Setting a Research Agenda for the Use of Artificial Intelligence & Machine Learning in Primary Care

Setting a Research Agenda for the Use of Artificial Intelligence & Machine Learning in Primary Care

Virtual Summit: March 18-19, 2021

FOR QUESTIONS CONTACT: Andrew Bazemore, & Mikel Severson at 1-202-600-9447

Event Details

Andrew Bazemore, MD, MPH

Andrew Bazemore, MD, MPH has served as the Senior Vice President of Research and Policy for the American Board of Family Medicine (ABFM), and co-director of the Center for Professionalism & Value in Health Care in Washington, DC., since 2019. Prior to that, he was the Director of the Robert Graham Center for Policy Studies, where he directed policy research with special interests in access to primary care, underserved populations, health workforce and training, and spatial analysis. He has authored over 200 peer reviewed publications. He also led the Graham Center’s emphasis on developing geospatial data tools intended to empower primary care providers, leaders, and policymakers and inform policy, such as HealthLandscape and the UDS Mapper, which currently helps to guides funding for all the nation’s Federally Qualified Health Centers. Dr. Bazemore sees patients and teaches at the VCU-Fairfax Medicine residency program, is an elected member of the National Academies of Medicine and serves on the faculties of the Departments of Family Medicine at Georgetown University, Virginia Commonwealth University, and the University of Toronto.

Ethan M. Berke, MD, MPH photo

Ethan M. Berke, MD, MPH is the Chief Medical Officer, Population Health Solutions, and Vice President of Clinical Innovation at Optum. In this role, Ethan serves as the clinical lead for provider and health-system focused solutions that improve the care of patients in the context of their community, and help the health system provide the highest quality care, at the lowest cost, with an exemplary patient and provider experience, no matter what payment system is utilized. He previously served as Medical Director of Clinical Design and Innovation for Dartmouth-Hitchcock Health System (D-HHS), an academic health system in New Hampshire. At D-HHS he was also Chief Medical Officer of ImagineCare, a 24/7 nurse-led, coordinated care model that leverages remote medical sensing and machine learning analytics to improve health and health care quality while reducing costs and empowering patients. Prior to leading these innovation groups. Dr. Berke was engaged in many operational initiatives, and formed and led the primary care service line at D-HHS. In his primary care leadership role, he focused on innovation in the provider practice, specifically developing and implementing value based compensation models for primary care physicians, an imbedded behavioral health clinician model, and multi-disciplinary team-based improvement projects to improve the patient experience.

Arlene S. Bierman, M.D., M.S. photo

Arlene S. Bierman, M.D., M.S., leads the work of CEPI, which consists of five divisions: the Evidence-Based Practice Center Program; the U.S. Preventive Services Task Force Program; the Division of Decision Science and Patient Engagement; the Division of Health Information Technology; and the Division of Practice Improvement, as well as the National Center for Excellence in Primary Care Research. Dr. Bierman is a general internist, geriatrician, and health services researcher, whose work has focused on improving access, quality, and outcomes of health care for older adults with chronic illness in disadvantaged populations. Dr. Bierman has also developed strategies for using performance measurement as a tool for knowledge translation and has conducted research to increase policymakers’ use of evidence.

Asaf Bitton photo

Asaf Bitton, MD, MPH, is the executive director of Ariadne Labs, a health systems innovation center at Brigham and Women’s Hospital and the Harvard T.H. Chan School of Public Health. He is a national and global expert on primary care policy, financing, and delivery.

He previously served as director of Ariadne Labs’ Primary Health Care Program, leading primary care measurement and improvement work in over a dozen countries along with previous work directing regional medical home learning collaboratives in Massachusetts. He is a core founder and leader of the Primary Health Care Performance Initiative, a partnership that includes the World Bank, the World Health Organization, and Bill & Melinda Gates Foundation dedicated to transforming the global state of primary health care. Currently, this partnership is scaling the launch and use of country-level dashboards on primary care performance across over 20 countries, with a goal of 60 countries by 2022. He is a senior advisor for primary care policy at the Center for Medicare and Medicaid Innovation. In this role since 2012, he has helped design and test three major comprehensive primary care payment and delivery initiatives, now active in 18 states, with over 70 payers and 3,000 practices that serve more than three million Medicare beneficiaries and 15 million total patients. These initiatives represent the largest tests of combined primary care payment and clinical practice transformation work in the United States.

Dr. Bitton practices primary care at Brigham and Women’s South Huntington clinic, a team-based primary care practice in Boston that he helped found in 2011.

Isabella Chu photo

Isabella Chu has been with the Stanford School of Medicine since 2001. She received her MPH in Public Health Nutrition from UC Berkeley in 2011 and joined The Stanford Center for Population Health Sciences (PHS) in 2016. Her research interests focus on social and environmental determinants of health, particularly the built environment and housing policy which promotes equitable access to the economy, education, and other opportunities. She is the Associate Director of the Data Core at PHS. The PHS Data Core specializes in hosting large, rich, high risk data which are used by hundreds of researchers to answer questions in precision and population health. Her primary responsibilities include overseeing governance and regulatory matters, data security, privacy and ethics and collaboration with the team of research scientists and engineers who have built the PHS Data Core platform. This platform and model have been replicated in several universities throughout the United States.

Jacqueline Kueper photo

Jacqueline (Jaky) Kueper is the first combined PhD candidate in Epidemiology and Computer Science at Western University and a graduate of the Transdisciplinary Understanding and Training on Research in Primary Health Care (TUTOR-PHC) program. Her research integrates these fields to 1) identify areas or challenges in primary health care where machine learning may be useful, and to 2) develop or adapt machine learning methods to support identified challenges and promote health equity. For example, Jaky’s doctoral research includes developing novel machine learning methods for decision support around multimorbidity care with the Alliance for Healthier Communities in Ontario, Canada. A pilot tool is currently underway and next steps include iterative machine learning model updating with primary care providers and then careful implementation tests and evaluation in clinical settings.

