Lessons Learned from the Pilot Phase of a Population-Wide Genomic Screening Program: Building the Base to Reach a Diverse Cohort of 100,000 Participants
Background and Objectives: Genomic information is increasingly relevant for disease prevention and risk management at the individual and population levels. Screening healthy adults for Tier 1 conditions of hereditary breast and ovarian cancer, Lynch syndrome, and familial hypercholesterolemia using...
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Veröffentlicht in: | Journal of personalized medicine 2022-07, Vol.12 (8), p.1228 |
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creator | Allen, Caitlin G Lenert, Leslie Hunt, Kelly Jackson, Amy Levin, Elissa Clinton, Catherine Clark, John T Garrison, Kelli Gallegos, Sam Wager, Karen He, Wenjun Sterba, Katherine Ramos, Paula S Melvin, Cathy Ford, Marvella Catchpole, Kenneth McMahon, Lori Judge, Daniel P |
description | Background and Objectives: Genomic information is increasingly relevant for disease prevention and risk management at the individual and population levels. Screening healthy adults for Tier 1 conditions of hereditary breast and ovarian cancer, Lynch syndrome, and familial hypercholesterolemia using a population-based approach can help identify the 1−2% of the US population at increased risk of developing diseases associated with these conditions and tailor prevention strategies. Our objective is to report findings from an implementation science study that evaluates multi-level facilitators and barriers to implementation of the In Our DNA SC population-wide genomic screening initiative. Methods: We established an IMPACTeam (IMPlementAtion sCience for In Our DNA SC Team) to evaluate the pilot phase using principles of implementation science. We used a parallel convergent mixed methods approach to assess the Reach, Implementation, and Effectiveness outcomes from the RE-AIM implementation science framework during the pilot phase of In Our DNA SC. Quantitative assessment included the examination of frequencies and response rates across demographic categories using chi-square tests. Qualitative data were audio-recorded and transcribed, with codes developed by the study team based on the semi-structured interview guide. Results: The pilot phase (8 November 2021, to 7 March 2022) included recruitment from ten clinics throughout South Carolina. Reach indicators included enrollment rate and representativeness. A total of 23,269 potential participants were contacted via Epic’s MyChart patient portal with 1976 (8.49%) enrolled. Black individuals were the least likely to view the program invitation (28.9%) and take study-related action. As a result, there were significantly higher enrollment rates among White (10.5%) participants than Asian (8.71%) and Black (3.46%) individuals (p < 0.0001). Common concerns limiting reach and participation included privacy and security of results and the impact participation would have on health or life insurance. Facilitators included family or personal history of a Tier 1 condition, prior involvement in genetic testing, self-interest, and altruism. Assessment of implementation (i.e., adherence to protocols/fidelity to protocols) included sample collection rate (n = 1104, 55.9%) and proportion of samples needing recollection (n = 19, 1.7%). There were no significant differences in sample collection based on demographic characteristics |
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Screening healthy adults for Tier 1 conditions of hereditary breast and ovarian cancer, Lynch syndrome, and familial hypercholesterolemia using a population-based approach can help identify the 1−2% of the US population at increased risk of developing diseases associated with these conditions and tailor prevention strategies. Our objective is to report findings from an implementation science study that evaluates multi-level facilitators and barriers to implementation of the In Our DNA SC population-wide genomic screening initiative. Methods: We established an IMPACTeam (IMPlementAtion sCience for In Our DNA SC Team) to evaluate the pilot phase using principles of implementation science. We used a parallel convergent mixed methods approach to assess the Reach, Implementation, and Effectiveness outcomes from the RE-AIM implementation science framework during the pilot phase of In Our DNA SC. Quantitative assessment included the examination of frequencies and response rates across demographic categories using chi-square tests. Qualitative data were audio-recorded