all of the original data that's associated with that card. But in most circumstances, or virtually all, investigators who access those samples would receive the identified samples. There has been at least one example otherwise for that, in which samples were being used to test for CMV, cytomegalovirus, that can have hearing implications for babies, and they wanted to be able to get back to families with information about prenatal infections for CMVs, so that the families could address potential hearing loss in the babies.
But mostly, it's de-identified. Some of the research here has been quite appropriately done with de-identified samples. Some of the early uses were with tracking HIV infection in mothers in New York and Massachusetts during the 1980s. These specimens were used in a de-identified fashion to see which communities, over a period of time, were seeing increases in HIV infection, for example. So those sorts of geographic locations may well be retained with the samples for that sort of epidemiologic purpose.
DR. TANG: Thank you. And I found the presentation very interesting. Some questions, I think mostly for Jeff. I have four of them, they're related. So when you talked about the focus groups and surveys, and asked them about would it be okay if further research was done on the blood samples, did you explain who would do the research? For example, was it just the Public Health System, and if not, who did you say would do it?
Similarly, in the ASU case, we talked about the diabetic whose tissue sample was later used for set-in schizophrenia. Who did that? And did you mention in one of these cases, maybe it was biobank, that the group who acquired the information, sold or shared it with other groups?
The third goes into your explanation that, if people are shown the video that explains what else could we be doing, people really appreciate the education and probably would consent even in an opt-in case. Do you think that that kind of willingness extends beyond the case scenarios that you presented? I don't remember if that was just case scenarios about newborn screening, or does it expand generally to public health, clinical research in general, and performed by whom? So that's all sort of related, but how much did the folks that you queried understand the broader context, and how much of your results, do you think, expand to the broader context?
DR. BOTKIN: We did not address too explicitly the sharing of samples within the video itself. We had a series of questions on the survey about how much would you trust different entities to do research in an ethical fashion, and we had academic researchers, public health, federal agencies and private companies. And there was a clear pattern where academic institutions received the highest level of trust, the federal government and private companies had the lowest level of trust. To use these in an ethical fashion is how we expressed that question. So I think we, at least in that context, gave them a sense that there would be potential access by a variety of different types of investigators to the samples.
The question about whether these issues extend beyond the case at hand. My sense in the literature is that they do. I think the literature pretty clearly shows that the majority of people understand healthcare research, are willing to share samples and data, but simply want that element of personal control about that. And I do think what our experience was, and I think this is reflected in the literature, is that you have a pretty solid minority of folks who are highly concerned about this arena, and have high expectations for privacy and control. And I think it's an interesting question in sort of political science, how you deal with minorities who have strong opinions about these kinds of issues. But it seems to me the majority is pretty accommodating, if you engage them.
DR. TANG: So you mentioned that you teased out who do you trust. But when you asked the question, "Is it okay?" what was their understanding? Is it okay just for the public health service agency who obtained the original sample, or is it okay to pass it on to others?
DR. BOTKIN: Yes, good question and we did not ask that. We simply said, "Is it okay to use this for different types of research?" But with those questions, we didn't break that down by would it be okay for different types of people to do different modalities.
DR. TANG: So considering the context of the survey, chances are they were saying this newborn screening and by the person who got it? I mean, that's a projector.
DR. BOTKIN: Probably.
DR. TANG: But it sounds a little bit like that's okay.
DR. BOTKIN: Probably. I think that would be a reasonable assumption, but don't know.
DR. SUAREZ: Thank you both for just a terrific presentation. I have a couple of questions for Michelle. I'm fascinated by the degree to which this population based detail, child BMI data, is being collected in Arkansas. And I was wondering if you know of how many other states are collecting it this way across the country? Is this a one-state project at this point, or do you know of how many other states are doing it?
MS. JUSTUS: I know that there are many other states that are doing it now. There's very few that are doing it statewide, so it's just Arkansas. A lot of states are doing it just in certain districts or communities, but not necessarily statewide. I think there are now maybe one or two other states that are doing it statewide, or are trying to do it statewide. I don't know that they're actually there yet, but there are some that are working towards that.
DR. SUAREZ: Interesting. And then, my other question is about how do the providers get this type of information. So this is collected by schools and maintained by the Department of Health, Department of Education, I believe. But do you share this information with providers, in any way?
MS. JUSTUS: We do not share it with providers. The Child Health Report that's sent to parents, there is a statement in there that says, "Seek your healthcare provider for further assessments," because it describes how it's a screening tool, and that they should really go to their primary care physician to have further assessments if they're concerned, and to take a copy of the letter. And we have heard reports from physicians that some of them are receiving or having families come in with their report.
We are actually working towards through a whole health information exchange type system that's going on in our state. We are working towards having a student health record at school, which would be, in the best case scenario, I guess, would be typical to a medical record file, and would then be able to be accessed by the physical, if there was permission from the parent. But we're not close to that, but that's just something that we're working towards.
DR. SUAREZ: Great, because that links to my other question, which is, you probably know under the Meaningful Use Program, EHRs are now required to be capable of, and providers are expected to begin, capturing BMI in their electronic health record systems. And so, we're going to see as we see it into the future, I guess, hopefully 100 percent compliance of every patient's electronic health record having BMI recording and maintained.
And then, of course, we're going to have this information being collected on a population basis, so how do you see the two interacting into the future? You seem to be leaning towards a concept of certainly making that connection between the school health record and the record maintained by the provider. Is that your sense into the future?
MS. JUSTUS: Yes, absolutely. We are at the table with the state plan for the entire state talking together through their electronic medical records. And so, the school piece is going to be a component of that. The details of how it's going to work and all of that are still to be determined, but that's definitely something that we're having discussions and trying to figure out the best way to do that. Right now, the early childhood population is one that's been left out of these assessments, which we also want to include.
And the early childhood children are actually required to have their BMIs done by a physician, and reported to the State Program Office on Early Childhood. So we're working with their office also. It's a pilot type thing to see how we can get their data and include that in this, and also provide a similar report to Early Childhood. So there's a lot of different pieces, where we're trying to figure out the best way to do that here.
DR. SUAREZ: Great. And I have one quick question on the privacy side, and this is mostly for Dr. Botkin. There is a lot of talk about consent. But particularly, I haven't heard too much lately about the role that privacy boards and IRBs play in deciding ultimately in the case of research, and I know in public health, public health agencies use also IRBs on privacy boards to make this type of decisions about obtaining their proactive consent.
Do you have a sense of where privacy boards fits into the perspective of consumers, and IRBs, I guess, and are they understood well enough by consumers to be the trusted place where decisions, such as authorizing of the collection of information for research, without consent or with consent, do they trust that on those privacy boards? I don't know if that's something that you cover in your analysis and in your survey, but your perspectives on that?
DR. BOTKIN: Yeah, well, part of our project involved interviews with mountain states newborn screening advisory boards. And these are boards of interdisciplinary boards, almost always including lay participation, that advise health departments about newborn screening programs. So we interviewed all of them in the Rocky Mountain West, specifically about this issue, and it was pretty clear that they did not perceive themselves to be the public advocate role here. They had much more participation by clinicians and some specialists, who were speaking to the more technical aspects of newborn screening, as opposed to the public perspective.
And it's pretty clear the public representatives on these boards also had not been adequately supported or schooled to see themselves as representatives of the public, as opposed to simply people who might have a wise opinion about issues to offer for the discussion. Most typically, the lay advocates on these advisory boards are people who have affected children for PKU or one of the conditions, and speak from that perspective, as opposed to somebody who's just a general public member.
IRBs are, of course, involved in all of the research access to the specimens, and typically it would be the public health department's IRB, as well as the investigator's IRB, who would take a look at these. And generally, with the identified specimens, they are not considered to be usually human subject concerns in this particular domain. Privacy boards, because it's a public health enterprise, it may well be that in many circumstances, HIPAA wouldn't be involved.
DR. SUAREZ: Yes, it wouldn't, but in some cases, actually public health agencies have gone an extra step in saying, "We are not covered entities, so we declare we're not, or we're not considering ourselves covered entities. But we believe that there is significant value in creating and using privacy boards, in making our determinations for how to collect and how to use health information." And so some state agencies actually have IRBs themselves, even though they are not covered by HIPAA, but they certainly in many instances are covered by research regulations that require IRB-type activities.
DR. BOTKIN: So clearly the IRBs are involved. We've not heard, at least in the mountain states region, health departments using any other privacy protection functions to look at these issues.
DR. SUAREZ: And then, my last question is about there's an issue of obtaining the action petition to do it. And then, the other big question and concern in many cases related to consent is, the longevity of a consent decision. And so, I wanted to ask you your perspectives on that. I know I used to live in Minnesota. I lived there for about 20 years, and worked there, so it has a very stringent privacy regulation that affects actually research and requires proactive solicitation of consent for research purposes, as well as consent for disclosures for treatment or payment-related functions.
And the big decision in the state back then was the longevity of each of these consents. And most common business practices was well, at least once a year, we will be requesting or asking a consent again to do this or that, the general kind of open consent to use or disclose data. So what's your perspective on the longevity, if you will, of the consent?
DR. BOTKIN: Yes, that's a great question and I don't know that there's been much discussion beyond the issue of should children who become adults have the opportunity or should there be a requirement to recontact those individuals, and get the informed consent of the then adult who contributed the specimens as a child. I think our focus groups and discussions with participants, they tended to favor that notion, that you would contact these people after 18 years and get their permission to continue to store the samples. I think, again, without much realization of the cost and complexity of that sort of expectation.
More broadly speaking, I just haven't seen that much discussion of this particular issue. I think particularly if you're using an opt-out approach, you simply allow that opt-out opportunity to extend, but I've not seen circumstances in which there's been a formal consent model that has required repeated positive consents for this type of distributed specimen or repository, simply because there's not that frequent contact with the individuals to make that a realistic expectation.
DR. TANG: Thank you.
DR. FRANCIS: Marjorie?
MS. GREENBERG: Thank you, and thank you to both of our presenters, very interesting and thought provoking testimony. I had a question for you, Michelle, and Walter actually asked part of my question, which was whether there was any direct communication with physicians. And of course, I think we're probably both of us had in our mind the experience in New York City with the hemoglobin with the A1cs. And you answered that and thank you.
I saw, it was on your slide, but we couldn't see what it actually said, and that was, "What should you do about this in the Child Health Report?" And what I'm wondering is, whether this initiative, which is clearly an impressive statewide initiative, is associated with, and particularly whether resources are associated with strategies for addressing childhood obesity. As you pointed out, everywhere throughout the state, there is a problem or an issue, though in some cases, more than others.
And I guess this would be the longer term research, but whether by if there are initiatives such as increasing healthy food choices in the school or more physical activity in the school or some of the other strategies I know are being used, whether there's any evidence that, by informing the parents of this and making this such a visible statewide initiative, there's more receptivity to participating in these initiatives or addressing them. I guess it might be a little early to know that, but obviously at the end of the day, that's what we are looking for, would be to decrease childhood obesity. So I'm just wondering what your experience or thoughts are on that.
MS. JUSTUS: Right. Yes, we actually here in Arkansas have said that we've halted the epidemic, so we're not continuing to have an increase, which the rest of the country has. But there are definitely other components of Act 1220, I just go on the BMI piece of it. But one of the pieces of it is to have a child health advisory committee, which is a state appointment committee that addresses those very things in schools. So we have actually done several things. One is that we have very high nutrition standards in our school for vending, for a la carte and things that are sold within the school day. So actually, a lot of the changes that have just been nationally are in the process of being changed, we have already been doing here in Arkansas.
Another piece of that is that we actually did make recommendations to increase the amount of physical activity and physical education in our schools. Unfortunately, because it was an unfunded mandate and schools already have so much on their plate, a group of people have took that back to the legislature and actually had that overturned. So we did have increased amount of minutes for a short period of time, but then, it was actually taken back down, so it was decreased back to the original state. So we're having to be creative and come up with innovate ways to address this issue.
Physical activity and education is one that we've really struggled with a lot. And actually, we have a program that started, I guess, the first year of implementation has been this current school year. And another group will start next school year, but it's called "Child Wellness Intervention Project," and it's funded by the Arkansas Tobacco Settlement Commission. And basically what it is, is the schools that get this grant are required to increase their number of physical education and activity minutes from 60, which is state law for elementary schools and middle schools, and they're required to increase that to 120 minutes per week instead of 60.
So we're starting to do that, we're also evaluating that project to see what the outcomes are of that. So we're doing many different things. We also have a program, and I don't want to take up too much time, but we're also working on an initiative called Joint Use Agreement, which is funded by our state through Tobacco Excess Tax Increase. And that is the grant program that funded to a school and to a community organization to partner together to open facilities after outside of school hours, for the community to use for increase physical activity. And we're also trying to figure out how to evaluate that. It's a little more complicated because you have people coming and going, and it's not a set group of people to evaluate. So there are other efforts in place that we're trying many different things to see what may work.
MS. GREENBERG: Thank you.
DR. FRANCIS: Thank you very much. I think we've come to the end of this portion of the panel. What we're going to do is take a 15 minute break. And in the last hour of the day, we are going to be inviting everybody to participate in thinking about lessons going forward, so we'll hope that you, Michelle, and on the phone, I don't know if that's possible, and Jeff, could be able to be around the table later today, as well, 3:00, okay? And a 15 minute break and we'll be back at 11:00.
(Break)
DR. FRANCIS: So we have one addition, Seth Foldy from CDC, our liaison, thank you very much. And I'm going to turn it over to Sallie, who is going to be chairing this session.
MS. MILAM: Okay, we're going to start our panel two. We'll focus on data management, governance and uses. Today's been just incredibly exciting, and I'm looking forward to hearing from the next three individuals. We have Staal Vinterbo on the phone. Dr. Vinterbo, are you there, are you with us?
DR. VINTERBO: Yes, I am. Thank you very much.
MS. MILAM: Great. And we have Denise Love here with us in person, and Rosamond Rhodes. I thought what we could do is to let each of the speakers give us a very brief bio, and then perhaps ten to fifteen minute presentation. And we'll go in the order of the agenda, and then we'll open it up for discussion. So Staal, if we could start with you.
Agenda Item – Panel II Data Management, Governance and Uses
DR. VINTERBO: Okay, a brief bio. So I'm a computer scientist by training and I'm currently an Associate Professor in the Division of the Biomedical Informatics here at the University of California, San Diego. And by main interest in machine learning and privacy, preferable in combination. So yes, that's a very brief bio.
MS. MILAM: Staal, we're having trouble hearing you. Are you on speakerphone?
DR. VINTERBO: Okay, I just turned off the speakerphone; is this better?
MS. MILAM: That's a lot better.
DR. VINTERBO: I'm a computer scientist and I'm an Associate Professor here at the Division of Biomedical Informatics at the University of California in San Diego. And my main research interests are in machine learning and privacy technology, so that's a very brief bio.
MS. MILAM: Great, and I think we have our slides up on the screen, so if you just want to let us know when to advance, we'll be able to support you here on this end.
DR. VINTERBO: Okay. Good morning, everyone. So what I am going to be speaking about today is whether there are limits to privacy preserving sharing of data. And my main take-home point, if you advance to the next slide, take-home point, is that in general, a purely technological solution to privacy preserving sharing of patient data might not be possible. And before I go into this, why that is, let's look at the current state, if you advance the slide, please.
So currently, sharing of data is practically impractical terms done in three different ways, and this is governed by HIPAA. It's the complete sharing of data, including Protected Health Information, PHI, and then there is the limited data set, which is an almost de-identified data set. And then there is so-called fully de-identified data. And the two first sharing types require oversight by IRBs.
And what do we mean by de-identification, and this is specified by the HIPAA de-identification standard. And this standard has two alternative formulations, as most of you are aware of, I assume. One is the Safe Harbor, which demands the removal of 18 predefined information items, all of which are either explicit identifiers, like Social Security numbers, or can easily be combined to form identifiers of data subjects.
The other option is, or the other standard option, is the statistical standard, so called. And essentially, it says that an expert declares that the re-identification risk in the data to be disseminated is very small. So what usually is the case is that overwhelmingly, the Safe Harbor standard is being used currently to de-identify data.
And there are some problems with sharing data currently, and one of them, if you advance the slide to the next slide headed "Problems", is that this IRB oversight is costly. And since the researcher has to write an IRB protocol, submit it and wait for approval before any research can take place. And depending on the institutional culture, this might actually be quite time consuming and painful process.
On the other hand, the institution or the IRB have to process this protocol and administrate it, so there's also a cost incurred here. Furthermore, it is difficult to do this kind of thing across institutions, because they have two individual IRBs and requirements are such that you have to have collaborators, and both your collaborator and you have to go through the same administrative process.
And from a technical standpoint, if you advance the slide please, de-identification by the Safe Harbor yields data with limited utility. For instance, geographic information that is specific enough for epidemiology studies, for instance, is removed by the Safe Harbor requirements. And other types of limitations and utility of the data that has been de-identified with the Safe Harbor, has been pointed out in the literature.
And secondly, de-identification by the Safe Harbor does not really prevent re-identification, so it's not even sufficient for privacy. And the combination of these two things is from a de-identification standpoint, the major complaint these days. And the problem with de-identification by the statistical standard is that the statistical standard is so vaguely defined. Literally, it says a person with appropriate knowledge, and then using appropriate tools, determines that the risk of re-identification is very small. So this type of statement is so vague that it just doesn't really lend itself to consistent quantification. So very few people use this standard in practice.