Winston Liaw photo

Winston Liaw is a family physician, health services researcher, and the Chair of Health Systems and Population Health Sciences at the University of Houston, College of Medicine. His research focuses on the primary care workforce, access, telemedicine, practice transformation, health informatics, and the integration of public health and primary care. In particular, his work focuses on assessing and addressing unmet social needs in clinical settings and integrating geospatial data and social determinants of health into prediction tools. Prior to joining the University of Houston, he was a researcher at the University of Texas Health Science Center at Houston and was the Medical Director at the Robert Graham Center, a primary care policy research institute affiliated with the American Academy of Family Physicians. He also served as residency faculty at the Virginia Commonwealth University, Fairfax Family Medicine Residency Program. Dr. Liaw received a BA degree from Rice University, an MD from Baylor College of Medicine, an MPH from the Harvard School of Public Health, family medicine residency training from Virginia Commonwealth University, and health policy fellowship training from the Robert Graham Center.

Dr Lin photo

Dr. Lin is the Executive Director of the Stanford Healthcare AI Applied Research Team (HEA3RT). He is an expert clinician, researcher, educator, and health system leader in the specialty of family medicine. Dr. Lin earned his MD from Stanford University School of Medicine and completed his medical training at Stanford’s family medicine residency program at O’Connor Hospital. He has received numerous national awards and is recognized among the top family physicians in the United States. Dr. Lin is the Service Chief for Family Medicine at Stanford Health Care. He cares for people of all ages, often for members of the same family. Dr. Lin has a particular interest in preventive cardiology, diabetes, viral hepatitis, and mental health. He is proficient in a wide range of primary care procedures – including over 40 different skin, musculoskeletal, and women’s health procedures that are performed in the office. Dr. Lin is the author of over 250 scholarly works and conference presentations. He is the Vice Chief for Technology Innovation in the Division of Primary Care and Population Health at Stanford. Dr. Lin’s current focus is on artificial intelligence in healthcare. He is a consultant and mentor to technology companies in the United States, Canada, Europe, and Asia.

John Maier photo

John Maier is an Assistant Professor and the Director of Research and Development in the Department of Family Medicine at the University of Pittsburgh. John is a Co-Director of the Innovation Core at the Clinical and Translational Science Institute where he is also the director of the Pitt Innovation Challenge. He completed his PhD in Physics and MD at the University of Illinois at Urbana-Champaign (UIUC) where his research focused on light-tissue interaction and its application to in-vivo spectroscopy. After completing the Medical Scholars Program at UIUC, he went on to the UPMC Shadyside Family Medicine Residency from 1999 to 2002. From 2002 to 2011 he worked at ChemImage Corporation in Pittsburgh as the leader of biomedical research and a member of the management team. In 2011 he returned to the University of Pittsburgh to join the faculty in the Department of Family Medicine where he serves on the executive committee and provides leadership and support to projects that span the range from comparative effectiveness research to health care system delivery innovation in community based settings. John enjoys teaching in the University of Pittsburgh School of Medicine where he is co-director of two courses focused on research project development and an area of concentration for students interested in bioengineering, bioinformatics, innovation and translation. Dr. Maier is a co-inventor on over 50 US patents and co-author on 16 peer reviewed publications and numerous proceedings, abstracts and presentations. “My position in the department of Family Medicine allows me to leverage my technical background in imaging and measurement science; my broad based primary care clinical background; and my experience in the industrial setting as I provide integration support and leadership to the complex work of translating academic and technical advances into clinical medicine.”

Miguel Marino photo

Miguel Marino, PhD is an Associate Professor of Biostatistics in the Department of Family Medicine at Oregon Health & Science University, and with the Biostatistics group in the OHSU-PSU School of Public Health. He received his B.S. in Mathematics from UCLA and his Ph.D. in Biostatistics from Harvard University. Dr. Marino maintains a broad statistical research program that focuses on the intersection of primary care and public health studies including utilizing novel statistical methodology to answer critical community and primary care research questions in health policy, health disparities and vulnerable populations, social determinants of health, health insurance monitoring, among others. Since 2013, Dr. Marino has been the Statistical Editor for the Annals of Family Medicine and he currently serves as the Publications Officer for the Health Policy Statistics section of the American Statistical Association. His body of research earned recognition in 2020 when he was selected by the National Academy of Medicine as an Emerging Leader in Health and Medicine Scholar.

Lars Peterson photo

Lars Peterson, MD, PhD is a family physician and health services researcher and Vice President of Research of the American Board of Family Medicine (ABFM) and an Associate Professor in the Department of Family and Community Medicine at the University of Kentucky. He received his medical and graduate degrees from Case Western Reserve University. His research interests include investigating associations between area level measures of health care and socioeconomics with both health and access to health care, rural health, primary care, and comprehensiveness of primary care. He has authored over 120 peer reviewed publications and made over 100 conference presentations. He is leading team research efforts at the ABFM to understand what family physicians do in practice and how the quality of care they provide can be improved. In particular, elucidating the ways in which Continuing Certification activities may be associated with quality of care.

Robert Phillips Photo

Robert Phillips, MD, MSPH is a graduate of the Missouri University of Science and Technology and the University of Florida College of Medicine where he graduated with honors for special distinction. He completed training in family medicine at the University of Missouri in 1998, followed by a two-year fellowship in health services research and public health. After fellowship, Dr. Phillips became assistant director of the Robert Graham Center, Washington DC, and from 2004-2012, he served as its Director. In 2012, he moved to the American Board of Family Medicine (ABFM) as Vice President for Research and Policy where he led the launch of a national clinical registry. Dr. Phillips currently practices part-time in a community-based residency program in Fairfax, VA, and is Professor of Family Medicine at Georgetown University and Virginia Commonwealth University. He served on the American Medical Association’s Council on Medical Education and as president of the National Residency Matching Program. From 2006-10, he was vice chair of the US Council on Graduate Medical Education, and from 2015-2019 he served on the National Committee for Vital and Health Statistics as co-chair of Population Health. Dr. Phillips currently serves as co-chair of the National Academy of Science, Engineering, and Medicine consensus study on Implementing High-Quality Primary Care. He served as a Fulbright Specialist to the Netherlands in 2012 and New Zealand in 2016. A nationally recognized leader on primary care policy and health care reform, Dr. Phillips was elected to the National Academy of Medicine in 2010 and currently chairs the NAM Membership Committee. In 2018, Dr. Phillips was named the founding Executive Director of the Center for Professionalism and Value in Health Care.