and transcribed, with codes developed by the study team based on the semi-structured interview guide. Results: The pilot phase (8 November 2021, to 7 March 2022) included recruitment from ten clinics throughout South Carolina. Reach indicators included enrollment rate and representativeness. A total of 23,269 potential participants were contacted via Epic’s MyChart patient portal with 1976 (8.49%) enrolled. Black individuals were the least likely to view the program invitation (28.9%) and take study-related action. As a result, there were significantly higher enrollment rates among White (10.5%) participants than Asian (8.71%) and Black (3.46%) individuals (p < 0.0001). Common concerns limiting reach and participation included privacy and security of results and the impact participation would have on health or life insurance. Facilitators included family or personal history of a Tier 1 condition, prior involvement in genetic testing, self-interest, and altruism. Assessment of implementation (i.e., adherence to protocols/fidelity to protocols) included sample collection rate (n = 1104, 55.9%) and proportion of samples needing recollection (n = 19, 1.7%). There were no significant differences in sample collection based on demographic characteristics. Implementation facilitators included efficient collection processes and enthusiastic clinical staff. Finally, we assessed the effectiveness of the program, finding low dropout rates (n = 7, 0.35%), the identification of eight individuals with Tier 1 conditions (0.72% positive), and high rates of follow-up genetic counseling (87.5% completion). Conclusion: Overall, Asian and Black individuals were less engaged, with few taking any study-related actions. Strategies to identify barriers and promoters for the engagement of diverse populations are needed to support participation. Once enrolled, individuals had high rates of completing the study and follow-up engagement with genetic counselors. Findings from the pilot phase of In Our DNA SC offer opportunities for improvement as we expand the program and can provide guidance to organizations seeking to begin efforts to integrate population-wide genomic screening.</description><identifier>ISSN: 2075-4426</identifier><identifier>EISSN: 2075-4426</identifier><identifier>DOI: 10.3390/jpm12081228</identifier><identifier>PMID: 36013178</identifier><language>eng</language><publisher>Switzerland: MDPI AG</publisher><subject>Altruism ; Breast cancer ; Codes ; Demography ; Deoxyribonucleic acid ; DNA ; Electronic health records ; Enrollments ; Genetic counseling ; Genetic screening ; Genetic testing ; Genomics ; Hypercholesterolemia ; Interviews ; Ovarian cancer ; Participation ; Patients ; Population levels ; Precision medicine ; Response rates ; Teams ; Web portals</subject><ispartof>Journal of personalized medicine, 2022-07, Vol.12 (8), p.1228</ispartof><rights>2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2022 by the authors. 2022</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c409t-26c7f88a723c6e1618f5b43e05842757ac9631d496375f97848bd9488b6cd3e83</citedby><cites>FETCH-LOGICAL-c409t-26c7f88a723c6e1618f5b43e05842757ac9631d496375f97848bd9488b6cd3e83</cites><orcidid>0000-0003-2043-1329 ; 0000-0002-9433-6634 ; 0000-0001-8999-3587</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC9410232/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC9410232/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,27924,27925,53791,53793</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/36013178$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Allen, Caitlin G</creatorcontrib><creatorcontrib>Lenert, Leslie</creatorcontrib><creatorcontrib>Hunt, Kelly</creatorcontrib><creatorcontrib>Jackson, Amy</creatorcontrib><creatorcontrib>Levin, Elissa</creatorcontrib><creatorcontrib>Clinton, Catherine</creatorcontrib><creatorcontrib>Clark, John T</creatorcontrib><creatorcontrib>Garrison, Kelli</creatorcontrib><creatorcontrib>Gallegos, Sam</creatorcontrib><creatorcontrib>Wager, Karen</creatorcontrib><creatorcontrib>He, Wenjun</creatorcontrib><creatorcontrib>Sterba, Katherine</creatorcontrib><creatorcontrib>Ramos, Paula S</creatorcontrib><creatorcontrib>Melvin, Cathy</creatorcontrib><creatorcontrib>Ford, Marvella</creatorcontrib><creatorcontrib>Catchpole, Kenneth</creatorcontrib><creatorcontrib>McMahon, Lori</creatorcontrib><creatorcontrib>Judge, Daniel P</creatorcontrib><title>Lessons Learned from the Pilot Phase of a Population-Wide Genomic Screening Program: Building the Base to Reach a Diverse