And one of the main points is also that, inferences about sensitive information can be made without re-identification. So one can make an argument, which I will do now, that de-identification, whether you use the Safe Harbor, the statistical standard or some other type of de-identification formulation, is not really sufficient for providing privacy that we would like to see, so called what I like to call "believable privacy."
And abstractly speaking, this is because de-identification has a directionality from data to identity, and it is this one-to-one association of data to the identity that de-identification is designed to disallow. Now, it doesn't really say anything about going the other way, so if you know someone already, you don't really need to de-identify. And we have to, as an example, please advance the slide, hello? Okay, I'm still there.
If you take a look at this slide here, many institutions provide a service for their researchers that allows them to query how many patients that fit a particular pattern they have in their data repository. These queries are often called "count queries." So here is an imaginary example of such a query interface. And I am querying for how many patients that have secondary diabetes are of age between 30 and 31 and are male, that my institution has in its data repository. And I get a count back that says "three".
Now, to this query, I add that they also have HIV, that they're HIV-positive. And again, I get the count "three" back. So now, I immediately can infer that anyone that has secondary diabetes is age 30 and is male, also is HIV positive, and I'm not re-identifying anyone. Say my neighbor, Bob, just told me yesterday at his 31st birthday barbecue that he has secondary diabetes and he lives right near to the hospital, so I know that he goes to this institution. So now, I can immediately, because I know Bob, infer that he's also HIV positive.
And note that none of these items that I'm querying about, also that are included in the HIPAA 18 that are supposed to be removed, none of them are uniquely identifying. And since there are three or "N" that fits both queries, I'm not re-identifying. I can't tell who it is uniquely, so there is no re-identification involved at all. But I know Bob, so this is an example of this insufficiency.
Now, a point of discussion is, if you advance the slide, please, is are these insufficiencies of de-identification too isochoric to be of practical concern. And currently, there is this discussion going on where some of my colleagues, they claim that, "Well, we think so." So it's not really of a practical concern because usually methods do a little bit more than the standard requires, and so on and so forth. And the arguments that are presented are sort of an empirical nature, if you wish.
So for instance, an empirical study, so a re-identification study, sort of, "Oh, we were able to re-identify X percent." So now, if this X is very small and you can sort of try to argue that, "Okay, so this is comparable to having an airplane disaster happen to you while you're flying," which is very small. And without discussing the ethics of it, you could say that's acceptable. But it is not really a valid upper bound because if you are not able to do this, it doesn't mean that someone else is not able to. An argument such that it requires an expert to do this, I don't think are really very found.
And the other thing is that, okay, we haven't really seen media attention around any problems with de-identified data, so we can assume that nothing has happened, because it should have, right? If something wrong had been done, then the media would certainly have picked up if it was a really big problem, because we see media attention about personal health information being lost and laptops going all the time. And to this, I ask you to note that breach reporting exempts de-identified data from a regulatory standpoint. And there are no tracking requirements for de-identified data. So if you go to a bank and you are denied your loan application, you don't really know that it is because someone re-identified you or identified as being in a cancer registry, and therefore, you're a too high risk for this loan.
And what could a possible alternative be, if you would please advance the slide. So I think of the ideal for individual privacy, note that I'm saying individual privacy here, is that information is privacy preserving if what can be learned about any individual is independent of this information. So the consequence is this, is that we are allowed to share information about the populations. And also note that this implies de-identification, and also protects against my example with Bob. And it's a very strong requirement for privacy, but it allows very detailed information about the population to be disseminated. Now, unfortunately, if this independence is taken in a statistical context, complete independence is not feasible, because this requires an infinite data set.
If you'd advance the slide, please. But there are some practical approaches and definitions that go a far way towards this ideal, and one I'm going to present briefly is that of differential privacy. And this differential privacy bounds the change in the likelihood of learning anything about an individual by his inclusion in the data. And it is a property of an information access method, as opposed to a property of data, and because it is much easier to prove quantities about methods than it is to prove the properties of data.
And there are access methods to data that provably guarantee differential privacy. And I'm going to present a sketch of one on the next slide, if you would please advance it. For this count query problem, basically a blue Bob here, I have a particular query I'm asking. And the counts I get, if Bob is in the data set is X, and if he's not, then I get Y. And the difference between X and Y is at most one.
And if I add noise to the responses, X and Y, I get a probability of returning an answer with a density that's given by these two halves, centered on X and Y. And the differential privacy is the ration between these at any point X. And if I use a particular noise that looks very much like these halves here, then I can guarantee that this ratio is never going to exceed a particular bound. And this is very important because it emulates, or at least it approximates, this ideal of independence. And it is provably boundable, so you can say something quantitative about it.
But of course, nothing is for free, so there is a fly in the ointment, and here is a very important point, is that this research around this suggests that there is a general property of a finite privacy budget, meaning that there are only a few trips to the well of information that you can go before violating privacy. And this is for the count queries, so if you had noise, you can ask the same query a bunch of times, and then you can average out the noise and find the real answer, which is the right little graph here.
And so, if you think about it, every new query extracts a little new piece of information from your data. And if some of the data that is finite, in a finite data set, is sensitive, sooner or later, you will start extracting this sensitive information, so that's kind of the intuition behind this idea. Furthermore, the more information you have about your patients, the smaller the budget is, the fewer queries you're allowed to ask before you enter this sensitive area, if you wish.
And this has, for instance, severe implications for genomic data, because whole genome sequences contain an enormous amount of information. So if you want to release information about genome that capture its entirety or are useful for general analyses, you will have a very hard time doing that without jeopardizing privacy, because of this result.
So how can we deal with this finite budget, if you advance the slide, please. So one option is to use all the budget up front, and to create a representation of this information, that you can then ask questions of in perpetuity. And that means that you're never allowed to access this data again in a privacy preserving manner, in order to guarantee privacy, but you can access the extracted information, though. Different uses might need different information, so it's not really the information that you're extracting by you spending the budget up front, might not be suitable for all types of analyses. And as I pointed out, for high dimensional data, such as genomic data, the budget is really very, very small. So you're not able to extract much information.
Or which I think is in general a more feasible approach, or a more general, at least, is to leverage in the environment in which you allow these queries to happen, or these questions or data access, information access, to extend this budget. And the principle is like in medicine, is to substitute some treatment for prevention. And this treatment could be trust, so you're sort of not requiring as stringent privacy guarantees because you trust the person you share this information with.
And to do so, this trust requires that you to know who you're sharing the data with, and that you're able to detect any misuse of this trust or breach of trust, and who is doing it, and that you have a mechanism of effectively sanctioning the perpetrator. And this is more a regulatory question around, for instance, data use agreements. And I think technology should be developed to support this kind of process, as well.
So if you advance the slide, please, my conclusion is then that de-identification, regardless of how you phrase it, as a definition of privacy, seems insufficient for believable privacy. And current theoretical research suggests that there are limits to truly privacy preserving, sharing of data, using technological means alone. And if you advance the slide one more, and I'd just like to acknowledge my collaborators, funding sources. Thank you very much.
MS. MILAM: Thank you, Staal. We'll go onto Denise.
MS. LOVE: It's a pleasure to be here. My name is Denise Love. I'm the Executive Director of the National Association of Health Data Organizations. I won't have slides, so I'll speak from my testimony. And I am reflecting that Utah is well represented here. I'm wondering if it's a reflection of our expertise, or that we just want some spring, because the weather has been beautiful here and it's been a pleasure to actually visit spring.
Anyway, as Executive Director of NAHDO, I work with states formulating data collection policy, specifically around healthcare data sets. My bio is that, well, a long time ago, I was nurse. Then I got into healthcare finance and manage care policy. I served nine years at the Utah Department of Health, developing and instituting their initial hospital reporting, HMO-reporting systems. And now, through NAHDO, I work on the ground with other states, doing similar work. And so I represent about at least two decades of this work in data policy.
NAHDO is a non-profit membership and educational association. It was established in 1986, spun off of the Washington Business Group on Health, at a time where they were escalating healthcare costs, and purchasers wanted some transparency and accountability, and I feel like we're back to the future here. But NAHDO, since that time, has developed and worked with states as they advance their reporting agendas. I believe that NAHDO and its members have been at the forefront of putting large scale healthcare data bases together, multipurpose or repurposing the data, and also have been at the forefront of releasing comparative reports to the public on providers.
Today, there are 48 states with in-patient hospital discharge data reporting. Forty of these states have mandates and operate under mandates. We're seeing a new kind of data system emerge, which is bringing up some new dynamics and conversations, and that's all payer claims databases. And those are a little more complex in that they bring in eligibility, medical claims, pharmacy claims, data into one agency, from public and private payers.
Our members have been linking their data sets with the hospital data sets with vital statistics, cancer and other registries to fill some data gaps as they attempt to measure outcomes and population metrics and variation. The states have long relied on the release of public data sets, research data sets and interactive web query systems to disseminate the data. Again, these data sets are state funded largely, there's no federal funding. So we are seeing variation in how some of the dissemination occurs on the ground.
So I welcome this conversation. I feel it's quite timely and I'm pleased to be here to pick your brains and see where we might want to go, because we are demanding more of our existing data. And the hospital data and some of the other large scale data bases are our workhorses, yet, we're falling short, and the data are falling short. No single data source that we collect today captures all the information that we need. These information gaps, as I said, are being filled through strategic linkages across data sets, but these linkages pose huge challenges and I'll talk about that.
So we need to think about how this linkage occurs. We need standards for how the data are captured in the first place, because we're seeing some of this variation inhibit those linkages, and inhibit the integration of the data across the system. And then, we're seeing a huge discrepancy in release practices, by data agencies in states and by data source.
So in this conversation, we believe that lessons learned through NAHDO and its members can inform future data policies to improve our national information sharing and infrastructure. The premise is that if we can solve some of the issues we're having around administrative data, even out some of these practices, it is my hope that when we get to that magical time of clinical and HIE and EHR and whatever you want to call it, we can draw on those lessons learned and those policies, because it's just going to make our data exchange sharing much more complex. I listen to the conversation on BMI and I sat here thinking, "Yes, there is a hope that the electronic record will capture BMI, among other things."
But what happens when we take our administrative data and link to that for outcomes and cost effectiveness? I think it just explodes. It's not a single data set anymore. It becomes a melded data set with the added complexity, so I think this conversation just needs to happen. So I'll talk a little bit about the need for the standards in patient and provide our identifiers, because that's causing some grief on the ground. Again, the need for improvement in data sharing and data exchange, and then some recommendations that we came up with.
So on the collection side, we absolutely need identifiable data captured on the front end. Some states have done a workaround by saying, "We'll collect the de-identified data from the providers or payers," which just, as I call it, neuters the data up front. So what you're going to do with it is limit it from the get go. I understand politically and legally why that might happen, but we really need to capture the robust identifiers at the front.
Even when the states are collecting these fields and data sources, we're finding different formats. The same data sets vary in the formats across states and jurisdictions and data sources. Again, that hinders the analyses, linkages and applications. One example that I'll bring up is, many states with their hospital data, have relied on Social Security number of the patient, as one of the identifiable fields. Again, I call it the "demographic suite of fields," of patient fields.
The Social Security number, when combined with the date of birth and the date of admission, date of discharge and gender and some other fields, it does create a unique record. But now, we're hearing from payers and providers that they are no longer asking for Social Security number, which wasn't perfect to begin with, but it will just diminish the availability of that field. So compounding that, then you have many of the discharge data systems where concerns of privacy never collected in the beginning, patient name or patient address. So as the Social Security number drops off, what's there to replace it?
So when we advise with states, they could back and change their rules and say, "Now we have to collect the patient name." The problem is, having that conversation with legislators in this day and time poses huge risks. So that we find ourselves sort of punting at this point. And then, if they do collect it, we're finding these names and formats vary. Cancer registries do not equal discharge data fields, and again, the linkages are a little noisy when you start linking with registries to say, "Define an episode of cancer care," and look at other outcomes of interest.
So if we can get address in hospital data or in another public health data set, and we're lucky enough to do that, what we're finding is that they're capturing often just one field. But that may be a P.O box in a rural area, which doesn't help with our geocoding. So distinguishing between the patient's billing or mailing address and their residential address where they reside is important for exposure, analysis and other types of geocoding. But again, having that conversation with legislators is a little prickly and a little tricky right now. Then if we have the cleaner data, then we can get smart de-identification and encryption and algorithm, and that is our hope, but we're not there yet.
Then, we get to the release aspects of data. So even if you have a perfectly captured data set that's identifiable, and you have all of the unique fields and you were able to get address, that data is not being shared, or not being shared very well, even with a public health department. Because of sensitivity now, you've added power to your data set, you've got say the holy grail of the patient demographics in your hospital data set, for example. Well, that just means that maybe you're not going to share it with anybody, or very few people. So we're seeing this lockbox mentality of, "We're going to keep it under lock and key until we figure out what to do with it." And this is where I'm going with this, we aren't figuring that out very fast. But NAHDO gets quite a few calls from agencies who want to share the data.
Now, you could say IRB, it could go to an IRB, but not really, because some of this linkage in public health departments isn't bona fide research. I mean, these are enhancements of data bases, and some of the applications for evaluation are gray areas, so not bona fide research. So it is pretty uneven, some states have figured it out and others have not. There may be legal restrictions, as well, in the state, but I maintain that most often, it's fear of what could happen if the data are shared, but also lack of resources. Many of our data agencies don't have any more people, and then the light is barely on. And these kinds of data sharing initiatives are hugely intensive, in terms of workforce and figuring it out across the system.
MS. MILAM: And you have about five minutes, please.
MS. LOVE: Okay. Many agencies do deploy statistical and management controls to release their anatomized data. We are seeing the one-way hash encryption that some states have applied and have been using for some time. All states will aggregate their fields, such as dates, and I won't get into the mechanisms. We feel that these de-identification methods in play in most of the states that NAHDO works with have proven to be an effective first line of defense to protect patient identity.
When combined with data oversight, data use agreements that stipulate authorized uses, I think the states have created a workaround around some of the issues. But still, we can do better and we must do better as we try to repurpose our data and get more utility out of it for the public's good. And I won't even bring up FERPA and health and epidemiology, that is for another time, another place. But that's a classic case where you have this huge silo, but a huge need to share with the public health department.
So again, we're seeing a huge amount of variation and practice, and we're seeing huge gaps in information about populations, and we think that we can do better. So NAHDO welcomes a national discussion, led by this committee, around these complex issues. We would like to see greater cooperation across states and data sources. And we need to maximize utility of existing data because we're not going to get too many more data sets funded and collected in this day and age.
So we need messaging, we need, and I heard that earlier today, policy makers and the public, what is the message? What is the utility? What's the value proposition? Why are these fields important? How do they help the public good, because society does benefit, and so we need a consistent and deep message. We need to encourage states and others to have uniformity and consistency of their demographic fields across the public data sets, in format.
We will be watching HITSB and what they're doing with the demographic model. We know that some of the new names are long and hyphenated, and some of the existing standards don't accommodate those fields. One of the examples that we brought up is a project underway by CDC and the National Program of Cancer Registries and NAHDO, and we've been harmonizing the discharge data bases with the cancer registry databases. In some cases, the hospital systems will change their standard and sometimes it makes sense for the registries to change theirs. But the belief is, harmonization across these data sets will facilitate linkages of cancer registries and hospital data sets, and it will reduce provider burden to report.
I don't think we have time to get into the huge issue of provider identifiers, but that is another kind of linkage and standard problem that's wreaking havoc, as states try to drill down in their data and assign attribution to the provider and to the physician, and messaging around the importance of a unique number is critical. We believe that de-identification will continue to play a huge role in data exchange, but we need smart de-identification. We need expert panels to help us define an analytic framework, that puts some sort of intelligence into the de-identified data sets that are linked. For example, if we could do a better job at the hospital discharge data level, by having the data agency that has the raw data add smart flags. This was a readmission, this was a readmission to the same hospital, you wouldn't need as many linkages. You would have some intel embedded into the data set, and you could send a de-identified data set out the door, without having to have the specific identifiers on that in every case.
So we also need to redefine or rethink how we talk about PHI. PHI is changing, as the field of genetic and biosignature data expands, and we see more sensitive data. And so, some clarity is what it is, what it is not. Other messaging information, model exchange policies come up because we are not doing a good job in exchange. And so, we really need to make it a guidelines or some sort of best practice, and highlight how it works and what the benefits are. We're seeing that geocoding enables us to connect the dots, but this added power creates heartburn because people are worried that it will identify the patient, and it does inhibit data exchange.
We have some legal problems with interstate transfer and jurisdiction exchange of data because again, a readmission in Maryland needs West Virginia data to really look at those readmission rates, but the legal prohibitions and political concerns inhibit those kinds of exchanges. Again, I sometimes think of PHI as we mix up the clinical world, so where there's a clinical end point and an intervention, you absolutely need that patient identifiable information.
NAHDO and its members and the users of our database really use anatomized data sets for statistical and research. We need to know it's an unique individual, but not who that is. And sometimes, I think those conversations get blended together. So I offer NAHDO's expertise in the field to join this discussion, and think of ways we can enhance our data sets. As we see, all payer claims databases take off the issues of identifiers, de-identification, methodologies for encryption are just adding more complexity, and that isn't even counting all the clinical data that is about to be merged out there. So I will conclude my testimony, and thank you again.