David Rehkopf photo

David Rehkopf is an Assistant Professor in the Department of Medicine at the Stanford University School of Medicine. His work focuses on the way in which social and economic factors impact health and mortality across the lifespan, with particular attention to the impact of work and earnings on cardiovascular biomarkers and obesity. He completed his dissertation at the Harvard School of Public Health in March of 2006 in the Department of Society, Human Development and Health. His dissertation, entitled “The non-linear impacts of income on mortality, biomarkers and growth,” documents the ways in which higher income has different returns to health and human development depending on a household’s position in the income distribution. He is currently the co-director of the Stanford Center for Population Health Sciences. In this position he is committed to making high value data resources available to researchers across disciplines in order to better enable them to answer their most pressing clinical and population health questions.

Sherri Rose photo

Sherri Rose, Ph.D. is an Associate Professor at Stanford University in the Center for Health Policy and Center for Primary Care and Outcomes Research. She is also Co-Director of the Health Policy Data Science Lab. Her research is centered on developing and integrating innovative statistical machine learning approaches to improve human health. Within health policy, Dr. Rose works on risk adjustment, comparative effectiveness research, and health program evaluation. She has published interdisciplinary projects across varied outlets, including Biometrics, Journal of the American Statistical Association, Journal of Health Economics, Health Affairs, and New England Journal of Medicine. Dr. Rose is the Co-Editor of Biostatistics and Chair of the American Statistical Association’s Biometrics Section. Her honors include an NIH Director’s New Innovator Award, the ISPOR Bernie J. O’Brien New Investigator Award, and Mid-Career Awards from the American Statistical Association’s Health Policy Statistics Section and Penn-Rutgers Center for Causal Inference. Dr. Rose was also named a Fellow of the American Statistical Association in 2020. Her research has been featured in The New York Times, USA Today, and The Boston Globe. In 2011, Dr. Rose coauthored the first book on machine learning for causal inference, with a sequel text released in 2018.

Mark Sendak photo

Mark Sendak is the Population Health & Data Science Lead at DIHI and helps lead interdisciplinary teams of data scientists, clinicians, and machine learning experts to build technologies that solve real clinical problems. Together with the DIHI team, he has integrated dozens of data-driven technologies into clinical operations at Duke Health. He leads the DIHI Clinical Research & Innovation scholarship, which equips medical students with the business and data science skills required to lead health care transformation efforts. His work has been published in technical venues and clinical venues, such as Machine Learning for Healthcare, Nature Medicine, Plos Medicine, and JAMA Open. He is an organizer of the annual Machine Learning for Healthcare conference and loves partnering across boundaries to tackle hard problems. He completed his Bachelor’s of Science in Mathematics at UCLA and an MD and MPP at Duke University.

Christina Silcox photo

Christina Silcox is the Digital Health Policy Fellow at the Duke-Margolis Center for Health Policy, working on policy solutions to advance innovation in health and health care and improve regulation, reimbursement, and long-term evaluation of medical products, with a focus on digital health. Dr. Silcox’s portfolio includes multiple areas in digital health policy and real-world evidence, with a focus on medical devices. Currently, she is concentrating on challenges to regulating and adopting of artificial intelligence-enabled software as a medical device, using mHealth to collect real-world data, and characterizing real-world data quality and relevancy. Her projects have included the use of patient-generated health data in medical device evaluations, the exploration of value-based payments for medical devices, and the convening the National Evaluation System for health Technology (NEST) Planning Board. Before she joined Duke-Margolis, Dr. Silcox was a senior fellow at the National Center for Health Research, focused on federal regulation of and policies for medical products. She earned a M.S. from the Massachusetts Institute of Technology (MIT) in Electrical Engineering and a Ph.D. in Medical Engineering and Medical Physics from the Harvard-MIT Division of Health Sciences and Technology (HST).

Zhou Yang photo

Zhou Yang, Ph.D., MPH, is the senior health economist of American Board of Family Medicine. Born and raised in Beijing China, Dr. Yang obtained her Bachelor of Medicine in China, Master of Public Health from UCLA, and Ph.D. of health economics from University of North Carolina at Chapel Hill. Dr. Yang is specialized in health care financing policy, and had a diversified career history in academia, domestic and international health policy consulting, and industry. She used to teach at University of Florida and Emory University, consulted for Congress, the World Bank Group, and Humana. Dr. Yang is running the AI/ML research portfolio of the American Board of Family Medicine.

Mahnoor Ahmed, MEng is an Associate Program Officer at the National Academy of Medicine.

Nakul Aggarwal, is an MD-PhD student at the University of Wisconsin-Madison. He is currently completing his thesis research in the lab of Dr. Ned Kalin, Chair of Psychiatry. His work leverages large, multimodal, and longitudinal neuroimaging datasets in humans and non-human primates to examine how alterations in the development of white matter microstructure relate to trajectories of childhood anxiety. In addition to employing machine learning techniques in his research, he is interested in the clinical applications of AI, specifically in the domain of child and adolescent psychiatry, and has served as a scientific consultant on AI-related projects with the National Academy of Medicine.

