5

Understanding Participant Needs and Preferences and Improving Diversity and Equity

In this session, panelists considered the policy issues associated with the implementation of genomics-based programs in health care systems and potentially in public health. Topics discussed included approaches to ensuring data security and participant privacy and methods for supporting equity and accessibility in genomics-based programs. Sara Knight, a professor in the Division of Preventive Medicine at the University of Alabama at Birmingham, discussed her work on understanding participant needs and addressing issues of diversity and equity in genomic health services. Carol Horowitz, a professor of population health science and policy at Mount Sinai Hospital in New York City, described the collection of genetic data from a diverse population while keeping the perspectives of the community in mind. Abel Kho, the director of the Center for Health Information Partnerships at Northwestern University, described the work of Pastors4PCOR as an example of taking research out into the community. The session was moderated by Vence Bonham, a senior advisor to the Director on Genomics and Health Disparities at NHGRI.

PARTICIPANT NEEDS, DIVERSITY, AND EQUITY¹

One of the important elements to consider when developing services is what patients need and want, Knight said. She described a series of studies designed to better understand patient preferences related to genomic testing, including a study examining preferences for Lynch syndrome screening in the general population and studies about integrating genomic screening in the Department of Veterans Affairs (VA). In all of these efforts, Knight emphasized the importance of shared decision making for ensuring diversity and equity in programs.

Patient, Public, and Clinician Preferences

The first study that Knight described was designed to understand preferences for genetic testing for Lynch syndrome (Walsh et al., 2012). Inter-

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¹ Knight clarified that the views expressed in her presentation are her own views, and do not necessarily reflect the position or the policy of the Department of Veterans Affairs, the National Cancer Institute, the National Human Genome Research Institute, or the U.S. government.

views and focus groups were conducted with patients at high risk for Lynch syndrome and with members of the public who were interested in Lynch syndrome screening. The participants were very enthusiastic overall, Knight said. Responses indicated that those who participated in the focus groups were willing to pay for the test, that they were very concerned about false negative results (i.e., actually having a condition that was not picked up in a screening test), and that they associated genetic testing with health benefits. Clinicians were also surveyed, and their concerns focused on guidelines for screening and the patient and family psychosocial experience (e.g., anxiety), including potential downstream harms.

The results of the first study on preferences for genetic testing for Lynch syndrome were used to design a Web-based survey, including a discrete choice experiment, to understand the characteristics of genetic testing that might influence preferences for getting tested. A probability-based online group of 355 U.S. residents aged 50 and over was surveyed in April 2010 (Knight et al., 2015). Knight noted that these were individuals who would most likely already have had experience with colorectal cancer screening because U.S. Preventive Services Task Force guidelines recommend routine screening starting at age 50. In response to the “best” test scenario, in which the test results would be shared with the primary care provider and there was a zero percent chance of false negative results, the researchers found that 97 percent of those surveyed would opt for using genetic testing. In the “worst” test scenario, test results would be shared with life and health insurance companies and there was a 20 percent false negative rate. In this case, 41 percent would choose to use genetic testing, although as Knight added, the survey was conducted around the same time that the Patient Protection and Affordable Care Act (ACA) was enacted, and this may have changed some perceptions surrounding preexisting conditions and insurability. The results demonstrated that the interest in and use of genomic services varies depending on participant preferences and also on the setting and conditions that surround the test, Knight said.

Incorporating Genomics into Routine Care for Veterans

Knight continued this line of study within the VA, conducting a retrospective cohort analysis of how genomics was being incorporated into routine care for veterans with colon cancer. This was followed by key informant interviews with clinicians in the Veterans Health Administration (VHA) to identify the barriers to and facilitators of routine genomic services for colorectal cancer patients.

The sample cohort included all veterans under age 50 in the VHA system who had been diagnosed with colorectal cancer between 2003 and 2010. The majority were men, which is typical for samples collected from

the VHA, Knight noted. Thirty-five percent were African American. Many of the individuals in the cohort had been diagnosed with late-stage tumors (stages 3 and 4). Knight said that the average age was 46 (with a range of 19 to 55 years), indicating that many of these individuals may not have been diagnosed through screening. At the time of the study (2003–2010), many of the guidelines recommended that those under age 50 diagnosed with colorectal cancer be given immunohistochemistry (IHC) and microsatellite instability (MSI) testing of tumor tissue to determine whether genetic testing for Lynch syndrome would be recommended. This molecular analysis of tumor tissue is a relatively low-cost approach for decision making about genetic testing, Knight noted. She shared unpublished data that indicated a marked increase in use of IHC and MSI testing in the VA beginning in 2010 as the systematic implementation of molecular analysis of tumor tissue was initiated, and she said that another cohort that captures the full implementation effort is now being assessed.