MS. MILAM: Thank you, Denise. Rosamond?
DR. RHODES: Okay. So a little bio, I'm a philosopher at Mt. Sinai School of Medicine. I'm Director of Bioethics Education. I teach our annual Research Ethics course. I'm also Professor of Philosophy at CUNY Graduate School and Professor of Bioethics in the Union Mount Sinai Bioethics Program, where I'm Associate Director. So recently, I've been working on an NIH project on the human micro biome, and privacy and confidentiality have been big concerns for us. So I'm going to approach this issue a little bit like a philosopher.
Okay, so privacy. So what I understand it, privacy is a concept from ordinary morality, common everyday morality, and it's different from confidentiality. Privacy identifies areas that are safeguarded from the scrutiny and intervention of others, and it's marked off from public space by natural boundaries. It's protected from the intrusion of others by laws, social practices and social sanctions. So domains of privacy are things that are separated by natural boundaries, so what's in my thoughts, what's inside of my body, what's inside of my own bedroom, what's inside of my home or my computer or my mail, we could go on and on with the list.
Now, privacy and common morality is a protection, but it's not an absolute protection. It's primarily a protection from unwanted government intrusion, and exceptions from privacy protection are allowed for the sake of the public good. So we do allow the police to break into your house if they think something nasty is going on that violates serious laws. They might even be able to search your bank accounts and other records for the public good or public safety.
Now, aside from this protection from government intrusion, the task of maintaining my privacy is largely left in the hands of individual citizens. So privacy, in common morality, is not a guarantee, except it's a standard of protection against the government. And if you think back to movie pictures I liked, "Rear Window," the Hitchcock movie, you see people looking through the windows that other people leave unguarded. If you want your bedroom kept private, close the curtains. If the windows are open, people are welcome to look in, and nothing terrible is done.
Now, this picture is not a mistake. It's actually, I think, my most important slide. So if you think about children riding bicycles, if you want to protect your child from harm, what would be your bicycle riding policy? So if you really want to protect children from harm, you might think they have to wear helmets, they have to stay on the bike path. They shouldn't go riding alone, they should go in company. But you know, they can really still get hurt if they wear helmets or if they're on a bike path or even if they're in the company of a parent. So if you're really serious about protecting the child from harm, you're going to say, "No bike riding."
Now, if that's your policy, "No bike riding," you can then ask, "Is that a good policy?" So a good parent, I think, encourages their children to ride bikes because you want the child to learn other things. You want the child to learn to explore the world, to socialize with other children, to manage risks. So for a good parent, you provide safeguards, but you recognize my child could be hurt physically, but we get these other benefits. And I think good public policy, with respect to anything, has to balance the goods with the harms, and come up with a reasonable course that navigates both of these concerns.
So important questions are, "What would be a good policy? What would be a reasonable policy?" So when you come to protecting privacy, such as HIPAA rules or absolute guarantees of no breaches of privacies, you can ask, "Are these protections reasonable or unreasonable?" And failure to take into account of other reasonable and legitimate social and personal goals, I think, is being unreasonable. So when we collect data and mass data sets, of course, somebody could be re-identified and they might not like that. They might choose otherwise. But I think in constructing our policy, we want to consider real important social and personal goals, like advancing science or protecting people from harm.
And it's also important to point out that when we say we must absolutely protect privacy, we are being paternalistic. What I mean by that is we're saying, "This good of privacy trumps everything else. Forget about everything else and I'm going to protect you, whether you want to or not." Now, Madison Powers at Georgetown calls this kind of paternalistic attitude towards research "Marxist" because big brother knows what's good for you and is protecting you. And I'm suggesting, with Madison Powers, that this paternalistic protection of privacy is unreasonable and also unjust.
So if you ask me personally, I may not care a great deal about protecting the privacy of my samples. At my institution, we have a biobank and I have signed up for it, and what they say at the beginning is, if you sign up for it, we only accept people who have a medical record ID. And that medical record ID is going to be linked with your biobank sample, and it's going to be used in research. We don't know what it is, so we can't tell you what it is, and we're not going to ask you about it again. And you can always withdraw your unused samples, but not your used samples. But if you want to sign up, we'd really love to have you. And we even offer an incentive, I got 20 dollars for signing up.
So I don't care about people using my samples. In fact, I care a lot about I want it used as much as possible, because I want the researchers to find out about people like me, so what they can find out might help my children and my grandchildren. So I may care more about advancing biomedical knowledge than I do about the absolute protection of my privacy. And I may care most about helping my fellow man.
So confidentiality; so as I see it, confidentiality is a concept from the professions, and we see it occur in the priesthood and the law and medicine. And confidentiality is especially important because it relies on the ethic of those professions, and it gives people a reason to trust that the information that they share with these professionals will be kept sacred and shared only within the profession. Now, think back to the cartoon diagram I gave you about privacy, and you'll notice the difference. So confidentiality identifies a space for professional interactions, where privacy is safeguarded from the scrutiny and intervention of others, and it's marked off from public space by constructed, non-natural boundaries.
So if somebody comes into the emergency department, they're going to be examined by the residents and the medical students and reported to the attending in the emergency department, and then they might be sent up to the floor, where they give their history to the physician who greets them. And that information is communicated with the whole team of residents and attendings and nurses and all kinds of other specialists, and to the pharmacy department, and the things will go for special tests and there might be surgery involved. So when we're talking about confidentiality, it's not two people knowing this information like in privacy. It's shared broadly and that sharing could go on through many buildings and many different spaces. And I think it's important to notice this difference between confidentiality and privacy. These are different concepts and we're very comfortable with accepting confidently in medicine.
So the question is about handling of research information. Should it be handled according to standards of privacy or according to confidentiality? So I think these concepts need to be distinguished from each other, and in the treatment and biomedical research, information about people should be treated according to existing standards of confidentiality that govern other medical information. For example, information in treatment needs to be shared with a whole array of people on a need to know basis. And I think the same should apply to research. So participant and public safety, as well as providing for the public good, may sometimes be more important than privacy.
So again, we can ask the question, do we want standards of confidentiality or standards of absolute privacy guiding research? And I think we've come down on the side of confidentiality, because confidentiality is already the prevailing standard in a lot of research that gets called by other names. So when we get the common rule, they carve out certain kinds of research that doesn't get called "research," and there, we use standards of confidentiality and it works very well. So all public health surveillance, if somebody comes into my hospital and they have SARS, it gets immediately reported to the Board of Health, with all kinds of identifying information because public health people need that information to track it. And we don't ask them for their informed consent before we share that information. It's necessary we do it and we accept it. It's also done standardly in hospitals and we call it "quality assurance" and "quality improvement," and we do it with registries, as well.
So in all of these circumstances, there is largely no objection, and also we already trust these agencies to uphold standards of confidentiality. Now, in one of my activities at Mt. Sinai, I've been involved in some research from the Emergency Medicine Department. These were studies called "Voices One" and "Voices Two" about community attitudes towards emergency research. So this is research that's done under the final rule, so research without informed consent. So it doesn't look exactly like what we're talking about, biobanks and sample banks and large data banks. But there is the similarity that here, you're talking about research where informed consent cannot be done. And our study was specifically focused on "What are community attitudes?" So we ask people "If, because of some health emergency, you can't give consent, who would you trust to make decisions for you?" And people said, "I want to decide for myself," and we explain again. "Well, what if you couldn't? What if you were unconscious? Who would you want to decide for you?" And they would say, "My daughter, my son, my husband, my loved one." And if you explain, "Well, we couldn't contact them. Who in your community would you trust?"
And we did this in multiple focus groups and then in large surveys, and people said not what you'd expect, not the clergy, not their political leaders, not their neighbors. The people who they said they would trust most would be health professionals. "I want health professionals making these decisions." And if you look at public health surveillance, well, then the Board of Health makes decisions about when should surveillance be done, what information should be gathered, who should get it, and we trust that this is largely done well.
When you talk about quality assurance and quality improvement, you have again boards in the hospitals of professionals making these decisions according to the ethics of medicine. And when you talk about registries, they are largely overseen by professional associations who are trying to collect information on whether this new hip replacement device squeaks or has other problems, and they want to track it. And virtually everyone is involved in these data gathering activities. It's all research, meant to guide future practice, so it is collecting knowledge to be used for others.
MS. MILAM: Rosamond, you have a couple of minutes left.
DR. RHODES: Okay, I'll go fast. I'm almost done. And we do it without any serious discomfort. So we've already talked about the need for widespread research participation, in addition to the general gathering data about obesity. We have on the horizon, human micro biome research, genomics, the promise of personalized medicine, and there are these new research techniques that will facilitate research that we couldn't have done before, so we want widespread participation.
And up to conclusions, so I've been arguing that when medical confidentiality is upheld, in medical treatment and research first, people are not harmed. And also, we should consider if we're thinking about harms and benefits, people are not harmed on the one side and you can get significant public good. And then, if you keep the desired benefits in mind, then with appropriate confidentiality limitations, data from biobanks and sample banks should be shared in order to significantly increase the research use of samples, identifying information should be limited to reflect the need to know, including the need to recontact people.
And where possible, and with informed consent, when samples are taken, material remaining from clinical uses and other research should be available for additional research purposes. And when informed consent is not available, there should be something like a process of consent, which is an institutional system, a board of professionals that meets and says, "What information should be shared, when and how and when it's appropriate?" And I'm done.
MS. MILAM: Great, thank you, Rosamond. Staal, are you still with us?
DR. VINTERBO: Yes, I am.
MS. MILAM: Wonderful. We'll now open it up to questions for all three panelists. I'll kick it off with just a quick one for Denise, and then we'll go around the room, we'll work the table. Denise, I'm wondering about your recommendation around guidance for data release and data exchange at the state level. I'm aware that NAHDO and others have inventoried and produced reports around different statistical disclosure methodologies, to de-identify or otherwise protect the data.
But is there guidance out there for states and public health who generally aren't regulated by HIPAA, that would tell them, guidance, how to select their methodologies, which methodologies to use, when is it adequate, when is enough enough, what data features can be released to this group versus that group? I'm wondering if there is anything out there that people can point to, and if there isn't, do you see a need for it?
MS. LOVE: There is nothing formal out there that I'm aware of. States share with each other, so the best practices are pretty good practices arising to the top, just through state to state sharing. But there is no formal, "This is how you de-identify a data set and methodology," and there is a great need for that.
MS. MILAM: Do we have other questions? Leslie?
DR. FRANCIS: Yeah, I want to address this to both Staal and Rosamond actually, which is in a way I think the two of you have somewhat similar conclusions, namely that de-identification isn't the way to go and that the way to think about protection is governance of data uses or misuses. So when you talked about dealing with a finite budget, detection of misuse, and when Rosamond talked about limiting to reflect the need to know.
What I'm interested in is, if you have further thoughts about either how to detect misuse, what would count as misuse. For example, the Havasupai thought it was misuse to have given their data for one reason, and then to have it be used for a different type of research. And what kinds of mechanisms there might be with respect to misuse prevention. This is all at the level of, we're not talking about individual opt-in, opt-out, the data are there. What we're interested in thinking about is, how to either decide what counts as misuse, detect it or prevent it.
DR. VINTERBO: Do I start off?
DR. FRANCIS: Sure.
DR. VINTERBO: So this is a very good question, and I think it hasn't been really answered. And if you think about detection of misuse, for instance, there are examples, as you pointed out, with the use of the data. This is fairly easy, well, in my mind at least, there might be things I'm not thinking of, but there are instances where this is easy to detect, because you wrote in your IRB that you were thinking of doing this, and you're now doing something completely different, and someone can detect that.
However, if you think of it in a context of the query to a database, and the example that I gave with this mechanism that allows you to question or query how many patients you have, the detection of your intent behind these queries and the actual information that you could actually distract from, a combination of queries, in the general case is undecideable from a theoretical standpoint. You cannot really tell what your intention was and what information you can compute out of this. So in this sense, it's a little bit of a pessimistic result, so this is the worst case. But I think arguments can be made for this kind of auditing for data use, that there are at least mechanisms that can allow you to filter out sort of use outliers, if you wish, sort of unconventional uses of information that could be audited by a human, that can make inferences that machines cannot do.
And so in my talk, I was limiting myself to sharing of data. I think there are ways of doing research where what you share is not data, but it can be information they aggregate that is extracted from a local context, and are then composited into a result that couldn't be derived from any single local context, so a sort of a multi-party computation, if you wish. And the extreme of that is sort of a very secure multi-party computation. And but this lists the extraction level, either up into sort of an informational realm and you're not sharing data anymore. Or you implement computational mechanisms that do provide privacy guarantees, while at the same time allowing computations to take place that employ all the information available, but not sharing it.
So but these are still fields under development and are not ready for employment to prime time, but this is kind of maybe something maybe we should think about when going into the future. So for the present, I think you are right that Rosamond and I share this view, and I unfortunately don't have a very clear technological answer on how to address the detection of misuse. And I think it has to be considered in specific contexts of what mechanism you use to access data, and how that can be audited and so forth. Thank you.
DR. RHODES: So I agree that it sounded to me as if Staal and I were very much on the same page. And also the focus of trust, as being the primary grounds for protection and also procedures, structural processes. So in our biobank, for example, we have two levels of oversight. So first we have a community board that includes physicians and people from our different populations, and a subcommittee of that is devoted to the biobank. And every project that wants to use the biobank not only goes through the IRB, but goes through the community board for the assessment of the appropriateness of the study, so that approves the study.
Then there's a separate only professional group that reviews the study and decides which information should be released to the researchers. So there's the biobank sample, the genetic DNA as a sample or as just the data, and then it can be linked to the medical record, which gives you a great deal of demographic information, and they're deciding which of this demographic information is relevant to your project. Nothing is off the table, it's all available, but you have to demonstrate that you need the information.
Now, in terms of illegitimate concerns or illegitimate uses, my ears perked up when I saw the words on the paper. I perked up about the Social Security number. I can't imagine any need to know, the Social Security number in particular, and then even if it facilitates research, I think there you have a big danger of people's identity has been stolen, and it has gotten them into huge economic problems. So I'm really concerned about the Social Security number.
And in our micro biome research, what has come out again and again is the concern that people have that their research information will be shared with law enforcement or immigration. In our community, there are a lot of people who could be illegal immigrants, and while they'd be eager to participate in the study, they're concerned about who gets it. And our biobank is supposedly subpoena proof. They've filed a certificate, but I think we need a national assurance, a real bright blind barrier to protect research information from being shared with law enforcement and immigration.
MS. MILAM: I have Walter and then Paul. Walter, did you have a question? I couldn't tell.
DR. SUAREZ: I think Paul went first.
DR. GREEN: Sallie, would you add me to the list?
MS. MILAM: Sure, got you, Larry.
DR. TANG: Thanks, very interesting panel again. I'd like to sort of compare Rosamond's presentation with Jeff's around this whole consent and use for other purposes, because I think you had sort of somewhat contrasting views.
DR. RHODES: I thought we were on the same page.
DR. TANG: So you used the word "paternalistic," and the way you used it was, you didn't want somebody to say you couldn't do things from a privacy perspective. You could almost flip that and think paternalism could also mean we to somebody and this guy will decide how we will use your data. So it's interesting you could actually have two different authoritative ways of looking at someone else making a decision for you.
What I thought was interesting about Jeff's presentation was, you know what, actually the majority and the super majority of folks, when given information which satisfied their need, their desire to have choice, and still yet contribute to public good. And that's where I saw your paternalism said, you know what, we really need to use this information for the public good. And really not necessarily, I thought I heard, we need to check with folks.
Now, you talked about why the use of your individual tissue could help other people like you. What about, and how do you reconcile this, if studying your tissue sample informed others about other people with similar tissue samples, that could be used for whatever those other people want it to be used for. It could eventually come back, and Jeff talked about the group risk in underwriting, for example, or in other things that may come back to harm the other people, even if it's not you. How do you figure that into the thought and your description of paternalism in how people should be doing some of these things?
DR. RHODES: So my understanding of paternalism is what a good parent does, through acting for the good of another, even when they don't want you to do it. So when I'm taking this information, my information, when I come into the emergency room with SARS and it gets reported, that's not for my good, that's for the public good. So it's not an instance of paternalism, it's a different principle. It's justified by the public good as opposed to, "I have to protect your privacy, that's for your good." So I'm distinguishing those concepts.
And I think making privacy protection so vigorous is paternalistic because what you're saying to everyone is you really want your privacy protected over and above everything else. And I think Jeff's data shows that, while people like to be asked and like to be participants in the decision making, when it comes down to it, what they care mostly about is, if my child has a problem, I want to protect my child. And if you can learn more things to protect my future children, my neighbor's future children, stranger's future children, I think it's a good thing and it's worth doing, even if I don't get to consent. So I think these are slightly different concepts.
MS. MILAM: Walter?
DR. SUAREZ: Yes, thank you to the presenters, fascinating discussion on new areas in privacy and confidentiality, I suppose, or same areas looked at from a different view. I wanted to create some distinction. It seems to me that we're mixing a number of aspects, and I wanted to separate two important areas, because I think privacy and confidentiality, even though it applies directly to them, they apply a little differently.