Sanjay Basu, MD, PhD, is a primary care physician and epidemiologist. He is the Director of Research at the Harvard Medical School Center for Primary Care, as well as Vice President of Research and Population Health at Collective Health. Dr. Basu received his education from the Massachusetts Institute of Technology (MIT), Oxford University (as a Rhodes Scholar), and Yale before completing his residency in internal medicine at the University of California in San Francisco. He has previously worked with organizations to create and evaluate a supply chain to deliver high-cost medicines to low-income patients, mitigate the spread of drug-resistant infections in hospitals, build a rural hospital and community healthcare worker network, and address food insecurity through a community-based food assistance program. He had published over 300 peer-reviewed journal articles, been named to the “Top 100 Global Thinkers” List by Foreign Policy Magazine, awarded the NIH Director’s New Innovator Award, and received the Presidential Early Career Award for Scientists and Engineers. His work has focused on preventing and treating chronic diseases, reducing the health effects of financial shocks and other adverse social determinants of health, improving access to essential healthcare services, and improving primary care infrastructure and quality. He co-founded Possible Health and serves as a Fellow at Imperial College London and an Associate Professor at University of Toronto. He currently practices medicine at San Francisco’s Integrated Care Center, a primary care, behavioral health, substance abuse, and oral health center for unhoused people.

Aaron Baum, PhD is an Assistant Professor at Mount Sinai. Aaron’s research uses methods from empirical economics and statistics to evaluate and personalize the targeting of health services and policies. Aaron has a PhD from Columbia University, where he studied health and development economics, and a BS in mathematics from the University of Chicago. He has a primary appointment in the Department of Health System Design and Global Health at Mount Sinai and a secondary appointment in the Department of Genetics and Genomic Sciences. Aaron is also affiliated with the Veterans Health Administration (New York Harbor), the Department of Medicine at Stanford University, and the Harvard Center for Primary Care.

Seth J. Chandler is a Law Foundation Professor of Law at the UH Law Center who specializes in insurance law and the application of mathematics and computer science to law. Professor Chandler won a prestigious university-wide teaching excellence award in 1995, was a first year winner of the Innovator Award from Wolfram Research, received the President’s Medal from Loyola University for extraordinary service in the aftermath of Hurricane Katrina, and has been called on twice to testify before Congress on the Affordable Care Act. Professor Chandler has a broad Internet presence; he is the author of over 100 interactive Demonstrations, 21 Resource Functions and several Data Repositories on the Wolfram Research website. He founded two blogs, acadeathspiral.org, which addressed the ACA, and catrisk.net, which addressed catastrophic insurance in Texas. Professor Chandler’s blog entries have over 400,000 views. He practiced with Munger, Tolles & Olson in Los Angeles and Williams & Connolly in Washington, D.C. before beginning his academic career in 1990 at the UH Law Center. Professor Chandler teaches contracts, health law, analytic methods and constitutional law.

Jessica Dobbins, DrPH, MA, is the Associate Director at Humana. Jessica’s academic training, research, and work experience has focused on the intersection of public health and primary care. Her work adapts population health models, health behavior theories, and research methods to industry needs. Jessica has experience leading interdisciplinary teams of leaders and facilitating multi-sector partnerships to support population health.

Nate Favini, MD, MS serves as Medical Lead at Forward, the innovative primary care practice that empowers top-rated doctors with advanced technology, reaching more people with better primary care. He leads Forward’s teams of health care providers, oversees clinical operations and supervises clinical product development for the organization. He recently led Forward’s efforts to rapidly scale up COVID-19 assessments and nationwide testing and helped to launch “Forward at Home,” a new offering that allows Forward members to receive longitudinal primary and preventive care without coming to the doctor’s office. Prior to Forward, he was Director of Primary Care at CareMore Health System. He earned his medical degree from Harvard Medical School, completed his residency in Primary Care and Social Internal Medicine at Montefiore Medical Center, and was a Robert Wood Johnson Foundation Clinical Scholar at UCLA. He holds a masters degree in health policy and management from UCLA. Prior to entering medicine he was a Peace Corps volunteer in Mozambique. He lives with his wife and two kids in the Bay Area.

Jonathon Gonzalez-Smith, MS is a member of Duke-Margolis’ Global team, which collaborates closely with Innovation in Healthcare and Duke Global Health Innovation Center, researching international models of accountable care, health financing, global health innovation, and payment and delivery reform. Primary and secondary research and statistical analysis are the focus of much of his work. Jonathan holds a Master’s in Public Affairs from the University of Texas and BA in Philosophy and International Relations from Northwestern University.

John David Heintzman, M.D.is an Associate Professor of Family Medicine and the Director of Postdoctoral Research Fellowship in Family Medicine at Oregon Health & Science University. Dr. John David Heintzman is a family physician who has a passion for delivering quality primary care to all people. Out of this passion came a realization that many individuals and groups to not benefit from equal access to lifelong, high-quality primary care. That spurred Dr. Heintzman to get public health and research training to better study access to primary care by Latino populations, especially those using community health centers. Dr. Heintzman has collaborated with others at OHSU Family Medicine and the OCHIN Inc. nonprofit to use electronic health records to better understand inequalities in care. This includes studying differences in asthma treatment delivered in primary care between non-Hispanic white children and Latino children. It also includes evaluating alternative ways to pay for primary care in community health centers. Dr. Heintzman is part of a team committed to using new methods to better understand nuanced health disparities in racial and ethnic minorities, and to give providers and policy makers better data to improve the health of all of us.

Ioannis A. Kakadiaris, Ph.D. is a Hugh Roy and Lillie Cranz Cullen University Professor of Computer Science, Electrical & Computer Engineering, and Biomedical Engineering at the University of Houston, Houston, TX, USA. He joined UH in August 1997 after a postdoctoral fellowship at the University of Pennsylvania. He earned his B.Sc. in Physics at the University of Athens in Greece, his M.Sc. in Computer Science from Northeastern University and his Ph.D. at the University of Pennsylvania. He is also the founder and director of the Computational Biomedicine Lab. His research interests include biometrics, computer vision, and pattern recognition, biomedical image analysis and cardiovascular informatics.