In a study of barriers to and facilitators of genomic health services in the VA, Knight and colleagues interviewed VA clinicians and administrators about their experiences referring veterans diagnosed with colorectal cancer for genetic counseling, molecular analysis of tumor tissue, and genetic testing. Clinicians from both high-oncology-volume facilities and low-oncology-volume facilities were interviewed, including oncologists, gastroenterologists, and primary care physicians (Sperber et al., 2016). Molecular testing of tumors was seen as low-cost and advantageous for decision making, Knight said, though most clinicians responded that they saw few cases of younger patients diagnosed with colorectal cancer and infrequently used molecular tumor tissue testing. Clinicians also noted that there were no request and approval routines in place in the VHA at that time. Clinicians were interested in the opportunity to consult with experts, such as clinical geneticists or genetic counselors, but they said that there was no standard referral process and that some referrals went through gatekeepers, which made the process time consuming. Clinicians (including oncologists and gastroenterologists) thought that they did not have the expertise to talk with patients about genetics and genomics. They perceived that information on genetics and genomics would be valuable for their patients, but they did not know where to obtain the expertise within the VHA. These findings on the lack of expertise in genetics and genomics suggest an opportunity for education, Knight said, given the limited workforce in genetic counseling and clinical genetics in VA and non-VA health care settings.

Aligning Genomic Health Services with the Values and Preferences of Veterans from Diverse Backgrounds

A study now under way at the VA is aimed at informing the design of a genomic medicine service in the VHA that would be aligned with the preferences and needs of veterans from diverse backgrounds.² The study seeks to understand veterans’ preferences for the return of results from whole-genome sequencing. Knight briefly described some of the challenges that can be encountered when trying to understand population perspectives on genomics using methods such as advisory committees, focus groups, surveys of convenience samples, and consensus panels. Each of these methods alone is limited in its ability to provide a generalizable picture of the types of genomic health care services that would be valued in diverse populations.

To address these challenges, Knight and her colleagues are using a mixed methods design beginning with interviews and focus groups of 120 veterans from four geographic regions of the United States (Northeast, Southeast, South Central, and Western) to assess the types of results that veterans would find valuable from whole-genome sequencing and the types of health care services they would want in order to understand and use the results. The focus group data will be used to construct a discrete choice experiment survey that will be tested for relevance to the VA and then delivered to a large random sample of veterans drawn from all veterans cared for in the VHA. Minority veterans will be oversampled, and the overall sample will be of sufficient sample size to examine differences in values and preferences across subgroups of veterans. The random sample of veterans from diverse sociodemographic groups will provide generalizable information on veterans’ preferences for the return of results from whole-genome sequencing.

The study was designed to comprehensively engage veterans and key VHA health care system leaders with researchers in the dissemination of findings in the VHA. Using a democratic deliberation method, VA stakeholders, including clinicians, policy makers, and veterans, will be educated about the integrated results of the focus groups, interviews, and survey and given an opportunity for informed discussion as a group to ultimately help define priorities for veteran-centered genomic testing and to inform VA efforts to develop policies for the return of results from whole-genome sequencing.

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² For more information, see https://www.hsrd.research.va.gov/research/abstracts.cfm?Project_ID=2141705720 (accessed January 24, 2018).

Multi-Level, Multi-Process Stakeholder Engagement

In conclusion, Knight emphasized the need for a multi-way, iterative dialogue among veterans affected by policies on genomic health care services, health services researchers, and policy makers. She said that policies developed with public participation are more likely to be perceived as legitimate and trusted and are more likely to be implemented. Her studies are now using a highly nuanced, multi-level, multi-process stakeholder engagement process that involves in-depth key informant interviews and representative surveys to inform ethical considerations, research methods, and translational activities; advisory boards of patients, family members, clinicians, health system leaders, and community leaders; and democratic deliberative process groups to engage the public, policy makers, and clinicians in the development of sensible genomic health care policies and genomic medicine programs that can be implemented in diverse communities and health care systems.