One is public health, and public health has functions and responsibilities and activities that are completely separate from the other activity, which is research. And I think we've got to look at the two and we've got to look at the elements around privacy, the collection of data in the first place, and how public health and when and why and where and all those things, can public health collect data. And then, the same concept around researchers. And they're different, because I think it's important to distinguish them because I think that public health responsibilities are quite distinct in reality, and are a community good that is also important, as well as the research side a community good. But it's a different type of community good, if you will.
And then, the other element in my two-by-two is the release of information or disclosure. And so, public health ability to disclose information, whether it's through reports into the public or into entities that identify whether it's population groups or individuals, as in providers or systems or whatever, never really identifying individual patients certainly, or consumers. But that disclosure function and release function is different from the research side, too. And so, I wanted to explore that distinction in your minds, in the three of you, the presenters, because I think when we talk about privacy and confidentiality and those concepts, and we try to bring them together and link them in public health and research particularly, it creates some confusion, at least in my mind. So I wanted to explore that distinction and see if you agree, there is an important difference that need to be taken into account when defining policies around privacy and confidentiality, how they apply to public health versus research.
DR. RHODES: I can talk about it, because I was the one who challenged the difference. So we get this sharp line coming out of the common rule. And I think conceptually, there is not the sharp line. So first, the focus of public health, everybody says, is the public, and everybody says the focus of treatment is the individual. Not completely. So when you have a lot of patients in the doctor's office, and one of them is coughing, you worry about the others. And in the hospital, we make decisions that are not always for the good of the individual, who gets into the ICU, who gets out of the ICU, who gets put into a room with special airflow because they might be contagious. So we're making these decisions in the context of treatment, with regard to the bigger public.
And in public health activities, we're also focused on the effect on the individual of a policy. So Typhoid Mary, we all know her name, and she got put on that island because she posed a risk to others. And when we have contact notification programs, we take care to protect people's confidentiality, even though it's not absolute. So there's a constant balancing by public health, as well as by clinical medicine, both the public and the individual. It's more common in public health, less obvious in treatment, but I don't think there's a sharp difference.
Also, when you talk about these activities like surveillance, what is your goal? Your goal is obesity screening, whatever it is, your goal is an intervention and you have a hypothesis. Obesity leads to shorter life expectancy, other health problems, or whatever the hypothesis is, you start with the hypothesis and your method is collecting data in order to reach a conclusion and decide what to do. And we do that in clinical medicine, we do that in public health. I don't see a marked distinction, and I think that there are a couple of sharp lines that get created by the common rule that conceptually make no sense. The difference between innovation, doctors can try an FDA-approved drug for any new use. Bless your heart, you're free to do it. But if you want to study it and learn something, then you have to go through all of the rigmarole that we all know.
Now, is there a sharp distinction? I could tell you story upon story, where you'll see that distinction gets blurred, because when the doctor has the idea of helping this patient with this intervention, there's a hypothesis. This is just speaking very generally, and you're going to observe what happens and try to draw a conclusion from it, and that conclusion is going to guide your future treatment of other patients, and it will guide what you teach the residents and the fellows and the medical students.
MS. MILAM: I'm going to have to cut you off, Rosamond, I'm sorry. We have two more people to respond, and Larry has already indicated he has a question and we have five minutes. So with that said, Denise and Staal, do you have anything that you want to add?
DR. VINTERBO: Yes, really briefly, that I think we often need to distinguish between the clinical care and research. And I agree with the questioner's assessment that there is a distinction between disclosure for public health and disclosure for research. And I also would like to comment really briefly on Rosamond's sort of analogy between, or a statement, that privacy is only for protection against government, which I don't really think is necessarily true. And yeah, that maybe confidentiality could also be viewed as a mechanism to provide privacy, and this seems to be how it is being used in the professional context that she outlined. So yeah, that was very brief. Thank you.
MS. MILAM: Denise?
MS. LOVE: When it comes to making data policy, it is very important for the states to distinguish between collection and release, and we are very clear that they should not really be lumped together. So you collect very detailed information, be it Social Security number, and we could talk about that all afternoon, but that does not get released. And so, those policies have to be clear.
MS. MILAM: Thank you, Larry? Are you still with us?
DR. GREEN: I'm sorry, am I there now?
MS. MILAM: You are.
DR. GREEN: Sallie, I was saying that I'm sitting out here, really struggling, with trying to consolidate this very productive morning and these great presentations, and to sum up these conclusions that align with the jurisdiction of NCVHS and the interest of our subcommittees. And what I would like to ask your indulgence to do is, I'm going to try to make up right now a couple of sort of sum up these statements and invite the three presenters to correct them in dissent from what I'm about to say.
It goes something like this, what I've been hearing is that we have an emerging world of health-related information that has already exposed weakness and insufficiencies. And the current law, the current rules, current regulations, current typical practices of insurers, payers, and doctors and researchers. And that this exposure has actually compounded challenges that were already large, to properly protect individuals and populations from harm, from health information, and sharing it, something like that. And that we're being presented with something that I would call nearly a stunning opportunity to reexamine both individual and population health information use, and that we're at a juncture in the country where it is really urgent to reexamine and consolidate a sensible approach to privacy and confidentiality.
So I need to stop here, hold that meandering in your thoughts, you three presenters, if you can, and I have a much simpler other summary conclusion from the morning, and it would go something like, "There is no sufficient approach resolving these confidentiality and privacy issues, using a purely technological solution." I'd like for you guys to disagree with those.
MS. MILAM: We'll start with Denise and then we'll go up to Rosamond and then we'll end with you, Staal.
MS. LOVE: I agree that we are exposing weaknesses and insufficiency with our current practice. There is a risk to populations, but I less agree, because I think from in terms of public health and state law, they've done a remarkable job with the protection, and I don't want that to be lost in the discussion. I just think we can do better. And I don't think technological approaches alone will solve the issues. I think it's much more sociologic and complex than just the technical solutions alone, so I agree.
DR. RHODES: I think we have already been treating a lot of our research data as under guidelines of confidentiality. And I think we do need to reexamine some of our research rules that make people jump through hoops to call to either anonymize data or to call it something other than human subject research, when they're talking about biobank and sample bank data.
MS. MILAM: Thank you. Staal?
DR. VINTERBO: Yes, I agree with Denise and also the statement made by the questioner. But I would sort of be a little bit cautious and say that just from a technological standpoint, I think the sharing of data is problematic. Whether this also applies to sort of the more aggregate sort of information content, that probably remains to be seen and I think there is a large opportunity for technology to help where sharing of data might not be possible. Some other form of collaborative mechanism can be used, so but yeah, I agree.
MS. MILAM: Thank you. I want to conclude with thanking our panel. Your presentations were fabulous and the discussion was really, really interesting. We're at 12:35. We're going to break for lunch now and we will reconvene here in one hour. Thank you.
(Whereupon, a luncheon recess was taken at 12:35 p.m.)
DR. FRANCIS: This is the third panel. Have we got people here on the phone? Maybe we can ask the people on the phone to introduce themselves?
Agenda Item: Panel III – Communicating Results
MS. MEREDITH: Well, there are three of us in this room. It's Janet Meredith, 2040 Partners for Health.
MR. WARE: George Ware, Taking Neighborhood Health to Heart Co-Chair.
MS. STEWART: Tracy Stewart, Board Member 2040 Partners for Health, and Food Subcommittee, Taking Neighborhood Health to Heart.
DR. FRANCIS: So we have really two groups here that are going to help us talk through the question of communicating results. And we have Debbi Main, who is here as the fleshly representative of the Colorado Group, the distance representatives are on the line and have introduced themselves. And we also have Kathy Alexis, who's the Clinical Quality Initiatives Manager from the Community Healthcare Association of New York, who is with us here, great.
DR. MAIN: Well, I don't even have to introduce my team now because they introduced themselves. But you guys can't see it on the phone, but George is right here in this picture, and there's Tracy in the picture. So Tracy, they can see at least the two of you. Janet, you're not in this picture. But thanks for coming back from lunch. I appreciate it. I was, like, "Oh, man, this is risky."
So in fact, you have our bios, but this is just listing and I know each of our team members on the phone actually talked about their role in this project. So I was originally the Lead Principal Investigator on it from the University. Janet is the Executive Director for 2040, and Tracy and George actually live in our neighborhoods, so that's how this whole thing started. In fact, George, I told the story earlier about you as a skeptical person living in a neighborhood, who wasn't sure if CBPR, Community Based Participatory Research, could actually work. So George joined us so that we could prove it to him, and he's still with us, so I think that's probably a good sign.
So I was sent questions. In fact, Maya sent some questions to us about the questions about confidentiality and some other things. And basically, I think we've sort of addressed the questions, and I hope that this presentation is sort of framed to help you answer the questions. But our basic premise is just this: that we believe that enhancing confidentiality, trust and relevance of community-based health information is best addressed early. And I should've actually underlined that phrase "early." We believe it's best addressed early and in an ongoing, meaningful way. And then, I'll talk a little today about this, but by actually engaging people who live in the neighborhoods, and I'll talk about our project where we're doing very local level data collection and dissemination.
And so, really involving people on the ground in designing sort of your data collection methods, interpreting findings, thinking really clearly about how to get the information out in many ways. And then, I think this is a critical piece, too, for us is that using data to develop the next steps. So I think the point of use is really important, as well.
So what we'll do during the presentation is, first of all, just talk about some of the challenges we've encountered in a project called "Taking Neighborhood Health to Heart," and then how we've addressed them. And then, I really want to talk about primarily some of the methods and processes we've used to get really data findings out to the community in a way that helps to increase trust, make it more relevant for people who live in these places, and make it more relevant also for people, like Janet and others, who are working in the neighborhoods as community-based organizations. And then finally, actually making it relevant and useful for researchers like me.
So a quick map of our neighborhoods, and I don't know how many of you are aware of Stapleton. It used to be our former airport and is now still one of the largest redevelopments in the country, and actually specifically designed with what they call "active living in mind." Right, so wide sidewalks, lots of green space, mixed use where you can walk to a store, you can walk to a restaurant, so making it easy to be outside and active. So with the redevelopment, you've had these other neighborhoods, northwest Aurora, east Montclair, what we call Park Hill and northeast Park Hill, who have been exposed for decades to the old airport, and all of a sudden, you have this new sort of redevelopment put in place. And it really presented a really interesting opportunity to begin to think about community health in a really different way.
The other thing that happened is we actually moved our medical school out to what we're calling the Anschutz Medical Campus, which was formally Fitzsimmons, just down the street from Stapleton in these neighborhoods. So a lot of change going on, and a lot of really interesting opportunities to understand kind of health on many levels, in a very local level.
So just a quick description of what we call our footprint, in terms of the demographics. And the thing to note is the real differences in our neighborhoods, so these aren't like Stapleton versus Park Hill versus east Montclair. If you look at sort of racial composition, education, a number of things, these are very, very different places, which again, presents really interesting opportunities when you think about collecting data and sharing data across very different neighborhoods.
So just a quick snapshot just to let you know how we started, and I think I already covered some of this. But it started with a grant out of NIH, to fund community-based participatory research. And the number one goal initially was to begin to engage people in the five neighborhoods in sort of a whole effort on data collection dissemination. And then, the second phase was to begin to collect critical information on both residents, as well as sort of the health of neighborhoods, and I'll talk more about that. Our key focus areas were physical activity, healthy eating, obesity and cardiovascular disease. But again, we collected a number of different kinds of data and I'll talk about that.
And then, the third aim of the grant was just to begin to make sense of the information we collected, and identify sort of using it to talk about next steps with community. And then, a research focus was really understanding the impact of these built places on health of people, as well the neighborhoods, in terms of health disparities.
Okay, lots of information. I think the key message from this is, again, we have lots of information collected in different ways. So we did a random household survey of initially 950 people or adults, and then we followed up with almost another 200 people who lived in apartment buildings, because we had a hard time actually getting into apartments to collect data and recruit people. So we had a household survey, we also collected very extensive data. So for example, if the household was recruited, we collected data around their houses basically, their neighborhoods, by looking at sort of sidewalks, lighting, all sorts of different features.
We also looked at sort of resources in neighborhoods, so we collected very detailed data, again based on community requests and interests on food. So where are the stores, if you walk in the store, how much does this cost? So really, we got inside the store, looked at availability, price and quality of produce. We actually went to parks, a number of parks in the neighborhoods. We went into the parks and said, "What's there?" So it's not just having a park there, but it's the amenities, the lighting, all the other things that make a park actually useful and accessible. And then, again, we had collected a lot of different information from surveys and others on safety, racism and discrimination, trust among neighbors, and then we have a lot of census data, as well. So lots of different information to describe sort of the context of these places.
So if you think about all the information that I had listed on the previous slide, and the fact that community were really involved, well, first of all, the key was they were involved, right? That's one of the key messages is everything I just talked about, people were involved in what's in the survey, to the point where we talked about sampling frames and how are we going to randomly select households? What's in the audit, what do we pay attention to if we walk into a park? Anyway, lots of involvement.
We actually hired and trained community members as really actually data recruiters. So in this particular project, we had community members as recruiters, and then we had a follow-up phone call from a computer-assisted telephone interview survey unit. But we also trained people, community members on qualitative data collection because, I'll talk about it later, we did household meetings with people to kind of disseminate findings.
And then, the other thing that came up, and this came up fairly early in the project is, okay, we're collecting a lot of information on people who live in these places, and we really want to sort of talk about the real issue about some of the abuses that have happened in the past. So I actually think this was one of our biggest sort of wins in the sense that we got it out there fairly quickly. How are we going to prevent any abuses from sort of coming to our neighborhoods, because people were worried about that from historical incidents. So that led to, in fact this is sort of what I'll talk about a lot, is the data review and dissemination committee, and Tracy and George are involved in that on the phone, so I'm sure they'll jump in later. But that's how this started is, we have a lot of data, how are we going to responsibly sort of be stewards of this information for the neighborhoods?
So the data review and dissemination committee is anywhere from ten to 15, depending on the month, we meet monthly. Early on, we met more than once a month. And it really is composed of both residents, as well as researchers, and through this whole process, and again I think this is a lot of important upfront stuff that happened, but we got together and developed principles for how are we going to use the data and how do people ask for data. So if community groups in the neighborhood want to use it, what should we ask them about how to request information, how to use information. So a number of processes were put into place early to actually have that conversation about what makes sense.
The other thing that happens, so we have principles, we have our large data sets with all kinds of information. And then, the other thing that I think was really important is, before we started sort of releasing information to everyone, there was a commitment with the DRAD, along with 2040, to release the data first to community members. So we had a big health summit where community members were invited. We also invited everybody who agreed to be contacted from our household surveys. So again, everybody got to come and see the data release for the first time. And I think that was a big deal in terms of sort of creating trust, and people not feeling like we just take off with their data and publish their findings. But instead, we disseminated first to community.
So some of our key issues, in terms of the ownership, so when people request data, projects requesting data should benefit community. Okay, so that was one of the sort of do no harm. Projects should benefit community, and there are places in the form where people write about how they're going to use the data. A lot of sensitivity in terms of when we release data, we only release data in certain ways. And to date, we've only really given people release reports with the data aggregated, depending on the question. But also, when we begin to disseminate and show data, even in meetings and things, we came up with some principles to how we can be more sensitive to not sort of stigmatizing neighborhoods and populations. And I'll show you some examples.
But early on, we have five neighborhoods. So when we showed all our slides, it's N1, N2, N3, N4, N5. Now, granted, you can look at them and guess, everybody always does the first time. I think I know my neighborhood, but I think the point is really important. It's symbolic in that we don't want all the neighborhoods, "Oh, look at Stapleton. Oh, look at Park Hill," so we just showed all the data blinded. Then we have neighborhood briefs, and I'll show you the face of those. But we did every neighborhood, one at a time, versus all the neighborhoods together, so we never have data, at least in the briefs, where you show all the neighborhoods kind of contrasting one another.
And then, even in our maps, because we do a lot of work with sort of maps and showing patterns of data, so the lowest level of reporting in maps is block groups. So in fact, we talked about this a little bit earlier. And then, I think this is key, a commitment to involving the community in interpretation of data, so it's not just showing survey data, but we also show sort of other patterns of data, or we show kind of social conditions in neighborhoods, to kind of begin to make sense of what we're seeing on some of the individual level data.
So those are, I think, some of our key principles around ownership of community, and really communicating the sense of trust among all of us. So let me just quickly show you an example, these will go fast. But this is a great example, this was like our health summit. This is a copy of a slide where, in this particular one, we show Colorado, we showed all the neighborhoods combined, and then again, N1, N2, N3, N4, N5. And in fact, even to this day, if we're showing data, we tend to just use these slides to just show the distribution with neighborhoods.
And then, same thing, again patterns showing broken down by neighborhood. Just a quick example of the focus on conditions and resources. In fact, this was a very interesting map in that we actually showed this to our community group, Taking Neighborhood Health to Heart, our big council, and to actually a few other neighborhood groups. And this, again, the point is, everything is at the block group level, but you can begin to see patterns and see that it's not just Park Hill or it's not just northeast Park Hill or east Montclair, but there's some common patterns across neighborhoods. And in fact, this slide, along with some other slides, where it was one of the early interests became food, because all of a sudden, we hadn't collected data on food, what's inside a grocery store yet. They saw this and they started saying, "What's going on? What else do we need to be paying attention to, to understand why this is happening?" And it started a whole sort of thread around food and security and food access.