Bruce E. Landon, MD, MBA, MSc, is a professor of health care policy at Harvard Medical School and a professor of medicine at the Beth Israel Deaconess Medical Center. He practices internal medicine at BIDMC. Dr. Landon’s primary research interest has been assessing the impact of different characteristics of physicians and health care organizations, ranging from health plans to physician group practices on physician behavior and the provision of health care services. His work in this area has included the development of a theoretical model to explain how health care organizations affect the quality of care, and he is now involved in several projects that will help describe and quantify the impact of a variety of organizational characteristics and strategies, including quality improvement strategies and financial incentives, on the provision of care. Dr. Landon currently serves as the principal investigator of an RO1 from the National Institutes of Aging studying the influence of informal physician social networks on local practice patterns and the diffusion of new technologies. Dr. Landon also is a project leader on an NIA-funded program-project grant that seeks to examine quality of care and utilization patterns in the Medicare Advantage program. Dr. Landon has also been particularly interested in studying organizational approaches to improving the quality of care. He completed a national evaluation of the HRSA Health Disparities Collaboratives, the primary quality improvement activity for our nation’s Community Health Centers, that was funded by the Agency for Health Care Research and Quality, the Health Resources Services Administration (HRSA), and the Commonwealth Fund. In this nationally representative study, he found that the collaboratives improved the processes of care for chronic medical conditions, but not the outcomes. Dr. Landon has also been interested in larger organizational entities, such as managed care health plans and has studied quality of care and patient experiences in Medicare’s managed care program. He also has been very interested in the area of payment reform and has been involved in studying both global payment strategies, such as Medicare’s Accountable Care Organization programs and payment systems for primary care. Finally, Dr. Landon has also developed a research program with vascular surgeons to study the comparative effectiveness of treatment strategies for vascular disease.

Cristina Mannie has a degree in Pharmacy, a master’s degree in Public Health and graduate certificates in Global Health, Health Finance and Management and Quantitative Methods in Clinical Public Health Research (in biostatistics and epidemiology).Together with Stefan Strydom, Cristina is the co-founder of Mast Analytics, a healthcare-focused analytics start-up aimed at bringing together the fields of health and data science to improve population health and health systems through the development of analytics solutions that support decision-making in healthcare. Cristina has 20 years’ experience in the public and private healthcare sectors. Early career includes serving as a specialised paediatric hospital pharmacist at a state paediatric academic tertiary hospital; principal pharmacist at a multidisciplinary primary healthcare facility; and 13 years in the managed healthcare environment during which time she focused primarily on population health analytics, the identification of at-risk populations for clinical care management programmes, intervention design and outcomes measurement.

George Macones, MD is the Chair of the Department of Women’s Health and a Professor of obstetrics and gynecology at Dell Medical School at the University of Texas at Austin, after serving for 14 years as the Chair of the Department of Obstetrics and Gynecology at Washington University in St. Louis. Prior to this, he spent 10 years on the faculty at the University of Pennsylvania, in a number of different roles, including Director of Clinical Research for the Center for Research on Reproduction and Women’s Health and Director of Obstetrics in the Department of Obstetrics and Gynecology. Dr. Macones is a nationally recognized expert in obstetrics and has held leadership positions in the American College of Obstetricians and Gynecologists and the Society of Maternal-Fetal Medicine. He has over 400 publications, and his research has been funded by the National Institute of Child Health and Human Development (NICHD), the National Heart, Lung, and Blood Institute (NHLBI), the National Cancer Institute (NCI), and the March of Dimes. He also currently serves on the Board of Directors for the American Board of Obstetrics and Gynecology and is Deputy Editor for Obstetrics for the American Journal of Obstetrics and Gynecology. He is an elected member of the American Society of Clinical Investigation and the National Academy of Medicine.

David Meyers, MD is a board-certified family physician, began serving as AHRQ’s Acting Director on January 12, 2021. He leads the Agency’s mission of producing evidence to make health care safer, higher quality, more accessible, equitable, and affordable, and working within the U.S. Department of Health and Human Services and with other Federal, State, and local partners to make sure that the evidence is understood and used. Before joining AHRQ in 2004, he practiced family medicine, including maternity care, in a community health center in southeast Washington, D.C., and directed the Georgetown University Department of Family Medicine’s practice-based research network, CAPRICORN. He is a graduate of the University of Pennsylvania School of Medicine and completed his family medicine residency at Providence Hospital/Georgetown University. After residency, he completed fellowship training in primary care health policy and research in the Department of Family Medicine at Georgetown University. In 2019, he was elected a member of the National Academy of Medicine.

Warren Newton, MD, MPH, serves as President and Chief Executive Officer for the American Board of Family Medicine (ABFM). As President and CEO of the ABFM, he also oversees the ABFM Foundation and Pisacano Leadership Foundation. Dr. Newton previously served as Executive Director of the North Carolina Area Health Education Center (NC AHEC), a national leader in practice redesign, continuing professional development, health careers programming, and innovation in graduate medical education, and Vice Dean of Education at the University of North Carolina (UNC) School of Medicine. From 1999–2016 he served as the William B. Aycock Professor and Chair of Family Medicine at UNC.Dr. Newton has served as a personal physician for 34 years, working in a variety of settings, including the UNC Family Medicine Center, the Moncure Community Health Center, and the Randolph County Health Department. In the 1990s he founded the first hospitalist program at UNC Hospitals and helped reorganize family medicine obstetrics into a maternal child service. For the last 15 years he led practice transformation initiatives at the practice, regional and statewide levels; North Carolina AHEC now provides ongoing support for health information technology, Patient Centered Medical Home, and quality improvement for over 1,200 primary care practices.

Stephen Petterson, PhD, joined the Robert Graham Center in 2005. He is currently the Research Director, both overseeing and contributing to the Center’s analytical activities. Previously, as a sociologist and social statistician, he was on faculty at the University of Virginia and a researcher at the Southeastern Rural Mental Health Research Center. Stephen has taught cours-es in graduate and undergraduate statistics, welfare policy, problems of urban life and sociology of work. He earned a Ph.D. in sociology from the University of Wisconsin, and an undergraduate degree in sociology and anthropology from Haverford College.