ENGAGING DIVERSE POPULATIONS IN GENOMICS-BASED RESEARCH

Horowitz began by sharing some perspectives from her diverse partners on a genomics stakeholder board (Kaplan et al., 2017). The board was formed to help guide the genomics work of the Center for Health Equity and Community Engaged Research at the Icahn School of Medicine at Mount Sinai in New York City and is composed of patients, advocates, clinicians, researchers, systems leaders, funders, and industry representatives. Horowitz listed a series of questions the board members have considered as they move forward with research in their community:

• Whose decision is it to integrate genomics? In other words, who needs to agree that genomic testing can bring value (e.g., payers, providers, patients, policy makers, researchers)? Understanding the audience for the evidence will determine the kinds of research questions that need to be asked.
• Who is at the table nationally and locally? Who is participating in the discussions and making decisions regarding what questions need to be asked, how those questions will be answered, and what will be done with the results?
• If genomics is not studied, will it happen anyway? If we do not study genomics, the board asked, who will, and in which patients? The answer to that question often comes down to funding. If only academic medical centers are funded to do genomics research, then it will only be patients who go to academic medical centers

• who are part of the research. It is important to reach out to more diverse sites, Horowitz said. The conclusion of the board was, she said, “One needs to be vigilant. The research should proceed, but carefully.”
• Can genomics-based research reach diverse participants and be equitably distributed? The answer is yes, Horowitz said, if the research is intentional, valued, resourced, and done carefully. She shared the input of one community partner who asked how science can be advanced in a good way, while not taking advantage of the vulnerability of a community. Horowitz observed that stereotypes and paternalistic attitudes can promote concerns among researchers about engaging minority populations that are unfounded, and she recalled one community partner who suggested that genomics can be integrated into community health in an equitable way. It is important to recognize who is rejecting whom, Horowitz said. Are communities really saying they do not have an interest in genomics, she asked, or are providers and researchers focusing on implementing where they have already been successful because it may be less difficult?

APOL1 Risk Variants

As an example of the collection of genetic data from a diverse population with the perspectives of the community in mind, Horowitz described the Genetic Testing to Understand and Address Renal Disease Disparities (GUARDD) study,³ a study examining the risk variants of the apolipoprotein L1 gene (APOL1).

People of African ancestry have a risk of kidney failure that is about three to four times higher than people of Caucasian or European ancestry (NIDDK, 2016). One out of seven people of African ancestry carries a genetic variant of APOL1 that increases the odds of kidney failure approximately tenfold if the individual has hypertension, Horowitz said (Genovese et al., 2010; Horowitz et al., 2017). This finding can explain up to 70 percent of the racial disparity in kidney failure, she said. Horowitz noted that she first became aware of this disparity when it was raised at a community board meeting. As a researcher, she felt it was necessary to have patient and community support to pursue any research in this area. After approaching a genetic ethicist for advice, Horowitz was initially advised against any race- or ancestry-based genomics research, being told that it would “set the disparities movement back 30 years.” However, when Horowitz spoke

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³ For more information on the GUARDD study, see https://ignite-genomics.org/sites/mount-sinai (accessed January 12, 2018).

with community leader Mimsie Robinson of the Bethel Gospel Assembly in New York, he was in favor of pursuing this research topic because gaining a better understanding of common genetic variants in African Americans associated with kidney disease might help to alleviate possible providers’ stereotypes that black patients are sick due to non-compliance or other negative attitudes or behaviors (Horowitz et al., 2017).

The GUARDD study is a randomized controlled trial funded by NHGRI as part of the IGNITE network. The study enrolled adults of self-reported African ancestry with hypertension and without diabetes or kidney disease, Horowitz said. Participants were randomized to APOL1 testing immediately, or delayed testing 1 year later. Because the availability of genetic counselors was limited, it was decided, with input from participants and providers, that local community residents with college degrees would be trained by genetic counselors to return results to participants with oversight from the counselors.