Cohort of 100,000 Participants</title><title>Journal of personalized medicine</title><addtitle>J Pers Med</addtitle><description>Background and Objectives: Genomic information is increasingly relevant for disease prevention and risk management at the individual and population levels. Screening healthy adults for Tier 1 conditions of hereditary breast and ovarian cancer, Lynch syndrome, and familial hypercholesterolemia using a population-based approach can help identify the 1−2% of the US population at increased risk of developing diseases associated with these conditions and tailor prevention strategies. Our objective is to report findings from an implementation science study that evaluates multi-level facilitators and barriers to implementation of the In Our DNA SC population-wide genomic screening initiative. Methods: We established an IMPACTeam (IMPlementAtion sCience for In Our DNA SC Team) to evaluate the pilot phase using principles of implementation science. We used a parallel convergent mixed methods approach to assess the Reach, Implementation, and Effectiveness outcomes from the RE-AIM implementation science framework during the pilot phase of In Our DNA SC. Quantitative assessment included the examination of frequencies and response rates across demographic categories using chi-square tests. Qualitative data were audio-recorded and transcribed, with codes developed by the study team based on the semi-structured interview guide. Results: The pilot phase (8 November 2021, to 7 March 2022) included recruitment from ten clinics throughout South Carolina. Reach indicators included enrollment rate and representativeness. A total of 23,269 potential participants were contacted via Epic’s MyChart patient portal with 1976 (8.49%) enrolled. Black individuals were the least likely to view the program invitation (28.9%) and take study-related action. As a result, there were significantly higher enrollment rates among White (10.5%) participants than Asian (8.71%) and Black (3.46%) individuals (p < 0.0001). Common concerns limiting reach and participation included privacy and security of results and the impact participation would have on health or life insurance. Facilitators included family or personal history of a Tier 1 condition, prior involvement in genetic testing, self-interest, and altruism. Assessment of implementation (i.e., adherence to protocols/fidelity to protocols) included sample collection rate (n = 1104, 55.9%) and proportion of samples needing recollection (n = 19, 1.7%). There were no significant differences in sample collection based on demographic characteristics. Implementation facilitators included efficient collection processes and enthusiastic clinical staff. Finally, we assessed the effectiveness of the program, finding low dropout rates (n = 7, 0.35%), the identification of eight individuals with Tier 1 conditions (0.72% positive), and high rates of follow-up genetic counseling (87.5% completion). Conclusion: Overall, Asian and Black individuals were less engaged, with few taking any study-related actions. Strategies to identify barriers and promoters for the engagement of diverse populations are needed to support participation. Once enrolled, individuals had high rates of completing the study and follow-up engagement with genetic counselors. Findings from the pilot phase of In Our DNA SC offer opportunities for improvement as we expand the program and can provide guidance to organizations seeking to begin efforts to integrate population-wide genomic screening.</description><subject>Altruism</subject><subject>Breast cancer</subject><subject>Codes</subject><subject>Demography</subject><subject>Deoxyribonucleic acid</subject><subject>DNA</subject><subject>Electronic health records</subject><subject>Enrollments</subject><subject>Genetic counseling</subject><subject>Genetic screening</subject><subject>Genetic testing</subject><subject>Genomics</subject><subject>Hypercholesterolemia</subject><subject>Interviews</subject><subject>Ovarian cancer</subject><subject>Participation</subject><subject>Patients</subject><subject>Population levels</subject><subject>Precision medicine</subject><subject>Response rates</subject><subject>Teams</subject><subject>Web