And this is some of the data that we got from that project, where basically each of these is in the neighborhoods is a grocery store or a corner market. And the green means percent that have all the fresh fruits, we had 22 fruits and vegetables, and what proportion were actually in the stores. And if you begin to see the patterns, so there are some stores way off here and a few right over here, but for the most part, having a store doesn't mean you're going to actually have fresh fruits and vegetables readily available, much less affordable.
I have another really interesting slide that I don't have here in this presentation, where it talks about price. And that's another sort of mind-blowing slide in the sense that, in the stores that actually have it, for example, one of these stores is very, very expensive. So again, I think the point is to show sort of neighborhood conditions. And then, very similar in terms of what our geography student called "health spaces," but it really shows the distribution of parks and open space in dark green, bike routes, rec centers, things like that. And as I'll talk about later, we actually, by mapping these kinds of things, people have actually begun to use our data to argue for the big gaps. Right, there's nothing in some of these places in terms of stores and in terms of rec centers and parks. And so, these kinds of data are pretty useful for that.
In terms of sort of what we've accomplished, the data review and dissemination group, as I said, we spent over a year in interpreting data. So it's not one of these things where you just go, "Okay, get the data out there." I mean, it really is carefully looking at data, figuring out the best ways to actually communicate and disseminate. So one of the first things we did is, we created each neighborhood has a series of, I believe, five or six briefs in English and Spanish, so we make everything available in Spanish. Actually in all the neighborhoods that had newspapers and newsletters, we wrote a story. It was like a half a page sort of story about neighborhood data and this project.
And then, we actually on a request by request basis, we provide data to researchers, students, community-based organizations for grant writing, things like that, so we provided a lot of data. And then, often our community members primarily are involved in posters, workshops, national workshops, went to Canada a couple of years ago, a group of our community members. So, a lot of work just talking about sort of, the importance of kind of their role in neighborhood health and actually disseminating data.
So DRAD was awarded, in fact the University of Colorado has a CTSA, Clinical Translational Science Award, and DRAD actually, in conjunction with 2040, applied for a grant and was funded a grant, first of all, to collect more data in apartments. And this, I think, is a very cool thing in that they have what they call "house meetings." So our community members were involved in facilitation trainings, and they took the information from our briefs, because we know that some of the neighborhood association meetings, only some people go to those, other people don't. So the goal was how do we actually spread the word in a very informal way about what's going on? And these were amazing and what came out of the meetings, so shared briefs and summary sheets.
And then a lot of what happened was, all these other things emerged about what were important to community members that we didn't ask about in the survey. So actually this process of house meetings, I mean, I think it's something that we're pretty committed to because we've learned so much about, number one, sort of how to do it, but number two, and most importantly, how it's pretty powerful as a way to kind of hear committee member stories about other things that matter that we didn't ask about. And then, all people who participate in the meetings, then we get them to start coming to our community meetings. So it's sort of one of these processes that feeds itself, and keeps momentum and interest going.
So that's what the briefs again, five briefs, and one for each neighborhood, so it's five times five neighborhoods. And then summary sheets again, the point is just to show that we also give a really one-page summary of different areas that are actually presented within the briefs. And really, the point is to get the data out there and the findings out there for conversation and use. All briefs are in Spanish, as I said. And then, I think this is my second to the last slide, but I think one of the other take home points, I think, from our group is the whole issue of use, so how data are used. And if you feel like data will be used, you're probably more likely to want to be involved.
If someone comes to me at my doorstep and says, "Do you want to participate in a household survey?" I'm like, "Oh, I remember seeing that five years ago in the newspaper, and I know what happened as a result. They put in a new park down the street." So it's that kind of process of sort of being involved and using data that will then reinforce the fact that people want to use more data and collect more data and participate.
So one of our neighborhoods did a health impact assessment, and they were off the radar in terms of a rec center, and then all of a sudden, they became back on the radar, and they got more money to improve a rec center, because they actually took data and said, "Here's what our findings are in terms of physical activity, in terms of obesity," and maps of what the gaps, so used data for that. Two or three weeks ago, I got a request from one of our local elementary schools. They were talking about diabetes in their health block, so they wanted their neighborhood briefs about chronic conditions, physical activity, things like that, so we sent those.
Again, lots of communities use it for grant applications. Here's one, they shared the survey, in fact, 2040 recently requested for one of their projects where they were working with medical students, and they wanted to know findings across neighborhoods and across other demographics on every experience of discrimination. So they requested, we gave information for them, and they're going to have a follow-up project and collect some more data with focus groups. Again, I talked about this where, because disseminated data, all of a sudden, the whole issue of food access kind of rose to the surface and became a really big deal and continues to be for us, where Tracy and others are writing grant proposals to try to fund some of the work within our neighborhoods.
So this is actually a snapshot of, to me, the key take home points of what we started with, is first of all, the arrows just keep going on and on. There isn't an end and I think that's one of the points is it really is an ongoing process where it's really meaningfully engaged in community, in terms of all sorts of things, methods, sort of what's relevant, what's not relevant. And then, paying attention to sort of some of these larger issues. I think the key is paying attention to what matters to people, and then in this case, in our community, this was really important, so we wanted to make sure that this whole system has information that's useful and meaningful.
When we were here in February, I know both Janet and Tracy really talked about the importance of sort of more qualitative data, and we found that out like crazy when we did house meetings, where all of a sudden, you start having people tell stories. You learn a lot about some things that you want to follow up with, sometimes with more quantitative data. And then again, sort of it keeps going on, but analyzing data and share findings to improve actions. So I think one of the pushes we keep getting from community is, "Okay, we want to use it for something. We don't want to just collect data. We think it's important, but what's next? How are we going to use it for actually policy and action?" And again, it just keeps going on and on. So that is the end of my presentation, thanks.
DR. FRANCIS: For those on the phone, we're going to have questions afterwards. We're going to hear right now from Kathy Alexis, concerning childhood obesity prevention in New York City community health centers, best practices and lessons learned. And there is a common theme about using data. The three community examples we have are all obesity, or at least in part obesity examples.
MS. ALEXIS: Good afternoon, everyone. My name is Kathy Alexis. I'm the Clinical Quality Initiatives Manager at CHCANYS, also known as the Community Health Care Association of New York State. Long name, so we just say CHCANYS, and thank you for having me here. Just to give you a brief introduction to CHCANYS, my apologies, this is actually a wrong year. We're now 40 years old, so I think we're still trying to claim that we're young, but we're a 40-year old organization based in New York City. However, we do serve all of the community health centers throughout New York state. That comprises of more than 60 parent organizations and approximately 457 satellite sites throughout the state.
We work to ensure that all New Yorkers, and particularly those living in underserved communities, have access to high quality community-based healthcare services. And as you see here, our mission is basically to focus on retaining and expanding primary care capacity, investigating in primary care health information technology, especially now as many locations throughout the country are adopting EMR systems, implementing primary care home standards, reforming the primary care payment system and developing the primary care workforce.
So our childhood obesity program was initially funded by the New York City Council, in conjunction with the New York City Department of Health and Mental Hygiene, to create what we call the New York City Prevention and Management Consortium. The funding structure unfortunately in New York City has not been to our advantage. Because even though the grant cycle begins, it's a 12-month cycle, unfortunately, by the time we go through contract signing and approvals, and it has to go through the mayor and then the commissioner and all that, our project ends up being just about five or six months unfortunately. But with that, we've still seen some great accomplishments throughout the five or six months, which I'll share with you.
For year one, which was only a five-month project, it was a very conservative project. We only worked with the community health centers, and remember these are only community health centers throughout New York City. In year two, we bumped up by a month, so we were now a six-month project. In the six months, we were able to include participation of school-based health centers. We worked with community-based organizations. We also partnered with other community resources, as well as incorporating what we called "parent ambassadors." Year three, we bumped back down to a five-month project, and because our funding was cut dramatically, we were not able to use the same resources that we used in year two. And so when I show you our data, you'll see that it's going to reflect that in our data, unfortunately.
So the aim of our consortium was to improve the overall screening rate of children using the expert recommendations stated by the National Initiative for Children's Healthcare Quality, which is NICHQ. And our basic focus was on children between the ages of two and 18 years old. So here's a long list of all the consortium participants. We worked with approximately eleven parent organizations, which meant 20 sites. They were all from four of the five boroughs. The fifth borough that was not part of the project was Staten Island, and unfortunately, if you all know anything about New York, Staten Island is usually the forgotten borough. They're not always so included, but only because, at the time that we were starting this project, Staten Island did not have a funded federally-qualified health center. They were not designated yet, and so we couldn't really have them participate. Even though we still shared a lot of our resources with them, they couldn't really officially be a part of the project at that time.
So I'm pretty sure that you all are aware of the childhood obesity epidemic, especially that which is in New York City. Overweight and obesity rates nationally for children have grown exponentially. We also know that being overweight and obese can lead to a myriad of health problems, and even a decrease in life expectancy. But what I wanted to focus on was the fact that, at least in our health centers, the recording of BMI was not yet part of a routine practice. And basically, providers just weren't comfortable in addressing the issue with patients and families. And so, CHCANYS saw this as issues that we could address throughout the consortium. We felt that providing some kind of resources, training to the providers, incorporating the parents, that this will then make them a part of the initiative and further take this message home to their children.
And again, you may all be familiar with the terminology for BMI categories. But what I wanted to concentrate on is that, no matter what the terminology you look at for the consortium, it was geared towards the 85th and higher BMI percentile, so particularly those who were overweight and obese. Now, particularly in the school-based health centers, once the BMI and weight classification and physicals were completed, the provider that was set at the school-based health centers, particularly nurse practitioners, they would call the parent immediately, right after the physical, and tell them, "This is what happened at your child's physical today. This was the result of the BMI. This is how we are now classifying your child." That was something that didn't happen prior to this consortium for a lot of these health centers.
So the data. All of the children, between the ages of two to 18, this is a list of our patient population of focus, who received medical attention at the clinic site in the previous 12 months, regardless of treatment or diagnosis. Now, as you see, as I said, in year one, we were very conservative, we only used health center patients. In year two, we moved onto using school-based health centers. So for year two, we were charged with only having a reach of 2000 children. As you see here, we reached more than 24,000 children. That we considered a great accomplishment, because I think at that point, not only did we know how best to reach the children, but the health centers were able to come up with strategies on how to reach the community, as well.
Despite the size of the teams or the health centers, they were able to document the BMI at very high rates, covering almost all of their target populations. So once again, everyone is over, I would say, 95 percent in documenting their BMIs. The consortium had great successes with process measures. As you see here, in every year of the initiative, 85 percent or more of the children were classified as underweight, healthy weight, overweight and obese. This measure was tied directly to addressing appropriate BMI documentation and classification as a part of routine practice. So with that, participating providers and their assisting staff were no longer allowed to just eyeball a patient. They had to actually go through the process of collecting the weight and the height, and put it in according to the BMI growth chart. The obtained the BMI percentile and then made the required classification and made the required recommendation for each of the child.
Of our children included in the population of focus, these were the percentages for each initiative year of those patients that were identified as overweight or obese. As you see, as the initiative went on, steady increases of patients who were overweight and obese, close to half, were seen at all of the participating health centers. So in addition to weight classification, we wanted to monitor whether or not children classified as overweight and obese were being given the appropriate follow-up care. In this case, that was the nutrition referral. Although each year we were able to reach our target, the highest numbers were reflected, of course, as of in year two. So by year three, the percentages dipped to its lowest point. This was really due to the changes in staff. We had a few health centers that participated in which a nutritionist was not available or went on medical leave or, due to funding that was cut, they had to have some layoffs at the health centers. So we had a goal of 20 percent of the diagnosed children having a nutritional counsel, and once again, as you see, that was a great success.
Our third and last process measure really tied into systems changes by setting a goal of 50 percent of diagnosed children having a follow up with a healthcare provider regarding their BMI. Because having follow up with diagnosed children requires sustained resources within the health center system, this is why we see a variance in the results. In year one, we had some progress. Year two, the teams did remarkably well in reaching their goal. And then, in year three, once again, it dipped due to loss of staffing and other loss of resources. And so for example, though we did referrals for a nutritionist, a lot of the nutrition counseling was not only done by a nutritionist, but it was also done by health educators, by the nurses, sometimes by MAs. And then, if those resources were limited, unfortunately the actual visit was not possible for the sites.
So again, here you see that it reflects the same pattern. This is the 40 percent. We had a goal of 40 percent of overweight and obese children in the population of focus reporting a healthy behavior. Once again, we had a dip lowering to for year three. But for year two, we feel that the reason why we had a higher percentage for year two was this was when we had a higher production of materials to the patients. We partnered with the 5-2-1-0 Campaign that was set up by NICHQ and we shared all of their materials, not only with the health centers, but we did a great campaign in sharing the materials with the communities in which these health centers served.
Out of all the measures that we tracked over the course of the three years, this was the toughest measure to achieve. Actually having the patients reach a healthy rate or reach the BMI, we found that it required a lot more work than just the five or six months that we were allotted. This is definitely a change that required us to follow the trend for longer than that time period. Although we did not meet the goal of the 20 percent, CHCANYS was happy with some form of a result, as you see with year one. They really were not collecting how many patients were moving onto healthy BMI or healthy weight. And at least at this point, they were starting to collect this information. And a lot of that was because, as health centers were starting to implement their EMR systems, there were flags being placed on the system to remind the providers to ask these particular questions. How is the patient doing, what are they doing at home to change their weight or change their activity?
This is where we started encouraging self management goal setting, where once again that was made a flag in the EMR system to ask what goals are they looking to adapt into their daily changes. And during their follow up session, the providers would make sure that they address the patient or address the parent, of whether they followed through with that goal setting.
So I gave you the why, the what, the when. I'm going to go into now how did we do all of this and what were some of the strategies we put into place. First of all, none of this work would be possible if we did not obtain buy-in from senior leadership. We felt that it was important to engage the senior leadership because in the end, they were the ones that were responsible for proving time, providing resources, as well as ensuring sustainment of the success once the grant dollars were gone. Unfortunately, we are now in a position where we're looking for funding, so we're not moving forward with the project, because New York City Council did cut the funding to a lot of the community-based projects. But though we're not actively funding this project, a lot of our health centers are still maintaining a lot of the successes that they experienced through this project.
Each year, we provided an extensive training on the chronic care model and the model for improvement, which were foundations of the approach or the change that the consortium took to make changes with the health centers. We also developed key partnerships. CHCANYS realized that we couldn't really do all of the work ourselves. We had to partner with the Children's Museum of Manhattan, which specialized in teaching the staff of the health centers, as well as the parents, on how to address healthier eating and physical activity in a fun and interactive way.
And kind of like a side note, one thing that they did was a nice little demonstration, and this was mostly for kids, again, remember, you have, two, three, four, five-year olds, and they did a demonstration of what's poop and where did it come from. And for them to actually understand what you eat, this is how it's processed through your system. And you want to make sure that your body is working well and producing good things, and so you want to eat well and eat your broccoli and eat all of this. So they had a really good way of how to talk to kids about what's going on with their body, and basically how important it is to conduct physical activity.
We also wanted the initiative faculty to come from a health center. We didn't want to bring outsiders to do this work, that's not really what we're about. And so, our faculty was a peer health center, the Urban Health Plan, which has been, if not nationally, but definitely locally, known as pioneers in conducting a lot of our collaborative work. We also provided teams with mentorship from returning teams. So as we moved on every year, we had another site come on as our mentor site. That site would be responsible for scaling up. So if they started off with using their health center, they would then scale up to a school-based health center, or they would scale up to another, if they use one site. If they're a multi-site organization, they would move to a second site or a third site. So we always feel that that was a way for them to spread and sustain the work that they accomplished.
Best practices were also a key to our consortium from strategy implementation. We wanted all teams to focus their efforts on practices that were already tried and true. So we had teams refer to what we call our "Childhood Obesity Change Package," and I can always share that with you afterwards. But it was definitely a change package that we shared with the sites to say that according to the care model, if there were certain changes that you'd like to implement, here are some ideas, here are some options that you can use.
As the initiative took place, we knew team members needed skill building opportunity on an ongoing basis. After the initial learning session, teams were provided with trainings on motivational interviewing, behavioral activation, general nutrition and other topics, as needed. We also used our health educators and other disciplines within the health center to help us with cereal sugar demonstrations.
We found that patients are wasting a lot of time in the waiting rooms at these health centers, so why not make use of that time by doing a demonstration. And the best demonstration out there to date is the cereal sugar demonstration. Every time you show them a bottle of soda and ask them how much sugar do you think is in that bottle, and we actually show them, the expression on their face is remarkable. And I think it immediately has a lot of changes. It promotes a lot of changes in their behavior.
Next, we engage the community through the use of team selected parent ambassadors. So parent ambassadors was a new program, a new aspect of the program for year two, where we identified parents who were patients of these health centers. And we used them as voices of the community, and we made them a part of the health center team.