A community–clinical–academic team developed the study methodology. The process began with formative research, introducing GUARDD at five federally qualified health centers, six neighborhood practices, and four academic primary care practices throughout New York City. At each site, the proposal was presented to the providers for their feedback. Many of the providers did not have much experience with genomics or research, Horowitz said. The recruitment strategy was developed by the team with the participants in mind, and Horowitz called it “a good invitation to a good party.” In other words, consider who the target audience is, and be flexible with when and where those people can participate. Recruiters were drawn from the community, and recruitment materials were developed with appropriate graphics and language and at appropriate literacy levels.

Enrollment of over 2,000 participants was completed in 2 years. At 3 months, 93 percent of participants were retained, and at 12 months, 88 percent. Horowitz noted that this was a difficult-to-reach population with some people experiencing extreme social stressors such as homelessness and recent incarceration and others having competing demands with jobs and professional conflicts. Despite this, there was a very low refusal rate (only 12 percent of eligible participants refused to join the study). All participants were of African ancestry, but they were diverse in other ways: 20 percent had low health literacy, 44 percent had less than a high school diploma, 53 percent had income under $30,000, 48 percent were non-adherent to their blood pressure medications, and 47 percent had uncontrolled blood pressure.

Based on a survey of the providers recruited to the study, about half were non-white. Of those, half were Asian, and half were black or Latino. Most of these clinicians responded that they had taken a formal genetics course, but only one-third had ordered a genetic test for a patient in the

last year. Even fewer (one-fourth) felt prepared to communicate results with patients who had genetic tests for chronic diseases. More than half of the providers responded that they had concerns about insurance discrimination, and more than three-quarters said they did not trust genetic testing companies. Most providers indicated that race and ancestry were good clues as to who should undergo genetic testing and that genes may play a role in existing health disparities.

A baseline survey of the beliefs and concerns of the 2,000 study participants revealed that few had ever had a previous genetic test or understood genetic testing. Despite that, Horowitz said, nearly all thought it was a good idea to get genetic testing to assess chronic disease risk. Most also wanted their children to be tested for APOL1 variants. Preliminary results 3 months later, after tests had been done and results had been returned, found that nearly all would get tested again and were satisfied with the timing, type, and amount of information they received.

Preliminary clinical results of the study suggest that participants who were told they had high-risk genetic variants had a greater decrease in systolic blood pressure at 3 months, Horowitz said, which was associated with self-reported improvements in blood pressure medication use. More detailed results from the study are expected to be published later in 2018.

Exploring Lessons Learned

In conclusion, Horowitz said, diverse populations and sites should not be just a funding strategy for studies. Patients and community partners emphasized that if researchers want to learn about them, then they need to be included. Partners also said that “the culture of understanding is far more important than the culture of fear, and the culture of understanding has no color.” Finally, patients and community partners need to have their voices harnessed, Horowitz said, adding that “people become engaged when someone who looks like them is at the helm.” She concluded her presentation with a message from her community partners: “Do the research now, do it right, and make diversity and engagement a priority from the get-go. Don’t make it an afterthought.”

CLOSING THE CIRCLE BETWEEN RESEARCH AND THE COMMUNITY

There are very good scientific reasons for having diversity in research, Kho said. He referred participants to the work of Green and colleagues on the ecology of care as an example (Green et al., 2001). Using administrative data, Green and his colleagues described how people use the health care system and followed the health care journeys of people who came in to see

a provider over the course of a month. In 1 month, for every 1,000 people, 800 reported symptoms of illness, 217 visited a physician’s office, fewer received care in other health venues (complementary or alternative care provider, hospital outpatient clinic, home health care, emergency department), 8 were hospitalized, and 1 or fewer were hospitalized in an academic medical center. Most research is conducted in academic medical centers, Kho noted. Overall, during the 1-month study period, only about 22 percent of the people in the study had seen any provider at all. This finding indicates that population studies, including genomics-based screening programs, may miss about 80 percent of the targeted group, which highlights the need for research to go out into the community, Kho said.