Russell S. Phillips is Director of the Center for Primary Care and the William Applebaum Professor of Medicine and Professor of Global Health and Social Medicine at Harvard Medical School. He is a general internist at Beth Israel Deaconess Medical Center, where he provides primary care in Healthcare Associates, a large teaching practice. He has been a leader in innovation in practice and payment in primary care, implementing new care models for patients with chronic illness and, using micro-simulation, testing the impact of global payment on value. He has served on a Massachusetts Health Quality Partners Advisory Group on the future of primary care. In Massachusetts, he is advocating for access to primary care, global payment for primary care, and financial support for small, independent practices threatened by the financial strain imposed by COVID-19. He is a leader in oral health integration into primary care and served on a Patient-Centered Collaborative Advisory Committee on Oral Health Integration and is Co-Principal Investigator on a related HRSA-funded Academic Unit. Dr. Phillips has expertise in the evaluation of innovations in care, systems improvement, patient safety, and quality of care and is a member of the Center’s care integration study team. In his prior work at BIDMC, which included serving as Chief of the Division of General Medicine and Primary Care for a decade, he led a task force to improve transitions in care, a working group to develop new sustainable practice models for primary care, and a task force to develop strategies for care management for high-risk patients. At the state level, he served on the Massachusetts Coordinating Council on the Patient-Centered Medical Home. He has championed palliative care services in primary care, wellness programs, and innovations to improve the quality of life for patients with chronic illness. A graduate of Massachusetts Institute of Technology and Stanford University School of Medicine, he has held leadership roles in the Society of General Internal Medicine, serving as Chairperson of the Research Committee, and as President of the Association of Chiefs and Leaders in General Internal Medicine. With more than 240 publications and an H-index over 100, his research has spanned disparities in care, screening for infection in office practice, patient safety, end of life care, and interventions to improve care for patients with chronic disease. He is the recipient of the two prestigious awards for mentorship at HMS; the Barger Award and the William Silen Lifetime Achievement in Mentoring Award. He led the Harvard General Medicine Fellowship Program for nearly 15 years, and the Harvard Research Fellowship Program in Integrative Medical Therapies for 12 years. He held a Mid-Career Mentorship Award (K24) from the NIH to support his mentoring activities. He has mentored more than 50 trainees, most of whom have gone on to successful careers as investigators and leaders in general medicine and in family medicine. His research has received support from the National Institutes of Health (NIH), the Agency for Healthcare Research and Quality (AHRQ), the Robert Wood Johnson Foundation, the Hartford Foundation, and the Macy Foundation. In his role as Center Director, he has authored 15 papers, reviews, and book chapters with a focus on the use of learning collaboratives to transform primary care, the impact of community health workers on resource use, and the impact of changes in primary care practice and payment on the finances of primary care practice.

Dr. David Price is a Professor of Family Medicine at the University of Colorado Anschutz School of Medicine; Senior advisor to the President, American Board of Family Medicine; and an advisor and coach in Health Professions Education, Quality Improvement and Continuing Professional Development. Dr. Price spent 27 years in the Kaiser Permanente (KP) system in several roles, including Director of Medical Education for the Colorado Region and the (national) Permanente Federation; physician investigator with the KP Colorado Institute of Health Research; Codirector of the Kaiser Colorado Center for Health Education, Dissemination and Implementation research; Clinical Lead for Kaiser National Mental Health Guidelines; member of the Kaiser National Guideline Directors Group, and Chair of Family Medicine for the Colorado Permanente Medical Group. From 2014-2018 he served as Senior Vice-President, American Board of Medical Specialties Research and Education Foundation, and Executive Director of the ABMS Multi-Specialty Portfolio Approval Program. Dr. Price served on the ABFM Board of Directors from 2003 – 2008, where he chaired the R&D and Maintenance of Certification committees and was Board Chair from 2007-2008. He is a past Director of the Accreditation Council for Continuing Medical Education, a past-president of the Colorado Academy of Family Physicians, past chair of the AAMC Group on Educational Affairs section on Continuing Education and Improvement, and currently serves on the AAMC Integrating Quality Initiative steering committee. He is widely published and has spoken nationally and internationally and published in areas ranging from continuing medical education/professional development, quality and practice improvement, mental health, and evidence-based medicine. Dr. Price received his M.D. degree from Rutgers Medical School in 1985 and completed his Family Medicine Residency and chief residency at JFK Medical Center, Edison, NJ, in 1988. He is Board Certified by and Maintaining Certification with the American Board of Family Medicine. He is a fellow of the American Academy of Family Physicians, the Alliance for Continuing Education in the Health Professions, and the Society for Academic Continuing Medical Education (SACME) and the recipient of the 2018 SACME Distinguished Service in CME Award.

Gordon Schiff, MD, is a general internist and Quality and Safety Director for the Harvard Medical School Center for Primary Care. He is Associate Director of Brigham and Women’s Center for Patient Safety Research and Practice and Associate Professor of Medicine at Harvard Medical School. He worked for more than 3 decades at Chicago’s Cook County Hospital where he directed the general medicine clinic and chaired the hospital’s quality improvement committee and was PI for the AHRQ Developmental Center for Patient Safety Research focusing on diagnostic errors (the Diagnosis Evaluation and Education Research (DEER) Project). He directed a four year AHRQ-funded Massachusetts malpractice and patient safety improvement PROMISES project (Proactive Reduction in Outpatient Malpractice: Improving Safety Efficiency and Satisfaction), was PI for the AHRQ-Brigham medication safety HIT CERT CEDAR (Calling for Earlier Detection of Adverse Reaction) Project, and has led multiple projects funded by the Harvard Risk Management Foundation to study diagnostic errors, pitfalls, and develop tools to help prevent and minimize such errors. He was PI for an AHRQ HIT Safety grant working to enhance CPOE by incorporating the drug indication into prescription ordering. He currently directs two large projects funded by the Gordon and Betty Moore Foundation, one focusing on improving diagnosis safety and quality and the other to promote more appropriate and conservative medication prescribing. The diagnosis project, the PRIDE (Primary-care Research in Diagnosis Errors) Learning Network, is working to study and improve diagnosis by sharing diagnosis cases from an unprecedented coalition of local and national stakeholders with interest and expertise in diagnosis safety.