So whenever the health center had a meeting or wanted to talk about strategies on how to address the community, the parents was part of that team and they were able to say, "That's not going to work in the community. The parents that I know, they're not going to understand what you're saying. This book that you're presenting in front of me, I don't understand it, and so my friends may not understand it, so that needs to change." And we felt that was an integral part of the team moving forward and providing resources and service to the community.
The parents also shared the information. They were trained on how to talk to other parents about healthier eating and physical activity. They shared this information at their PTA meetings, they shared it at their church. If there was a health fair or a block fair, they had tables at these health fairs and block fairs, and they shared the information. What was best about that is that it wasn't coming from another doctor or a nurse or something. It was somebody that was just like them in the community, probably a next door neighbor, that was sharing the same information. And we found that it worked.
At the end of every year, we had what we called a harvesting session for the health sessions. And these were just forums to share best practices among the teams. But we also invited the senior leadership of the health centers of CHCANYS, of the funders. We also opened it up to the community to be a part of these forums, so they can see the data that was coming out of the health centers, and they can also learn about what resources is available.
So lessons learned and there were a lot, a lot of lessons within the past years. We always built on the foundations, lessons learned from previous years. We also found, once again, leadership buy-in was integral. For the sites that we were not able to maintain, the leadership buy-in, they were not able to come back just because the support wasn't there for them to continue this work. As FHQCs are striving to achieve patient-centered medical home status, CHCANYS has focused our collaborative to mirror that model. And we did that by adapting a multi-disciplinary approach. We found that integrating current resources and addressing the patient's care as a team further addressed their needs in a more efficient manner.
Healthy eating and physical activity definitely, we felt, should be introduced to the parents and children in an interactive, creative and fun way. We found that, a lot of times, if we shared this information with the kids, they ran home and shared it home with their parents. And the parents were kind of forced to do something about it, because they felt like they saw that their kid found this really important to share with them. They were like, "Okay, we'll have broccoli for our dinner tonight," or "We'll have this," just because little John brought that home.
And another, we had a focus group with a lot of the parents who were part of the parent ambassador program. And what they shared with us is that, the reason why they take their children to McDonald's or the reason why they take their children to all these fast food places, and especially children of immigrant parents, they felt was because they weren't home a lot. They were working, mostly because that's really what they had to do. And so if they wanted to find a way to bond with their child, the way to bond with their child was giving them what they want. And what do kids want? They want to get that new toy at McDonald's that is being advertised these days, and so that's what they did. And they shared with the teams that if there was a way that the greater organization, whether it's the state or a national, if there's a way to change the advertising towards children, for example, with McDonald's, why give those toys, because those toys are really what the kids want to get. They bother the parent, the parent feels they want to bond with their kids, so they take them to McDonald's. And so there has to be an effort together, not only just with the health centers, but nationally to have a change.
There was adoption of best practices, which required creative strategies in regards to the finances and human resources. As I said, with the finances being that a lot of the funding was cut, not only to CHCANYS funding, but also to the funding of the health centers, we had to think about different ways of using current resources, the staffing. Like I said, the waiting room demonstrations, those are just ways that we try to bring the information to the community. And providing ongoing coaching and incorporating team feedback through the initiative assured maximum success, and we did that by having collaborative calls.
The structure of our project was that every week, we had a collaborative call where the health center teams came together, shared their successes, shared their challenges. We troubleshooted a lot of problems. We also did a lot of work on discussing how to perfect their EMR system so that it can collect the data that they're looking to collect, and then they can then disseminate to their quality improvement team internally. And so, when we're looking at next steps for the teams, we're hoping the teams that we worked with in the past, and the teams that we hope to work with in the future, will sustain any of their system changes so that they can scale up and or spread. Currently in New York City, we have 100 percent implementation of EMRs.
In New York State, it's 88 percent. So with that, we continue to use electronic health records to mainstream and ease the data reporting. Unfortunately, in New York State, we have 12 different EMR vendors, so that makes it really difficult to kind of standardize a practice throughout the state. But once we have an idea of how each of the EMR systems work and what the main pieces are to them, then we can assist the health centers on how to use their data.
And for CHCANYS overall, we'd like to continue working with our partners, whether it's with the community-based organizations or with the community, to further the work that we have, secure continuance, trying to secure funding for the project so that it can continue. And most of all, we're looking to spread this project statewide. Right now, as I said, the project is mostly New York City based. Though some people think New York City is the entire state, but it's not. There's a whole other world outside of the city and we'd like to just take this further and bring it to the communities outside of the city. Thank you.
DR. FRANCIS: Thank you. I am going to open it up to questions from committee members and the group more generally.
MS. MILAM: Debbi, I've got a question for you. You talked about data release and just going down to the block level. Could you speak a little to how you determined that block level was appropriate, the right level of aggregation and what other sorts of release rules you put in place and how you knew they were right or what testing you did? Where you drew them from? Thank you.
DR. MAIN: So it was actually through community meetings. We were trying to figure out, and based on if we sort of distributed the survey data, and number of people per, we wanted to have enough people. So it was around anywhere from 15 to 35 or 40 in terms of numbers. But I think, and I'm going to punt it, too, to my community collaborators, because it was more than just the numbers. I think part of it was the message. And I don't know if someone in Colorado hears this and wants to kind of jump onto this answer.
MR. WARE: Well, this is George. And certainly one of the things that we were concerned about was stigmatizing various neighborhoods. And so, after a lot of discussion, we just came to and learning what size the block group, how many people that might encompass. We thought that that would be an adequate way of being able to describe the neighborhoods, but not to the point of stigmatizing them.
There were points where we talked about, especially with the neighborhood audits, where they went to and looked at the conditions in the neighborhood, and looked at the things like windows. We just didn't want it to be the case that someone might be able to say, "Oh, you don't want to live in a certain place, because look what the data is showing about that neighborhood." And so, it was through a lot of discussion that we said that that was probably the level that we should be doing the analysis.
DR. GREEN: I'd like to follow up on what George just said. Before I do, let me declare that I've got a conflict of interest, but I certainly have a duality of interest because I'm on the Board of Directors for Partnership 2040. That said, I have a question to follow up on what George just said, and I also wanted to ask it to Kathy, also. Can you comment, can you actually tell us about particular harm that came to your communities because of communicating the results of your work? And then, the second part of my question is, can you just continue, as George was, can you also give us a listing of the fears of harms? Actual harms and fears of harms, that's really the questions for both of you.
MR. WARE: I'll start off. One of the things, it was even for my skeptics becoming involved with Taking Neighborhood Health to Heart, was I work for the state health department. And when we had done various surveys and focus groups, people complained out how often information was gathered, but it wasn't used to benefit. They didn't see where it actually changed anything. And in fact, they also talked about harms that were done. And I don't recall hearing specific examples that they gave of information that was used by the health department, but they did have this overall sense of all it does is, this is just one more example of, in the case of one of the communities that we were serving, we were serving around disproportionate rates of STIs among African-Americans.
They said this is just one more example of what's wrong with our community, and people were just very resistant to taking part in any type of work that the health department was doing related to that history. And so, that's' what I was bringing to the table when I became involved with Taking Neighborhood Health to Heart. But I can't give you a specific example of when that happened.
MS. STEWART: This is Tracy. I just wanted to chime in. One of the things that did happen through the CBPR piece that was very enlightening and might kind of go along with what you're talking about, is the harm that's been done when you look at African-American and Latino communities, specifically from a top down research perspective, is that you already walk in with assumptions about what you're going to find.
And so, the harm that's been done in this community is that we have never looked at environmental conditions around asthma. But when we did the CBPR piece and we started gathering data there, and the way that people answered the questions on the surveys, we started to realize that there is this incredible explosion of asthma, both in adults and children, especially in the northeast Park Hill area. And what was interesting about that is that, if you were ever in Denver, you'd see that we have a lot of environmental factors that are going on alongside I-70 and Smith Road and all that. And those things had an impact on the community.
But for years, because of the way research has been done in these communities, and it's an African-American community, we only went in looking at diabetes, heart disease, high blood pressure, the typical known factors.
The other harm that's been done, and we just had a big conversation about this, in a couple of instances is that one of the other things that popped up for the communities were issues around mental health. And again, for years, we've been looking at hypertension as sort of, "If only people could eat better and walk more," and not looking at the stressors of life, especially for communities of color, people living in those communities, and how that stress and that lack of care on the mental health level plays into a physiological phenomena, which might be considered a defense mechanism. So there has been harm out neglect.
DR. FRANCIS: Kathy, do you want to jump in on that, too?
MS. ALEXIS: Yes. I just jotted down three notes in thinking about that question. And one fear that I remember parents sharing with us is that this could easily be another great project introduced into the community, and once the funding is gone, it's taken out of the community and nobody follows up. I can only speak for New York, I feel that that is something that the people in the community are accustomed to, especially folks from the government coming in, doing something, and then just leaving with the successes and not leaving some kind of foundation behind. And so, a lot of the work that we do at the health centers is to ensure that some of this work is sustainable. We're not at 100 percent of doing that. Unfortunately, it is very difficult, and as there are high turnover rates at the health centers. But I think, for those sites that are motivated to keep this work going, they do try to find some way to sustain it.
There's also the fear of low self image on the children. They feel that, if you keep talking about weight and physical activity, for those children who are larger, that there's some kind of low self esteem or low self image. And so with that, one thing I forgot to mention in my presentation is that, from the parent ambassador program, one of our health centers, one of our mentor sites, they took that program and developed into something totally different and made it a peer-to-peer mentoring program, where the peer-to-peer, they identify children who were part of their patient panel, who was diagnosed as overweight, and they lost a considerable amount of weight, and they identified those kids to be the peers in the community.
And so, these were the kids that they learned how to talk to their friends about physical activity and healthier eating. And they were able to go out into the community and talk to their friends about, "Hey, this is what you should be doing," or "This is something else you can eat instead." And a stipend was given to the kids, these are kids, want to keep their interest, so we gave them a stipend to keep them as part of the team. But they did learn a lot and they were able to share a lot of this information with their friends.
A challenge that we did have was, once again, we're dealing with underserved communities, a lot of it, especially New York City, are immigrant populations and where the idea is a big child equals a wealthy family. And so, if you're coming to this family and you're saying, "Your child is overweight. He really needs to lose weight," and they're, like, "What are you talking about? He's great. He looks healthy. That's a good child, that's what you want, that's what we want in our family." So the challenge was to kind of change that mindset.
And really, the only way to do that is to have a culturally sensitive format at the heath centers, folks that understand the culture. And New York City being what it is, there are so many cultures there, it's just a matter of making sure that everything, all of the resources and all of the trainings, are all culturally sensitive.
MS. MEREDITH: I have one thing to add if there's time. This is Janet in Denver.
DR. FRANCIS: Okay.
MS. MEREDITH: We did a childhood obesity study in these five neighborhoods. And one of the issues that was raised many times was the issue of using BMI, and that BMI is a very sensitive issue because with people's different backgrounds, they tend to grow and weigh differently, their bones are heavier. And this sense that, if you categorize people all as overweight or obese because their BMI is in the top 15 percent of national average, it doesn't necessarily reflect that a child is overweight or obese, and that that itself is stigmatizing.
And in talking to our researcher, we had a lot of discussion about the fact that it's one of the few measures that's available. It still doesn't make it necessarily an accurate reflection of health. And it was funny because, you know, I think there was a comment earlier about how the medical professionals need to do more than just look at a child. They need to measure BMI to see if they're healthy. And part of what we're saying is sort of the reverse, which is, "Okay, do your BMI thing, but then take a look at the child. Because there are lots of kids who you would very quickly say, all right, this kid is healthy." So the BMI issue is alive and well, and truly an issue with different cultural backgrounds.
DR. FRANCIS: Walter?
DR. SUAREZ: Thank you. I have two questions, one about resources, the other is about funding. They're kind of the same, but resources meaning resources in terms of the, well, let me start with this. Both efforts, and I see a lot of initiatives around this, use CBPR, Community-Based Participatory Research, which is something different, I guess, in terms of how research is done in community-based oriented research, involving individuals from the community, directly helping define the research agenda, define the data analysis, the data dissemination, and even perhaps the intervention into the work.
So my question about resources is, because I did this type of research back in Minnesota and the most significant issue we identified was the need for training community health advocates, community health workers, whatever we call it. So the need to have this new group of people at the community level that are going to help support the community in identifying all this information, using it and ultimately achieving improvements in the community health at that level.
So my question about resources is, do you think that there is enough of that kind of resource in the community at this point, or is there a need to really look at finding ways to training and to bringing in and increasing the pool of this type of individuals and resources that are needed at the community level. Do you have that experience in terms of resources?
MS. ALEXIS: I feel that there are not enough resources out there, especially when you're thinking about community health advocates. I know that we are starting to work with community health workers in New York, but unfortunately, a lot of the work that they use, and particularly patient health advocators, and community health workers, there's so many different titles that you can place on that one entity.
But if you wanted to speak of patient health navigators, they're usually used in the cancer field, and a lot of the research has been around colorectal cancer and other types of cancers. We're now starting to research the use of patient navigators and diabetes care management, and I think slowly into, and I think there has been some work about, diabetes care management and childhood obesity, and using the patient navigators to assist the parents and the kids, not only in how to navigate their care within the system, but also how to identify the resources in the community, how to identify how to get it, how to use it, and it's really slow.
Actually, I'm hosting a webinar next week, particularly on how to use patient navigators and diabetes care management. And the information is not really out there, especially if it's not around cancer, you don't really know how to use it. And I've found like a lot of people are craving the answers on how to not only identify the right people in the community, to be these patient navigators or the health workers, but also how are you going to sustain the program and pay for it, because right now, there's no reimbursement for that resource, if you include that. So really, it's a much needed resource, but there is no way to sustain it because there are no dollars behind it.
DR. SUAREZ: Well, I don't know if you had any additional comments.
DR. MAIN: It's a whole different kind of resource and infrastructure. I mean, part of what happens for us, because we're really talking about collecting data, disseminating data, ideally using data for advocacy and policy change and things like that. So it's a different kind of infrastructure, but part of what happened, in fact, within the project, what, six years ago or five years ago, is we actually started really developing capacity. And even our teenagers, I mean, we do some inner generational work where we're building capacity within people who live in the neighborhoods, where now, in fact, we have two of them, one of them is now a data analysis.
And so, it's a different sort of level of infrastructure and resources that I think is really challenging because of funding, but our model ideally is to sort of train people who are very comfortable in community and data collection and dissemination and some other things, in more than one language actually.
DR. SUAREZ: Exactly. And so my second part of the questions really, it's a two-part question more than two different questions, is about funding and how to support this type of efforts long-term, because most of this I refer to as projects. And one of the principles on community-based participatory research is, you don't come to our community to do a project. We own and we want to own and we want to maintain, and we want to keep running with it. And so, how do you see finding the funding that is needed to help support those kind of initiatives? Is it a funding that gets incorporated into the funding at the state level of communities?
DR. MAIN: I think it's a great question. And in fact, your whole point about it's not a project. Finally, I should say, I changed this from project to initiative, because part of the figure is, as we keep going and depending on what happens in our analyzing data and making sense of it, we keep collecting more data, which is not cheap. And so, part of it is self-funded, part of it grant funding, but I think you hit the nail on the head, is we don't have the consistent infrastructure and funding to really make that figure kind of realize and sort of be realized in a full way. And I think that's the exciting piece is to figure out how to do it really well, where you don't have to keep hiring people for different things, but you have a very talented group of people who can do this work really well. It's challenging.
DR. FRANCIS: There are a couple of other hands, but I can't resist asking you a question before I go to them. So you collected your own data, neither one of you used existing data sources for a different purpose, or maybe you contemplated it. But one of the questions for us is, what sort of confidentiality, if any, how should we be thinking about, say it would've been really useful to use clinical records. Now, Kathy was mentioning that some of the information that you collect will go back into clinical records. But did you do any thinking about using other data sources, and if so, getting community input into the permissibility of that?
MS. ALEXIS: There was no thought of that, I have to be honest, I don't believe so. I think the PCA, we're in a different position in that, because we are working with the health centers, it would be the health centers to collect that kind of information. And I think that makes a good point in which we can assist the health centers on how to do that. But I think, as the PCA, because we're at a different level from the community, we probably would not be able to do that kind of data collection. But we could definitely work with the health centers or at least how to set up a system to do that.
DR. MAIN: Does anyone from Colorado want to respond?
MS. STEWART: Debbi probably spoke for us pretty well there.
DR. FRANCIS: Okay, Paul, and did I see Marjorie, too? Paul? Marjorie, then first.
MS. GREENBERG: To Debbi, you'll think this is what I always say, but it's what I said in February, too, that this has been really very exciting testimony and testimonials and information. And I thank you both. I'm inspired by both of you and by what you're doing, and at the same time, concerned. I'd like to think that you are just a tip of the iceberg and that you represent similar things going on all over the country. And I know there are some and we had nine exemplar communities, or 11, thank you. But still, I don't think it's true. I know it's not where we're putting most of our money in this country. So I'm trying to think, what can we do to kind of move some of this forward.
But actually, although we were talking, it may seem somewhat disparate, but how all of these presentations that we heard today have sort of come together. We heard from Dr. Botkin, and I thought it was such an important point from the beginning, that frequently research, biomedical research or other research, that is even if it's de-identified, the goal has been to fly under the radar. That has actually not just been the outcome. I think in many ways, many times, it's been the intention.