Kho described a similar analysis performed by his group using recent data to estimate how many people actually have their data captured in an electronic health record (EHR) in a given month. His analysis suggests that 20 percent of individuals studied are seen by a provider in a given month and therefore have a chance of having their data captured in the EHR. An additional challenge with EHR data is that they are fragmented across institutions. On average, about 20 percent of any person’s information is likely missing across systems, Kho continued. If a patient goes to one health system, there is a good chance that there is some record of that person in another system within the network (Kho et al., 2015). The extent varies somewhat across different conditions. For a patient with type 2 diabetes, for example, looking at one institution provides only a portion of that person’s record. Looking across all of the systems in that area gathers about 20 percent more data. Furthermore, only about one in five people in a community will have EHR data of any quality. From a genomics standpoint, if research is tethered to EHR data, then phenotypic information for a vast proportion of the population will be missing in a pure, care-based approach. This is a potentially significant limitation, Kho said. While the EHR is a good resource if it is available, from an epidemiological standpoint, there are many places where there will not be EHR data. The question is how to obtain that wider set of information.

Kho said that his work has been focused on how to get out of the academic center and into the community. About half of his work focuses on quality improvement and measurement. He pointed out that there are significant financial incentives for quality improvement within the health care systems. If research goals can be aligned with the quality improvement initiatives of health care systems, a sizable amount of funding can be tapped to underwrite the research infrastructure, he said.

Pastors4PCOR

As an example of taking the research out into the community, Kho described the work of Pastors4PCOR, a Patient-Centered Outcomes Research Institute (PCORI)-funded community health outreach initiative engaging faith-based communities in Chicago’s south side and south suburbs.⁴ Kho suggested that Pastors4PCOR is actually the community engaging academia rather than the other way around. In this emerging model, when academia fails to sufficiently engage with the community, the community takes the initiative and engages researchers on its own terms. A group of community advocates and faith-based partners, including leaders from local churches, researchers from academic medical centers, and community health partners, came together to identify research priorities based on community interest.

Pastors4PCOR brings together these stakeholders to create a survey skills training program that allows community members to support the health and well-being of their communities. Essentially, Kho said, pastors and key members of the parishes are being trained to engage in research. The initiative is very effective at promoting research by focusing on being informed, having respect for the lived experience, trust, understanding the context of where community members are, and working together on issues that matter to all partners, he added. Over the past 2 years, Pastors4PCOR has been conducting health research ambassador workshops around Chicago and is now beginning to spread the movement to other areas in the United States, including Los Angeles and parts of Arkansas.

One of the most valuable lessons Kho said he has learned from Pastors4PCOR is to find an elegant way of distilling messages into something simple and understandable. For example, informed consent is explained as “making sure everyone knows what the study is about and understanding they can withdraw at any time,” and confidentiality “requires a clear explanation of how data sharing will be respected and processed.” “Voluntariness” is a term they use to describe how there should not be consequences for saying “no” to engaging in research. For example, participants should not be pressured, made to feel bad, threatened (e.g., with loss of services), or offered lots of money to take risks.

Surveys of the ambassadors-in-training show that they tend to be around age 50, with the majority (80 percent) female, and they are generally very well educated (75 percent have college degrees or higher). Although technology use in the wider population in Chicago is quite high, Kho said, the surveys show that while the ambassadors do use the Internet,

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⁴ For more information on Pastors4PCOR, see https://www.pcori.org/research-results/2015/pastors-4-pcor-engaging-faith-based-communities (accessed January 3, 2018).

smartphones, and e-mail, they do not use social media as much, which is becoming a bit of a challenge as they begin to engage in the research. The ambassadors ranked high blood pressure, diabetes, cancer, substance use issues, and mental health issues as the most prevalent health conditions in their faith-based communities, followed by obesity and gun violence. Kho noted that this was confirmed by looking at the co-localized distribution of the participating churches and the distribution of cases of hypertension and diabetes in Chicago. When the ambassadors were asked what they would like to learn more about from researchers, the top-ranked responses were cancer, high blood pressure, diabetes, mental health disorders, heart disease, and stroke. The top health-related factors that faith-based communities should focus on were identified as behavioral information and education, followed by support for mental health, access to health care, family and social support, access to healthy foods, and community safety. At the end of the 12-week training program, nearly all of the participants felt confident that they could communicate the concepts of patient-centered outcomes research back to the community in a way that would be effective.