Margaret Smith is the Director of Operations of HEA3RT where she works with industry collaborators, and clinical and operational leaders at Stanford on the development and implementation of artificial intelligence technologies that improve the lives of patients, providers, and health systems. Her expertise lies in healthcare quality improvement, complex problem solving, facilitating cross discipline collaboration, and design thinking. Her passion is building and applying collaborative mix-methods approaches to develop, implement, and study technology solutions in healthcare that work for providers and patients rather than impede care delivery. Previously, she held senior positions in quality improvement for many years in academic and non-academic medicine garnering extensive experience in a broad set of organizational and incentive structures. In these roles, she managed portfolios of projects across all care settings, achieving consistent and sustained results leading large multidisciplinary teams, and guided senior executives on visioning, strategy development, goal setting and managing improvement across the enterprise. Margaret holds a bachelor’s degree in finance and risk management, a master’s in business administration with a specialization in healthcare management from the Baylor Hankamer School of Business, Robbins Institute for Health Policy and Leadership, and a Lean Six-Sigma master black belt certification.

Leith States photo

Leith States, MD, MPH is a native of Los Angeles, California. Dr. States received his bachelors degree from Azusa Pacific University, masters degree in public health from the Loma Linda University School of Public Health, and his medical degree from the University of California at San Diego School of Medicine. He received internship training in Internal Medicine at the Naval Medical Center San Diego, and completed residency training in Preventive Medicine at Loma Linda University Medical Center, serving as Chief Resident in his final year of training. From 2011 to 2013, States served as Battalion Surgeon for 1st Battalion, 1 Marines, 1st Marine Division, where he deployed in support of combat operations during Operation Enduring Freedom. He directed a medical department consisting of one physician assistant, two Independent Duty Corpsmen, and over sixty Navy Corpsmen in garrison and combat-related care for over 1200 United States Marines. From September 2015 to July 2018 he was assigned to Navy Environmental and Preventive Medicine Unit FIVE where he served as Department Head for Operations, Officer in Charge for the Forward Deployable Preventive Medicine Unit – team FIVE, and the Navy Medicine West Public Health Emergency Officer, providing public health expertise to an active duty population of over 500,000 spread across the Pacific Command region. He currently serves at the Deputy Chief Medical Officer for the OASH working on issues of national public health importance for the ASH. Dr. States is board certified in Preventive Medicine, and is a current member of the American College of Preventive Medicine. He has published previously on pediatric oncology molecular biology, and has been actively involved with development and implementation of clinical programs aimed at improving preventive care services delivery to veterans living with HIV/AIDS. He has also served as a fellow with the Office of Disease Prevention and Health Promotion, HHS, engaging in research on patient-centered health information technology. His personal awards include the Meritorious Service Medal, Navy and Marine Corps Commendation Medal, Navy and Marine Corps Achievement Medal and multiple unit and campaign awards.

Stefan Strydom is an experienced data scientist and machine learning engineer with over 10 years’ experience in the healthcare industry. During this time, he has worked on diverse projects, ranging from statistical analysis and actuarial modelling to advanced analytics and machine learning. Recent machine learning projects include the development of a state-of-the-art automatic ICD coding system from free-form text EHR data completed as part of his MSc thesis, the co-development of a text summarisation model for patient-to-doctor mobile chats and two medical computer vision algorithms. Stefan is also a Fellow of Actuarial Society of South Africa. As a healthcare actuary, he has special interests in health financing and alternative payment models, particularly for primary care. With Cristina Mannie, Stefan is the co-founder of Mast Analytics, a healthcare-focused data science and analytics start-up. The mission of our company is to use data science, machine learning and analytics to improve public health

Ayin Vala, MA is the Associate Director, Cloud Computing and Data Science, VPHS Population Health Sciences at Stanford University and the founder of DeepMD and cofounder and chief data scientist at the nonprofit organization Foundation for Precision Medicine, where he and his research and development team work on statistical analysis and machine learning, pharmacogenetics, molecular medicine, and sciences relevant to the advancement of medicine and healthcare delivery. Ayin has won several awards and patents in the healthcare, aerospace, energy, and education sectors. Ayin holds master’s degrees in information management systems from Harvard University and mechanical engineering from Georgia Tech.

Xujing Wang, PhD, is the Program Director for data science and computational biomodelling at the National Institute of Health.  Xujing manages a research portfolio of projects that develop methods and tools that enable the utilization of data science in, that utilize high-throughput (Big) data in, and that develop computational, or joint computational and laboratory approaches to model biological processes relevant to, diabetes and metabolic disease research, or any other area of disease or biology of relevance to the DEM mission.

Jeremy Weiss, MD, PhD is an assistant professor of health informatics at Heinz College. His research focuses on the development of machine learning algorithms for analysis of electronic health records (EHRs). The recent growth in EHR usage underlies a transformation in analytic approaches to medical data. His research in machine learning provides tools to characterize and make predictions from EHRs about the health of populations and individuals. Jeremy received his MD-PhD from the University of Wisconsin-Madison with a focus in medicine and computer science.

Dr. Williamson is the Senior Data Scientist at the Canadian Primary Care Sentinel Surveillance Network (CPCSSN), Associate Director of the Centre for Health Informatics, and Associate Professor at the University of Calgary, Canada. Dr. Williamson’s research involves applications of data science methods including machine learning and natural language processing to primary care electronic medical record data and linking large health data assets.