And I remember a hearing, and Maya, you may have been there, soon after HIPAA came out, I'm sure Gayle was there. And we were sitting in the basement of a hotel in, I think, Silver Spring. And I won't mention what agency said this, but it was after HIPAA had come out and the privacy rules and everything. They said we were doing fine before, people didn't really know what we were doing, but it was good and it was for the public good. And now, we have this problem. And these were not bad people who said this, and they were doing good work. But that, I think you just put your point on it, that it will come back to bite you at the end of the day, if nothing else.
And then, I just tie that in with what we heard this afternoon, where not only did they not try to fly under the radar, you were all flying together, holding hands. The more people knew about what you were doing, the better, and not just so you could do it, but so it would meet people's needs and it really would impact on population health.
And then, I come to the middle of the sandwich here with Denise, who kindly joined us today. And your first recommendation here was that you would like to see the national committee and certainly with NAHDO and other organizations and the department and everyone else, I'm sure, but lead the effort to develop messaging for the public and policy makers.
You said specifically about the need for identifiable data, but to improve the public's health through evidence-based decision making. And so, I feel that is very tied also to this whole idea of we have to dispel the view that it's better for people not to know what you're doing. We have to find more effective ways to reach out to people, and you have certainly some best practices here, to engage people.
And then, some of these issues about, well, certainly suing people or going to court or whatever, I mean, there will always be some that will do that. But it's like they'd be suing themselves, because this is part of the process. It's not these people doing something to those people, as you said, not a project or whatever, not even an initiative. It's an organic situation. And so I don't really have a question, but I just wanted to sort of bring those strands together that are in my mind, because even so, I don't think this is well understood. And yet, it's so compelling to hear it.
I did have one specific question about these 12 different EMR vendors, which both Paul and I sort of groaned. And now, some of these may well have come on line before this whole meaningful use initiative, and that could happen, I guess. And so, that's an interesting point, that they didn't maybe need the funding that's part of meaningful use, so they didn't require to be standardized either. I'm hoping that that can't happen now, as people getting the incentive payments or whatever, that the organizations do have to have standards in place, so they aren't just 12 different systems, that these systems can talk to each other. But have you found this to be a significant issue from the point of view of comparing data or sharing data?
MS. ALEXIS: Yes, absolutely, because they do not speak to each other at all. And I'm relatively new to the whole quality improvement world, and so, to figure out what happens with each EMR, how does each one of them work and the different lingo. I heard about jellybean the other day, and I'm like, jellybean? I'm like, what does that mean? But all the different EMR vendors has a different format or a different platform. And there's no way someone coming into these health centers from the outside can understand what that means, so that we can provide the type of assistance that they need.
And then, with that, there's no way that a patient coming from New York City, that decides to move to Albany, that patient record, there's no way the information is going to transfer over for that patient. And so, you're going to start anew. So having all these 12 vendors, I mean, it's great, it's nice to have options, but sometimes the way my brain works, I don't really like that many options.
So there's just all these options, it doesn't work when you really want to deliver the kind of care that you're looking to deliver to the patients in such a big state, because it's big and there's' all these different sites. And as I always try to tell people, when you look at one community health center, you look at one community health center, not one of them are the same. And so, it would be helpful to kind of fix.
MS. GREENBERG: But they have a lot in common, right?
MS. ALEXIS: They have in common, yes.
MS. GREENBERG: I mean, they could be more similar.
MS. ALEXIS: Yes, they can.
DR. FRANCIS: Paul, you had a question?
DR. TANG: I'm struggling with how to formulate it. One of the interesting things, who said it, it was in the Colorado House meetings, and in the sense, what that represented was a sort of a local focus group. But you said there was new information that came at you, and I'm going in the direction of ethnography. In other words, in trying to guess or deduce something from even data, what do people really need? What gets in the way? And then, Kathy reminded me of that when she talked about the patient navigators.
So in a sense, how do we discover what really gets in the way of health? I can't remember the program, but I think it was in New York, where this woman started out trying to help people with their health in free clinics and all, and found out that it's pretty hard to be healthy and homeless, and ended up turning into really a community-based effort to deal with needs that interfered with health, just like education.
And so I'm circling around how do we understand all the various things. And then, if we understood that well and understood what their perception, the community residents' perception of their needs, then wouldn't we have a natural job description for a navigator. And if we really had a ethnography-based job description of a navigator, then wouldn't it get sustained. That's where I'm ending up. Wouldn't it get sustained? Because if there was a true perceived felt need for something, then we would find a way. We, the community, go back to ownership, would find a way to make it happen. The ownership can't happen after the grant. It doesn't happen before the grant, I mean, because of the grant. It's got to happen because it's needed to happen.
And so, that's where my question boils down to the ethnography and how do we discover what is, one, the real need, but also marry it with their perceived need, so that you get ownership. So I'm asking it as an opened-ended question, how do you deal with that? Am I even on the right track, and then wouldn't we have a job description for a navigator?
MS. MEREDITH: Can I take a stab at that, here from Denver? All right. This is Janet. So there are a couple of things that we have been finding in talking to community advisory groups about health. And one, this doesn't directly answer your question about navigators, but it brings in a couple of issues that I think influence this. And one is that, there is no sort of generic way to understand these issues. You really have to understand what's happening to people in a specific place. And once again, mentioning that qualitative research is what tells the story. There is a story of what happens to people, and it's never been more apparent to me than when we had our group together, talking about mental health issues in our neighborhoods, and what happens to a family when they have a child, even up to say a 30-year old child, who suffers from severe mental illness. The data is never going to tell the story, it's all about the qualitative information of what really happens to people.
I think one of the challenges with CBPR, and this now rolls into the question about funding, is that it is not a linear process. You have to be willing to collect data, look at the data, do qualitative fact finding, and then determine how you're going to do programs or interventions or whatever you need to do, to try to change things, and then see what works. One of the big problems that we face is that, you referenced that that this is really an organic process. There really is no funding for organic processes. And people tend to focus on funding, either one piece of that or needing to know where it's going in order to be willing to fund.
And I think that we are really onto something big here. But the problem is, we're fighting tooth and nail, like every step of the way, to find the right funder, to define what the outcomes might be, before we know them. And I think there has to be a different way of thinking about long-term health and the organic nature of it, if we're going to fund it, structure it and be successful.
MR. WARE: And this is George in Denver. One of the things you mentioned, ethnographic research and how do we know real needs versus perceived needs. One of the things that was, I think, the beauty of our doing the neighborhood meetings, the household meetings, was that people began to engage around, it wasn't just the sense of someone taking the information away and saying, "Oh, based on what we're hearing, this is what we're thinking needs to be in place."
There were people in community who were beginning to own what the next steps to what needs to be in place. And that sense of ownership, the beauty of this is that you don't necessarily have to wait even for a funder, even though we could use the funding, but for a funder to say, "Oh, yeah, we'll fund that initiative." There are some things that begin to happen at the grass roots, and I think our food subcommittee that we have, that's taking a look at how to make food more accessible, healthy good food more accessible in our neighborhoods. That's an example of, at the grassroots level, through this project, through this initiative, through the work of Taking Neighborhood Health to Heart, that's an example of people at the grassroots saying, "We're going to take this on and we can't just wait for the funding."
DR. FRANCIS: Thank you. So we're sort of past the three o'clock point, but what we're going to do is continue with this discussion actually. But I'd like to invite people who've been sitting around in the sort of audience or not really audience, former earlier in the day participants. If you've got thoughts you want to make sure that we don't lose hold of, because what we're going to do is continue this discussion, but with an eye to what are our next steps.
DR. GREEN: With apologies, could I jump the line because I've got to go. And could I just notice one thing from the afternoon, and as people are getting organized to talk? Is that okay?
DR. FRANCIS: Sure.
DR. GREEN: This last session, yeah, I'm taking it back to the title, the community is a learning system for health, using local data to improve community health. I think this links back to the morning session very nicely, and leads me to conclude that enabling committees to be a learning system for improved health using local data, it is much more a sociologic than a technological problem. And secondly, that the whole country is simply missing a sustaining enterprise for communities to improve the local health. The country's invested in projects that come and go, but the communities need an enduring mechanism and a way to sustain the opportunity to work together with the healthcare providers, as were so beautifully presented this afternoon in those community health centers.
But we are missing a place to pull the provider community, the administrative data and the insurer community. There's no place for them to come together. And I thought that just literally leapt through the phone lines out here today, listening to people talking. So that's my contribution to the follow up discussion and thank you for letting me do it. may I jump the line?
DR. FRANCIS: Thank you very much for being with us, and I'm sorry you've got to go. Other comments?
DR. FOLDY: Seth Foldy, CDC Atlanta. I'm going back to the morning's discussion on security, privacy, confidentiality, and only one of the speakers is still left. But something for the group to consider, the word "consent" didn't really arise during the morning's discussion. But it is coming up a great deal in discussions around the sharing of health information, not just health data for various statistical or community sharing purposes. But once again, around the sharing of information between two clinicians, or between clinicians and public health. And it seems that some of the things that are driving this new discussion, there are some discussions out there about actually increasing the level of restriction on the exchange of information, for example, between two clinicians caring for the same patient. The requiring of higher levels of consent, or more explicit consent than is currently encoded in the HIPAA legislation rules that have been in effect so far.
And I think there's a number of things going on around this. One is an interest in addressing the issue of, again, our patients being given the appropriate level of control over how their data is being used. There's some discussion that I'm hearing about an interest in trying to make it far more granular which information might be consented for sharing, and which information might be withheld, which I think raises lots of very interesting and difficult issues regarding downstream effects.
I think one of the speakers, Rosamond, I was very glad to hear her bring up the balance between privacy and other goals, other goals that may be very important to the same patient, such as making sure their doctor knows what their allergy list is, making sure that they don't suffer a drug interaction that might've been avoided, so there's always a balance between privacy and other goals, such as the quality or safety of healthcare, and larger social goals, like public health awareness and community health threats.
So where am I going with this? So we do hear more talk about more consent requirements on the exchange of health data. And I have heard even the work of this committee cited sometimes as an important underpinning for the need for those discussions and the need to reopen the discussion. I think there are some really critical issues. One is, there's been a lot of discussion about people issuing consent about the future use of data ongoing. That strikes me as something that's very difficult for people to imagine how they would want their data used a year from now, two years from now, when they're unconscious, when they're awake. It seems like a very difficult thing to talk about.
There is a lot of discussion about people establishing a consent today about the use of their data years down the road. There's also discussion out there about trying to come up with the new technical solution around consent, and those of you who've studied the PCAST report are aware of this. I think there is a hope being held out, and I don't know how robust the hope is yet, that you can take this kind of granular consent and attach it to a particular piece of data and make it available into the future.
So I would just say that, this morning's discussion touches on the ongoing issues of consent that we're starting to hear more about today. And the conversations about consent, touch very much, I think, on the work of the committee. And I'm hopeful that it will start to try and contribute to the discussions going forward, because I think it actually has very broad implications. If our speakers would have been here, I would've said, "So, you didn't say much about consent. What do you have to say about consent?"
DR. FRANCIS: If I could make just a comment sort of for them. My thought, and I'll just put this out as a group question is, what we're here about today isn't patient care. It's about uses of data, essentially for public health and particularly plugging back into the community for local area health improvement.
I think one of the questions on the table is whether consent is a relevant model, particularly when there's not a direct link to an individual. So those could be separate questions, or whether there are other models that are better models for protecting people. And so, that's sort of partly what is an alternative to individual consent and opt out is an alternative to individual consent transparency. I mean, maybe that's a coordinator, is an alternative to individual consent, some kind of community-based participation in research design, and then people get to opt out, if they want to, but those are some of the models that are out there.
Or it could be that, if there's community-based consent, we don't even have, I mean, I don't know. How would we make sure we protect, in light of what our structure is and whether we don't have, if we're not insisting on individual informed consent at every moment. Those are the questions we're really trying to explore today.
DR. FOLDY: And if I could just add, I think people's hopes that there will be a major convergence of health information, collection and management systems means in part we may not have such separate systems in the future for collecting community health data from collecting individual health data, so that the discussions necessarily becoming intertwined, unless they're carefully dissected out and discussed.
DR. FRANCIS: You were so close to me, I did not see your hand. Sallie?
MS. MILAM: Just playing off of Seth's consent discussion, one of the interesting threads that I found from panel one was around the consent issue. And I'm looking back on my notes from Michelle Justus, and that was around BMI. And with regard to consent initially, they had no consent at all. And then, they moved to opt out, but no notice was required, and the opt out was really onerous on participants. It required a written letter from the parent, to send it into the school system, which from a consumer perspective, it's just too much work. Most people won't do that much work to opt out.
And you compare that with Jeff Botkin's response around blood spots, and you know the survey data reflected that people really felt it was important to have a meaningful discussion and understand what their information was being collected for. But he also said that he actually personally thought that opt out was fine. And I think what he was inferring that as long as there's meaningful notice, and people understand what's going on, that they're fine.
So the questions that I noted from my self were, this is a big difference between Arkansas, who with no notice and they had no real fall-out from no notice, but the issue was weight, versus Utah with blood spots, and the people wanted notice, so that is a lot more sensitive information. So I was wondering, is the dichotomy about sensitivity of information, or is it about what Jeff also refers to the lawsuits that resulted around blood spots where people didn't know what was going on. So is it sensitivity is tied to real issues then tied to action, in other words, suing? Or is it something else all together where we have different cultures of privacy around the country and people are reacting differently? So those are some of the thoughts that I had, at least from the first panel.
DR. FRANCIS: Sallie, I can give you a little bit of an answer on the Texas blood spot. I think two things that really concerned people were, in one case, the thought that the data had been used for commercial purposes. And in the other case, and I can't remember if it was Jeff or Rosamond who mentioned this, it was Rosamond, the use for law enforcement. And so some of it, at least some of the concerns weren't the sensitivity of the data, but the use to which the data was going to be put, I think.
MS. BERNSTEIN: I know Larry's gone now, but I think when he recommended that we talk to the Arkansas people, and we didn't have enough time to ask Miss Justus, who I assume is not on the phone.
DR. FRANCIS: Let's just check, is there anyone new on the phone?
MS. BERNSTEIN: Or who joined us from earlier in the day? Yeah, my sense was that the very beginning, so remember that she told us that there was a very short time they had to get the funding, get the legislation and then actually do the thing, all in the first year, that there was actually some kind of outcry at the very beginning, before they really got up and running, and the second year, that there was some kind of backlash from the parents, after which they got an IRB together and did a bunch of things. And she didn't talk about that, but that would've been my question to her because that's what I understood happened. I could be incorrect about that, I don't want to say that I know it. But my understanding is that there were, in fact, some pushback in Arkansas before they got the thing off the ground.
And after that point, they had a procedure going forward. I don't know if anybody around the table knows about this. There were various nods and sort of.
MS. MILAM: But Larry did ask her that question, was there any fallout from it. And if there was, she may have mentioned it to you, but she didn't give that response when Larry asked in front of the group.
DR. FOLDY: Did she not say that between year one and two, there was a change?
MS. BERNSTEIN: She said later there was a change, yeah.
DR. FOLDY: So I'm thinking something triggered it.
MS. BERNSTEIN: Yes, when he did ask her about that, I thought she was talking about, at the end, after they had collected the information and the disclosure of the information or whatever, but I don't know. So maybe one of the things is to go back and I can go back to her and ask her specifically about those things.
MS. MILAM: Well, if we feel like we want to follow up on consent, I know in the past, when we've talked about consent, we felt like the policy committee was taking the lead with that and we were going to focus on other things.
MS. BERNSTEIN: Well, not just about consent, just about what was it that they did that got the community to buy in. So we were talking about alternatives to consent, sort of can you engage the community in some way, get political buy in, get legislation, get other ways that might not require specific consent from individual people, because as we said, it's burdensome and administratively difficult and so forth. But the question is, what in fact did they do? They had legislation, they went through the schools, they did go back to the parents with this written report that they gave examples of. But it's worth just making sure that we're clear about what happened there in that program. I felt like I didn't have enough time to talk to her. There were some more questions, maybe around the table. So we can do that, though, we can go back to her.
DR. SUAREZ: Yes, thank you. I just wanted to follow up on this point, because I think there's a common thread in a lot of this activities, initiatives, project, programs. And that is that, there's usually a state regulation or law, or some sort of a regulatory activity that creates the ability for the entity that's going to collect the data, to collect the data, and then define some of the parameters on how the data can be used.
Now, what we are seeing, at least going back to some of the comments that Marjorie said, 15 years ago, there wasn't necessarily that level of degree of expectation in the community of transparency and sensitivity and ask me first and everything. And so, a lot of activity that was going on back in those days, fell generally under the authority of state agencies to do this type of efforts and projects.
But now, more and more, we're seeing the need to create legislation for a specific type of program that deals with the privacy of that program. And my concern, of course, is that within a state, there's hundreds of programs, and each program handling privacy a little bit differently because, well, this program we use opt-in and this other program we use opt-out. In this program, we ask consent first and only for certain things. It's going to create even a more difficult patchwork inside of state regulations that drive the privacy process across this initiatives.