portals</subject><issn>2075-4426</issn><issn>2075-4426</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNpdkU2L1TAUhosozjDOyr0E3AhazVeT1IXgXMdRuGDxA5clNz29zaVNapIO-E_8uZMy43A1iyScPDy84S2KpwS_ZqzGbw7zRChWhFL1oDilWFYl51Q8PLqfFOcxHnBeqqJU4MfFCROYMCLVafFnCzF6F9EWdHDQoT74CaUBUGNHn1Az6AjI90ijxs_LqJP1rvxpO0BX4PxkDfpmAoCzbo-a4PdBT2_RxWLHbp2soovVkDz6CtoM2fPBXkPIo40ffEirm2D8KsdDjQ7JGjtrl-KT4lGvxwjnd-dZ8ePj5ffNp3L75erz5v22NBzXqaTCyF4pLSkzAoggqq92nAGuFKeyktrUgpGO511WfS0VV7uu5krthOkYKHZWvLv1zstugs6AS0GP7RzspMPv1mvb_vvi7NDu_XVbc4Ipo1nw4k4Q_K8FYmonGw2Mo3bgl9hSiaXAMreV0ef_oQe_BJe_t1Iid8gpztTLW8oEH2OA_j4Mwe1aentUeqafHee_Z_9WzG4A-eqmTg</recordid><startdate>20220727</startdate><enddate>20220727</enddate><creator>Allen, Caitlin G</creator><creator>Lenert, Leslie</creator><creator>Hunt, Kelly</creator><creator>Jackson, Amy</creator><creator>Levin, Elissa</creator><creator>Clinton, Catherine</creator><creator>Clark, John T</creator><creator>Garrison, Kelli</creator><creator>Gallegos, Sam</creator><creator>Wager, Karen</creator><creator>He, Wenjun</creator><creator>Sterba, Katherine</creator><creator>Ramos, Paula S</creator><creator>Melvin, Cathy</creator><creator>Ford, Marvella</creator><creator>Catchpole, Kenneth</creator><creator>McMahon, Lori</creator><creator>Judge, Daniel P</creator><general>MDPI AG</general><general>MDPI</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>8FE</scope><scope>8FH</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>COVID</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>LK8</scope><scope>M7P</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0003-2043-1329</orcidid><orcidid>https://orcid.org/0000-0002-9433-6634</orcidid><orcidid>https://orcid.org/0000-0001-8999-3587</orcidid></search><sort><creationdate>20220727</creationdate><title>Lessons Learned from the Pilot Phase of a Population-Wide Genomic Screening Program: Building the Base to Reach a Diverse Cohort of 100,000 Participants</title><author>Allen, Caitlin G ; Lenert, Leslie ; Hunt, Kelly ; Jackson, Amy ; Levin, Elissa ; Clinton, Catherine ; Clark, John T ; Garrison, Kelli ; Gallegos, Sam ; Wager, Karen ; He, Wenjun ; Sterba, Katherine ; Ramos, Paula S ; Melvin, Cathy ; Ford, Marvella ; Catchpole, Kenneth ; McMahon, Lori ; Judge, Daniel P</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c409t-26c7f88a723c6e1618f5b43e05842757ac9631d496375f97848bd9488b6cd3e83</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Altruism</topic><topic>Breast cancer</topic><topic>Codes</topic><topic>Demography</topic><topic>Deoxyribonucleic acid</topic><topic>DNA</topic><topic>Electronic health records</topic><topic>Enrollments</topic><topic>Genetic counseling</topic><topic>Genetic screening</topic><topic>Genetic testing</topic><topic>Genomics</topic><topic>Hypercholesterolemia</topic><topic>Interviews</topic><topic>Ovarian cancer</topic><topic>Participation</topic><topic>Patients</topic><topic>Population levels</topic><topic>Precision medicine</topic><topic>Response rates</topic><topic>Teams</topic><topic>Web portals</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Allen, Caitlin G</creatorcontrib><creatorcontrib>Lenert, Leslie</creatorcontrib><creatorcontrib>Hunt, Kelly</creatorcontrib><creatorcontrib>Jackson, Amy</creatorcontrib><creatorcontrib>Levin, Elissa</creatorcontrib><creatorcontrib>Clinton, Catherine</creatorcontrib><creatorcontrib>Clark, John T</creatorcontrib><creatorcontrib>Garrison, Kelli</creatorcontrib><creatorcontrib>Gallegos, Sam</creatorcontrib><creatorcontrib>Wager, Karen</creatorcontrib><creatorcontrib>He, Wenjun</creatorcontrib><creatorcontrib>Sterba, Katherine</creatorcontrib><creatorcontrib>Ramos, Paula S</creatorcontrib><creatorcontrib>Melvin, Cathy</creatorcontrib><creatorcontrib>Ford, Marvella</creatorcontrib><creatorcontrib>Catchpole, Kenneth</creatorcontrib><creatorcontrib>McMahon, Lori</creatorcontrib><creatorcontrib>Judge, Daniel P</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>Coronavirus Research Database</collection><collection>ProQuest Central Korea</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Biological Science Collection</collection><collection>Biological Science Database</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Journal of personalized medicine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Allen, Caitlin G</au><au>Lenert, Leslie</au><au>Hunt, Kelly</au><au>Jackson, Amy</au><au>Levin, Elissa</au><au>Clinton, Catherine</au><au>Clark, John T</au><au>Garrison, Kelli</au><au>Gallegos, Sam</au><au>Wager, Karen</au><au>He, Wenjun</au><au>Sterba, Katherine</au><au>Ramos, Paula S</au><au>Melvin, Cathy</au><au>Ford, Marvella</au><au>Catchpole, Kenneth</au><au>McMahon, Lori</au><au>Judge, Daniel P</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Lessons Learned from the Pilot Phase of a Population-Wide Genomic Screening Program: Building the Base to Reach