To conclude, Kho briefly highlighted the PCORI-funded ADAPTABLE (Aspirin Dosing: A Patient-Centric Trial Assessing Benefits and Long-Term Effectiveness) trial as an example of one of the Pastors4PCOR projects. As discussed, hypertension, diabetes, and cardiovascular disease are priorities in many of the communities. Kho and colleagues are helping Pastors4PCOR drive the trial, though he noted that there have been quite a few unanticipated challenges. For example, there is very little in the way of infrastructure, including computer support. At the request of those involved with Pastors4PCOR, Northwestern has helped set them up with tablets and computers, which gives them the ability to check participant eligibility across the different systems in an anonymous way and to start recruitment.

DISCUSSION

To start the discussion, Bonham prompted panelists to suggest to the Roundtable one specific activity or focus area for increasing diversity in genomics-based programs. Knight recommended that the Roundtable carefully consider the types of diversity that are important to include when designing community-based care and health care systems (e.g., race, ethnicity, education, socioeconomic status, material hardship). Assumptions are often made that the fears or concerns expressed by certain groups are race based; however, that is not necessarily the case. Kho emphasized the need to get out into the community more often in order to bring in diverse perspectives. There is a lot of ongoing work that, while not focused on genomics, could potentially feed into genomics-based efforts. Horowitz suggested that

the Roundtable could become more diverse or could form a “network of networks” to reach out to more diverse places for more diverse perspectives. Learning from other disciplines about their successes in creating a more diverse research workforce and research programs that engage diverse populations could also be helpful, Horowitz said. Genomics is a newcomer to translational research relative to some other disciplines, and it can learn from them, she added.

Participants considered ancestral versus genetic identity, genetic discrimination, and the equitable distribution of the benefits of genomics. Throughout the discussion, speakers highlighted the need to consider the context of implementation and to engage participants in a thoughtful way.

Genomics and Ancestral Identity

Horowitz said that participants were recruited to her study in real time based on their self-reports of having African ancestry (not being African American), as opposed to being genetically defined. This is an important distinction, she said, as the study was more about ancestry in genomics than race in genomics. In this case, there happened to be a close correlation between people who self-reported African ancestry and those who had genetic African ancestry, but determining genetic ancestry was not part of the study. Horowitz noted that the researchers spent considerable time consulting with a diverse group of experts and stakeholders to determine how best to ask community members about their African ancestry. The study also considered other social determinants of health and how they intersect with genomics, including depression, anxiety, racism, life chaos, food insufficiency, and other elements. Knight said that some of her studies ask very detailed questions about race, ethnicity, and ancestry, in part to attempt to recruit participants from groups underrepresented in genomics research, such as those of Asian and Indian ancestry.

When asked if researchers had concerns about not genetically confirming self-reported ancestry, which could potentially affect conclusions made from research, Horowitz emphasized the need for care and sensitivity in reporting genetic ancestry to individuals, and she noted the potential challenges of having to report to individuals that they do or do not actually have genetic evidence of the ancestry they identify with. Horowitz and Kho both noted their doubts about the usefulness of genetic confirmation of ancestry. It might be interesting from a methods standpoint, Kho said, but he agreed that handling discrepancies would be a challenge. Bonham said that his work is focused on better understanding social and cultural contexts and added his caution that in considering variation in the genome in relation to ancestral backgrounds, genomic measurement of identity is something that requires further discussion. Genomic information and

variations across ancestral backgrounds hold promise for research, but contextual issues should be carefully considered, Horowitz and Bonham suggested, adding that the issues might be a topic for future discussion by the Roundtable.

Genetic Discrimination

Differences in policy may affect populations differently, said a workshop participant. For example, genomic screening studies or cascade testing of current or former members of the military could affect their careers or retention of benefits. Knight responded that veterans, military service members, and members of the federal government are not covered by the Genetic Information Nondiscrimination Act of 2008 (GINA); however, in her own research she has observed that veterans are covered by other policies that may actually be more protective of their rights than GINA. Understanding the Department of Defense and VA policies is important when reassuring people about their level of protection, so that a veteran or a military service member can make an informed decision about participating in genomic studies. Ethically, it is important to be aware of and thoughtful about the fact that the policies that govern their protections are different from the policies that govern the protection of most of the rest of the population.