And we are just talking about public health. I'm focusing on public health, because I think clinical care and care delivery and all that is now, there's a lot more regulated around that and there's a lot of other parameters. But public health is now, in my mind, and that kind of is our focus really because the policy committee doesn't really necessarily get too much into the details of public health, with respect to privacy. But I think that is what is going to be the challenge, is the creation of this multiplicity of approaches on privacy for specific public health initiatives. And I think that's biggest concern I have.
MS. KANAAN: I hope it is all right for me to offer an observation. I think that in some ways, what we learned from the latest presentations, particularly, I think, the Denver one, is that sometimes we see these questions of privacy, confidentiality, consent, etcetera, etcetera, most clearly when we look at them in a broader context, and not just at the processes around consent or no consent and so on. And it seems to me that, we haven't called out the whole idea of activation, but I think that's really, really an important piece here.
And you talked about as community ownership, but looking at it from the individual level, activation in terms of health, I think is a principle that now is recognized. We're talking about even a broader sense of activation, which is the individual patient as a part of a community. And I think that at least some of these projects that we've been looking at or these initiatives, are helping people understand themselves as part of the community, and that including, in many cases, leading them, empowering them into a kind of advocacy around health and environmental determinants of health. And I think that needs to be recognized as a part of what we're talking about here, not just the consent practices and the data handling practices.
DR. FRANCIS: Could I ask the two of you just one more question that's kind of specific? I know when we heard the Arkansas example, I mean, obviously the thing they did was they sent results back to parents. And one of the things that worried them from a confidentiality perspective was kids getting stigmatized when the kids were given the information and taken back. Now, I take it in New York, the families got the information, so I'm interested in how that individual feedback was handled and what some of the issues were around protecting confidentiality or from teasing or stigmatization and so on.
Maybe I've got this wrong, but my sense is that, in the Denver one, there's no specific health information specific to people, to individuals. So you're not, for example, going door to door and taking people's blood pressure, or figuring out body mass indices or anything like that. What you're learning are people's perceptions of whether the streets around them are safe, but you're not feeding back information to individuals?
DR. MAIN: No, though Janet briefly talked about the childhood obesity study, where we actually had people at the door, collecting data, doing height, weight, face to face. Again, I'm not sure, I don't think there were actual. They did get feedback around also, they did fitness testing and some things, but I think it was right there at the door. They didn't get anything later in terms of feedback.
In our surveys, we actually ask about, we sort of replicate. A lot of our data are similar to the BRFSS, in terms of questions where it's self-report data. So we weren't taking blood or any other clinical information in ours. It was more self-report, some of which was about perception, some of which was self-reported health behavior and other things.
DR. FRANCIS: Yes, I was just wondering, basically whether that kind of information, rather than what's in the grocery store, raised more concerns and different kinds of confidentiality concerns. And I really meant to have that be for Kathy, too.
MS. ALEXIS: With our school systems, particularly with the school-based health centers, the providers would call the parents directly. And a lot of times, it was like nurse practitioners from the schools. They would call the parents directly and say, "This is the BMI, this is the child's weight, this is what you need to do, these are some suggestions of resources in the community." There was in-depth conversation with the provider and the parent. And this was mostly for the sites that participated in the project.
We did not hear of any confidentiality issues, we didn't hear of any teasing, because we felt that the health centers and the school-based health centers, they did really well in not really having the children stand out in any way. For example, the scales were not in the waiting room or anything like that. It wasn't in a public arena. They were mostly in the exam rooms, so if there was a conversation to be had with the child, it was done privately. Nothing was done outside, in front of their friends or anything like that. So I think in doing that, it minimized any possibility of teasing that would come directly from the assessment of the provider.
But I think, like I said, with the health center that did their peer-to-peer mentoring program, that helped a lot, when it came to the teasing part, because it's kind of like, "Well, that guy, he was large and he lost weight, and now, look how cool he is. He got money to teach us about how to lose some more weight." So it really not only raised the self esteem of the child itself, but it did put him in a place where he can now be of a mentor to his friends. So I think that was really one of the positive aspects of that project.
MS. GREENBERG: Your question started making me think about something, and then just the answers. Well, a year ago or so, this subcommittee had a hearing about the sensitive data categories or whatever, and adolescent health was a major focus. And being the mother of a daughter who was once adolescent, somehow they all have to pass through it, I guess, but weight can be a very sensitive issue. Even if you say nothing, it's sensitive. I mean, if the mother says nothing or the parent, it's sensitive to the child, and particularly to a daughter. So I'm thinking of this dynamic where, was this also up through the adolescent ages, where the nurse or practitioner called the parent?
MS. ALEXIS: Absolutely.
MS. GREENBERG: And how did they engage the child? I could see this being rather inflammatory, and I just wondered how you handled it.
MS. ALEXIS: Yeah, one of the school-based health centers that participated was a high school. And it was mostly elementary schools, middle schools and high schools, and I would say the more challenging population was the high school. And I think that has to do, there are a lot of social issues behind that. The community that we were working in, there were just other problems outside, kind of specific to what was mentioned earlier. There are so many other social issues going on in which healthcare was just not priority for these kids. We're not even talking about the parents. Just for the kids themselves, taking their health or eating well was not really the first issue.
But I feel that with the younger population, it was easier to share the information on healthier eating and physical activity. But the problem was really how to change the culture in the school itself, because you can't really ask a child to exercise more, where there's no recess, or there's nowhere for them to go out. I mean, I grew up, my elementary school, our recess was the street. They would close down the street and we would play outside. That's the reality for a lot of schools. And so, if you don't even have that opportunity to, let's not talk about a playground, if you don't even have the opportunity to just go outside, it's hard to have that conversation with a child or with a parent to say, "Your kid should do more exercise wise." So I'm not sure if I'm really answering your question, but I think there it really depended on the age range. The high school's was much more difficult.
MS. GREENBERG: With the older children, I would think that although a parent may observe that he or she thinks this child is overweight, or at risk of being overweight or even obese, people make those distinctions, many parents of adolescents have no idea what that child actually weighs. And the child does not want the parent to know what he or she actually weighs. So often when you take an adolescent to a doctor's appointment, the parent isn't even in the room, and then, afterwards, there's some discussion. But I'm just wondering if the child was told they were going to tell the parents. I don't know?
MS. ALEXIS: No, the child is told. I know that at the health centers, the child is told that the parent will receive a call from the health center to discuss the result of the physical, to discuss the results of the BMI and what that means. The child is told that, so it's a matter of what happens once the child gets home. I don't know.
MS. GREENBERG: There's some interesting issues there that go back to the whole discussion of adolescent health.
DR. FRANICS: And part of it, a core to the discussion of adolescent health actually was that, in a number of states, the law gives different access rights. For example, mental health information, unless there's an immediate danger, or reproductive or sexually transmitted disease information, without the adolescent's consent, the parent in a number of states, doesn't have a right to see that. So unless you have separate ways of handling some of those types of information, you can't even run a patient portal into an electronic medical record for adolescents. So that's part, that's the kind of information we were hearing.
One of the questions that I think we should also just have out on the table, and I don't know. We're beginning on shy on time for a number of people, but I think another issue that has been of concern with respect to consent, non-consent, opt-in, opt-out, is shifting uses of data.
So, if something's given for commercial use, or if something's given for research, and then it's given for commercial use. But even within data types, so I know discussions, for example, cancer patients entirely happy with the use of their data for research purposes in cancers and related illnesses, but not so happy with the use of their data, even for, say, mental health research.
And so I think one of the things we're going to need to continue thinking about is appropriate levels of transparency about data uses, and changes in data uses. I mean, I wonder, for example, if the BMI data then got used for a sexually transmitted disease study. Well, it would be really interesting to find out whether the kids with higher BMIs are more or less sexually active. That might be an interesting thing to find out, but that might be something that would really raise hackles, right. So we've got Seth and Denise and Kathy.
DR. FOLDY: You are starting to pull apart three strands that I've heard evolving in the discussion. And I think that Rosamond talked about this very nicely, that when you're talking about how data is used, that's a different question than talking about, and I think this came up when we were talking about the data bases, the multi-pair data bases. So there are several methods and there are several outcomes. Aggregating data, so you can't de-identify it, is one kind of method and one kind of outcome, and it has one set of effects on what we can do with information.
Consent is another strategy. It has other effects on what we can and cannot do with information. And then, really trying to control who uses the information towards what purpose, which probably is not easy to engineer in advance, and maybe even perhaps more of an enforcement. But in the end, it probably involves trust, too, is a third approach with its own ramifications.
MS. LOVE: I come at this from a slightly different view than some of you and I concur with Seth. And it brings me back to the large aggregate databases that I'm familiar with, that we work with. And that's why, I think we just have to do a better job of coming up with better analytic products or database designs, that have embedded intelligence to answer some of the questions that those databases can answer. And the patient won't even know that their data are being used, and they frankly probably don't care because it's so removed from their personal record.
And so, I really think getting smarter de-identification algorithms and embedded intel, together will take away some of this opt-in, opt-out on the personal health information, because I think that's going to be onerous to aggregate it for each individual study. We're going to do a BMI study, we're going to send a query out, opt in, opt out, aggregate the data for one-time use. I think that's going to be onerous, and so we probably need both. But I agree that we need a better aggregation methodology.
DR. FRANCIS: Kathy, I'd love to ask your reaction to the hypothetical.
MS. ALEXIS: In thinking of how we collected the data for our projects, as was stated earlier, we did all of our own collection. We created our own data collection tool that we used and we shared with the health centers. The health centers now use it as a way of creating their own dashboard. Unfortunately, because the primary care association is mandated by HRSA to not share data, any data that we share must be de-identified. And that would be any sharing the information with our funders, sharing the information with anyone, we really can't identify a particular health center to that data.
But I think in essence, we can say in this community, for example, a community in Queens, they had about 75 percent of that population of their children that was classified as obese. That was information we can share. But then, if we wanted to kind of delve down a little bit deeper with that, there were a lot of challenges. So I agree with other suggestions where we need to have a wider standard as to how to use that data, and probably open it up a little bit more so that we can see what it really says.
DR. MAIN: I think one of the issues that has to be put on the table, too, is I'm taking your example, and what would happen if all of a sudden, what was originally data collected for obesity was used for, I can't remember what we were using it for.
DR. FRANCIS: Sexual activity.
DR. MAIN: Yeah, STD's. And my first reaction to some of that was, I looked back at Kathy and I thought, here's the deal. Kathy went in, developed relationships, sort of laid out this long-term infrastructure for doing work with community health centers and communities for a long time. Something like that, it's gone, right? And so, you will never have the opportunity then to go back and do a really great study on STD and obesity.
And so, I think it's thinking about the big picture. I think your point about use now, use later, and you're not going to know what happens later, but you have to be really careful because you engage in this contract with people. And honestly, even words like "embedded intelligence", I think I would not use that because all of a sudden, it's like, oh, you're doing something. That's sort of what got us here in the first place and the whole trust thing. So just being really careful about how think about it now and later, because these relationships, as Walter said earlier, these are long-term. This isn't a project, this is really a commitment. And so, my first reaction is, oh, I worry about Kathy and her relationships and the community health centers and their relationships with people, and the school-based health centers.
DR. FRANCIS: Thank you. I think this may be a really great way to say what our next steps should be, which is we're going to start with an outline, with Susan's help, of what we've heard today about issues for trust, and methodologies, things that seem like likely to work, things that seem less likely to work. And then, see where we will be following up. But this is going to be part of a report, or at least a sketch of a report, that will be at the June 9th Health Data Initiative Summit, I think that is what that's called. Some of us will be there, and then the next step is going to be, we would really like to come out of this with some guidelines for good things to do in using the kinds of data sets.
I think we're also going to want to look at questions like what can make data sets more useable, and what kinds of recommendations should there be out there?
MS. BERNSTEIN: Are you anticipating that you, or is anyone on the committee anticipating that you might want to have another workshop in this series?
DR. FRANCIS: It's quite possible.
MS. BERNSTEIN: I'm just throwing the question out there.
MS. GREENBERG: Just being sort of very specific now that today's the 12th and that meeting is June 9th, so we have the report from February 8th, that I think has been vetted, etcetera. It's going to go up on our website, if it isn't already there, and it's certainly in a condition that we can distribute it. The question is, there isn't enough time to get this one, integrate this, necessarily, but could there be some key findings or observations? Is the subcommittee willing to work with Susan on that, so that maybe we could have at least, if not integrated right into that document at this point, an additional smaller document? That would require obviously on Susan's part, putting this together, and then some teleconferences, I think.
DR. FRANCIS: That would be our hope.
MS. BERNSTEIN: So I understood when we scheduled this meeting, that the point was to have it, realizing that it was later than we wanted to have it from the original scheduling, so that we would have sort of talking points or bullets or whatever it is, to participate adequately in that meeting, not necessarily to have a report written. Although, you know, if we could do that, that'd be fabulous. I think to have enough information for somebody to participate in the June 9th meeting based on what we did here, as representing NCVHS.
MS. GREENBERG: Initially, we actually thought that we were being asked to make some kind of presentation at that meeting. But it turns out, that's not really the type of meeting that it is. It's a lot of demonstrations and a lot of workshops. And so, what I have kind of worked out with Todd Park and Greg Downing, is that we will have several members of the committee will be there. Leslie's going to be there, you're going to be there. I think you're not able? Are you going to be there, Paul, and Justine. And Ed Sondik, and you can attend whatever sessions you want, but I would ask you all to go to the Community Health Data, at least some of you, to be at that Community Health Data session, which Ed Sondik is organizing. And we can make available at that session a document.
So the question is, we certainly have the document that's came out of the February 8th meeting. My question was, what you want to add to that, either to that document or as a suite of documents or whatever, given the period of time we have. Now, also obviously, you can speak up in workshops and whatever you want to bring to it. But we don't have the time, I don't think, to fully integrate today's session into that document.
DR. SUAREZ: Is that document already approved by the committee?
MS. GREENBERG: It went out.
DR. SUAREZ: So it has been formally approved, so it's ready for release?
MS. GREENBERG: Yes, we sent it out. It doesn't have recommendations in it, but we sent it out to the full committee. And it went through the subcommittees, I think it went to the executive subcommittee. And if anybody had any issues with it, we can stamp it "discussion document" or something.
DR. FRANCIS: My thought in reading it was that it was an initial, the best draft from the February meeting. But I had always understood that some of what happened here would be.
MS. GREENBERG: It would eventually go into it, and that might be a final product, that would then be sent to the department as approved, with a cover letter that might have some actual recommendations.
DR. FRANCIS: Or that there might even be a need for another workshop, because the goal of this is best practices in the kind of feedback loop community research together with how to be appropriately protective so that we don't have trust disasters, of the kind that happened in Texas with the blood spots, or that we were jokingly referring to, or not so jokingly, with research that ended up surprising people.
MS. BERNSTEIN: I assumed that the document that we had from February was incomplete without the rest of the pieces of the different workshops.
MS. GREENBERG: Well, it's sort of a part one.
MS. KANAAN: Right, it was a snapshot of a particular moment in time. And Leslie and I actually talked on the way over this morning about creating a maybe one-page document with just the key bullet points from this discussion, and these presentations initially.
MS. GREENBERG: It seems like it'd be a lost opportunity not to share that document that's already been.
DR. HORNBROOK: Leslie and Marjorie, this is Marc Hornbrook. I'm a member of the committee. I have no conflicts and I'm from Kaiser Permanente Center for Health Research in Portland, Oregon. And normally, I would be there in the room, except that I'm trying to get a grant application out tomorrow. The thing I was thinking about is the health information exchanges. Even though they are designed for business purposes, the fact that medical information, as these things work, flows back and forth across lots of different actors, pharmacies, hospitals, insurers, FHQCs, government agencies, et cetera, Medicare, Medicaid, state health insurance. And then these new health insurance exchanges, which evidently are going to be a way to bring in 32 million US citizens.
It raises this notion of community health assessment, though aggregated EMR data. And Marjorie, I'd sent you an email of an example of an organization called OCHIN. That is tying together FHQCs through a common electronic medical record. It happens to be the Epic vendor system. But they have a research arm, and as a non-profit, they can get grants. So they've been doing research projects. The problem is, of course, they don't cover hospital care. They only cover outpatient care in these FHQCs.
But we've been looking at the data and you get a very different kind of picture of community health when you look at the clinical care, as opposed to a community health survey. But I'm just wondering, somewhere in our strategic planning, you should come back to this when we see more development of these kinds of systems and data interchange developments, as we've been promised through the Office of the Coordinator.
DR. FRANCIS: I think that's a very good point and it's actually part of why I was asking whether any of the groups had integrated clinical data. So I think we're at a point where, we're losing people with airplane needs, and so including myself, I'm sorry to say. We're going to bring this to an end and thank everyone, but most especially, I need to say to Maya Bernstein, thank you, thank you, thank you.
MS. BERNSTEIN: When I said thank the staff, I didn't mean me.
DR. FRANCIS: I mean you, and I also need to say the same thing to Gayle, who held everybody's hands and to all the other staff.
MS. BERNSTEIN: To Jeannine in particular.
DR. FRANCIS: Yes, Jeannine, the person who would emails us and says, please, please, please, get it done. Thank you.
MS. BERNSTEIN: So we'll set up some phone calls and we'll figure out, over a conference call, if we'll have a new workshop and when that might be and what our next steps are.
(Whereupon, the meeting adjourned at 3:55 p.m.)
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