a Diverse Cohort of 100,000 Participants</atitle><jtitle>Journal of personalized medicine</jtitle><addtitle>J Pers Med</addtitle><date>2022-07-27</date><risdate>2022</risdate><volume>12</volume><issue>8</issue><spage>1228</spage><pages>1228-</pages><issn>2075-4426</issn><eissn>2075-4426</eissn><abstract>Background and Objectives: Genomic information is increasingly relevant for disease prevention and risk management at the individual and population levels. Screening healthy adults for Tier 1 conditions of hereditary breast and ovarian cancer, Lynch syndrome, and familial hypercholesterolemia using a population-based approach can help identify the 1−2% of the US population at increased risk of developing diseases associated with these conditions and tailor prevention strategies. Our objective is to report findings from an implementation science study that evaluates multi-level facilitators and barriers to implementation of the In Our DNA SC population-wide genomic screening initiative. Methods: We established an IMPACTeam (IMPlementAtion sCience for In Our DNA SC Team) to evaluate the pilot phase using principles of implementation science. We used a parallel convergent mixed methods approach to assess the Reach, Implementation, and Effectiveness outcomes from the RE-AIM implementation science framework during the pilot phase of In Our DNA SC. Quantitative assessment included the examination of frequencies and response rates across demographic categories using chi-square tests. Qualitative data were audio-recorded and transcribed, with codes developed by the study team based on the semi-structured interview guide. Results: The pilot phase (8 November 2021, to 7 March 2022) included recruitment from ten clinics throughout South Carolina. Reach indicators included enrollment rate and representativeness. A total of 23,269 potential participants were contacted via Epic’s MyChart patient portal with 1976 (8.49%) enrolled. Black individuals were the least likely to view the program invitation (28.9%) and take study-related action. As a result, there were significantly higher enrollment rates among White (10.5%) participants than Asian (8.71%) and Black (3.46%) individuals (p < 0.0001). Common concerns limiting reach and participation included privacy and security of results and the impact participation would have on health or life insurance. Facilitators included family or personal history of a Tier 1 condition, prior involvement in genetic testing, self-interest, and altruism. Assessment of implementation (i.e., adherence to protocols/fidelity to protocols) included sample collection rate (n = 1104, 55.9%) and proportion of samples needing recollection (n = 19, 1.7%). There were no significant differences in sample collection based on demographic characteristics. Implementation facilitators included efficient collection processes and enthusiastic clinical staff. Finally, we assessed the effectiveness of the program, finding low dropout rates (n = 7, 0.35%), the identification of eight individuals with Tier 1 conditions (0.72% positive), and high rates of follow-up genetic counseling (87.5% completion). Conclusion: Overall, Asian and Black individuals were less engaged, with few taking any study-related actions. Strategies to identify barriers and promoters for the engagement of diverse populations are needed to support participation. Once enrolled, individuals had high rates of completing the study and follow-up engagement with genetic counselors. Findings from the pilot phase of In Our DNA SC offer opportunities for improvement as we expand the program and can provide guidance to organizations seeking to begin efforts to integrate population-wide genomic screening.</abstract><cop>Switzerland</cop><pub>MDPI AG</pub><pmid>36013178</pmid><doi>10.3390/jpm12081228</doi><orcidid>https://orcid.org/0000-0003-2043-1329</orcidid><orcidid>https://orcid.org/0000-0002-9433-6634</orcidid><orcidid>https://orcid.org/0000-0001-8999-3587</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Altruism Breast cancer Codes Demography Deoxyribonucleic acid DNA Electronic health records Enrollments Genetic counseling Genetic screening Genetic testing Genomics Hypercholesterolemia Interviews Ovarian cancer Participation Patients Population levels Precision medicine Response rates Teams Web portals |
title | Lessons Learned from the Pilot Phase of a Population-Wide Genomic Screening Program: Building the Base to Reach a Diverse Cohort of 100,000 Participants |
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