Another participant asked whether the panelists had heard any concerns from communities about the potential for genetic discrimination and what can or should be done to ease those concerns, especially in light of anticipated changes to the ACA. As a provider, Kho voiced concern and added that health care systems appear to be concerned, and he said that he had observed distrust in communities. Knight said that the issues of privacy and protecting one’s ability to get health care were identified as very important in her first preferences study. Her current study, which is a much larger, population-based study, will allow her to analyze subgroups (including veterans who are underserved and underinsured) for differences in their preferences and perspectives regarding data protections and participation. She said that in her first study there was optimism in the focus groups that the ACA would address concerns regarding preexisting conditions. There is greater concern now, however, and that concern will need to be taken into account as an important contextual variable in the current study. She said that she expects that the population-based survey would include questions to understand how the heightened concern about genetic discrimination might influence preferences and value.

Equitable Distribution of the Benefits of Genomics

Several individual participants highlighted several areas to consider when discussing diversity and equity in genomics-based programs, including disparities in access to and use of health care, rare diseases, health literacy, individuals with limited capacity to consent, and the use of trusted brokers to reach out to underserved populations.

One disparity to keep in mind is whether and how people are covered by health care benefits and the extent to which they use services, George Isham said. Uptake is variable, he noted, and is affected by social and other factors. When considering how health care systems can scale their approach to genomics in terms of databases and investment in large infrastructures to support programs, it is also important to consider how implementation can be done to ensure that the benefits of genomics are distributed more equitably across the population. In this regard, Kho highlighted the issue of data sharing by health care systems (see Chapter 4 for more information). He observed that there are commercial endeavors working toward collecting and linking all of the different types of data available for an individual, independent of the health care systems. Leaders of health care systems need to be thinking much more broadly about how to bring together the many elements of the health data world, where bits of data are strewn everywhere, he said.

The low prevalence of certain diseases is a challenge for genetic screening, said a workshop participant. Low-prevalence diseases include both rare diseases and diseases that are very specific to certain populations. The participant asked whether there are efforts to ensure that particular genetic screening tests are accessible to those groups that might be affected more than others and also asked about efforts to include data on rare diseases in databases. While highly prevalent conditions can be studied using population-based approaches, rare diseases are often brought to the forefront by the self-organization of those affected, Kho said. In many cases, families affected by rare diseases have pulled together to form registries, which are often quite deep and include informed consent models and biospecimens. Kho also noted that some of these groups have come forward asking to build a link to their disease in the EHR in order to advance research. He agreed that there is a need to find equitable approaches to using genomics to study rare diseases, and he emphasized that data have value and that it is important to ensure that the people whose data are being shared and used are reaping the benefits. Knight emphasized the importance of transparency when designing genomic medicine programs, adding that understanding the perspectives of different groups, some whom could benefit more and others who might benefit less, is critical to equitable system design and decision making.

Patients who have limited capacity to consent to research projects due to learning difficulties, delirium, dementia, or related conditions represent another area of diversity for consideration. These groups of patients are often underrepresented in studies, Turner said. Based on his experience, patients at the sickest end of the spectrum have comorbidities and polypharmacy that can be barriers to enrollment in studies; however, these patients could benefit from pharmacogenomics knowledge. Turner asked about any initiatives to include this cohort in genomics programs while also protecting and preserving their dignity. The field needs to think very broadly about the groups that are underrepresented in genomics research, Knight said. Another underserved population is people with multiple morbidities who live in highly rural areas in the southern United States, she added. Horowitz observed that some individuals who are thought to be unable to consent actually can consent when appropriate language, literacy level, and techniques are used (e.g., the teach back method). On the other hand, she cautioned, it is important not to coerce people or to assume understanding based on physical cues. Bonham added that the All of Us initiative is being very thoughtful about how it defines diversity and is considering factors beyond those of economics, race, and ethnicity.

Building trust with diverse groups to encourage participation in genomics is important, and having trusted brokers to facilitate communication and engagement with underserved or diverse populations would be helpful, said a workshop participant. The community health worker model has been found to be a very well-accepted way of engaging the community, Kho said, but there has to be a willingness to learn and listen based on the context of where you are. Horowitz suggested directly asking the group that you wish to engage with whom they trust. For example, some of the younger people in the communities they serve have become less trusting of churches, meaning that other trusted brokers need to be identified, she added. Asking small business owners and leaders in the business community in small southern towns to become more involved in stakeholder groups could be another solution, Knight said, because businesses are often a hub where people congregate. Business owners are very knowledgeable about their communities and can be influential as representatives of their communities on advisory boards or panels that are involved in engagement.