Thursday, March 18, 2021

1:00PM – 5:00 PM EDT | 10:00AM – 2:00 PM PDT

1:00 – 1:15 PM EDT | 10:00 – 10:15 AM PDT

Welcome & Brief Meeting Overview


1:15 – 1:45 PM EDT | 10:15 – 10:45 AM PDT

Brief Introductions


1:45 – 2:50 PM EDT | 10:45 – 11:50 AM PDT

AI/ML & Primary Care: Opportunities to Transform Delivery
(Panel Presentation & Discussion)

1:45 PM – 1:50 PM Steven Lin, MD
1:50 PM – 1:55 PM Asaf Bitton, MD, MPH
1:55 PM – 2:00 PM John Maier, PHD, MD
2:00 PM – 2:05 PM Ethan Berke, MD, MPH
2:05 PM – 2:10 PM Christian Silcox, PHD

2:50 – 3:00 PM EDT | 11:50 – 12:00 PM PDT

Break


3:00 – 4:00 PM EDT | 12:00 – 1:00 PM PDT

AI/ML & Primary Care: Opportunities to Transform Research (Panel Presentation & Discussion)

3:05 PM – 3:10 PM Arlene Bierman, MD, MS
3:10 PM – 3:15 PM Mark Sendak, MD, MPP
3:15 PM – 3:20 PM Jacqueline Kueper, MS, PhD Candidate
3:20 PM – 3:25 PM Miguel Marino, PhD
3:25 PM – 3:30 PM Sherri Rose, PhD

4:00 – 4:30 PM EDT | 1:00 – 1:30 PM PDT

Breakout Session A: Small Group Discussions on Advancing AI/ML application in Primary Care Research & Practice


4:30 – 4:50 PM EDT | 1:30 – 1:50 PM PDT

Small Group Report Outs


4:50 – 5:00 PM EDT | 1:50 – 2:00 PM PDT

Wrap up, Review Day 2 Agenda & Adjourn

Friday, March 19, 2021

10:00AM – 1:00 PM EDT | 7:00AM – 10:00 AM PDT

10:00 – 10:20 AM EDT | 7:00 – 7:20 AM PDT

Welcome, Review Lessons from Day 1, Agenda for Day 2


10:20 – 11:00 AM EDT | 7:20 – 8:00 AM PDT

Breakout Session B: Small Group Discussions on Setting Priorities for the AI/ML to advance primary care agenda:


11:00 – 12:00 PM EDT | 8:00 – 9:00 AM PDT

Small Group Report Outs, Reactions & Ranking Exercise


11:00-11:15 AM EDT | 8:00 – 8:15 AM PDT

Break


12:15 – 1:00 PM EDT | 9:15 – 10:00 AM PDT

Next steps/Working together to advance an agenda


1:00 PM EDT | 10:00 AM PDT

Adjourn


Download the pdf

Thursday, March 18, 2021

1:00PM – 5:00 PM EDT
10:00AM – 2:00 PM PDT

1:00 – 1:15 PM EDT
10:00 – 10:15 AM PDT

Welcome & Brief Meeting Overview


1:15 – 1:45 PM EDT
10:15 – 10:45 AM PDT

Brief Introductions


1:45 – 2:50 PM EDT
10:45 – 11:50 AM PDT

AI/ML & Primary Care: Opportunities to Transform Delivery
(Panel Presentation & Discussion)

1:45 PM – 1:50 PM
Steven Lin, MD
1:50 PM – 1:55 PM
Asaf Bitton, MD, MPH
1:55 PM – 2:00 PM
John Maier, PHD, MD
2:00 PM – 2:05 PM
Ethan Berke, MD, MPH
2:05 PM – 2:10 PM
Christian Silcox, PHD


2:50 – 3:00 PM EDT
11:50 – 12:00 PM PDT

Break


3:00 – 4:00 PM EDT
12:00 – 1:00 PM PDT

AI/ML & Primary Care: Opportunities to Transform Research (Panel Presentation & Discussion)

3:05 PM – 3:10 PM
Arlene Bierman, MD, MS
3:10 PM – 3:15 PM
Mark Sendak, MD, MPP
3:15 PM – 3:20 PM
Jacqueline Kueper, MS, PhD Candidate
3:20 PM – 3:25 PM
Miguel Marino, PhD
3:25 PM – 3:30 PM
Sherri Rose, PhD


4:00 – 4:30 PM EDT
1:00 – 1:30 PM PDT

Breakout Session A: Small Group Discussions on Advancing AI/ML application in Primary Care Research & Practice


4:30 – 4:50 PM EDT
1:30 – 1:50 PM PDT

Small Group Report Outs


4:50 – 5:00 PM EDT
1:50 – 2:00 PM PDT

Wrap up, Review Day 2 Agenda & Adjourn

Friday, March 19, 2021

10:00AM – 1:00 PM EDT
7:00AM – 10:00 AM PDT

10:00 – 10:20 AM EDT
7:00 – 7:20 AM PDT

Welcome, Review Lessons from Day 1, Agenda for Day 2


10:20 – 11:00 AM EDT
7:20 – 8:00 AM PDT

Breakout Session B: Small Group Discussions on Setting Priorities for the AI/ML to advance primary care agenda:


11:00 – 12:00 PM EDT
8:00 – 9:00 AM PDT

Small Group Report Outs, Reactions & Ranking Exercise


11:00 – 11:15 AM EDT
8:00 – 8:15 AM PDT

Break


12:15 – 1:00 PM EDT
9:15 – 10:00 AM PDT

Next steps/Working together to advance an agenda


1:00 PM EDT
10:00 AM PDT

Adjourn


Download the pdf
With the digitization of everything from videos to voices and documents, artificial intelligence and machine learning (AI/ML) have revolutionized industries, including medicine, but have yet to transform primary care. A review of primary care AI/ML concluded that the field remains in “early stages of maturity,” despite a history spanning nearly 35 years.1 Only 1 out of every 7 of these papers includes a primary care author; therefore, one barrier to greater impact is engagement from the primary care community.

Transforming primary care is a necessity if we are to reduce waste and reverse declines in life expectancy.2,3 Primary care touches all Americans,4,5, and its presence in communities extends lives.6 Despite this benefit, primary care remains underfunded and overwhelmed.7 To care for patients holistically, primary care practices must coordinate with specialists, hospitals, mental health providers, and public health – a function that is critical to the effort to combat the current coronavirus disease 2019 pandemic.8 The resulting avalanche of data exceeds what individuals and teams can realistically manage, and practices struggle to turn these data into the insights needed to improve quality and health. Once obtained, these data must be stored in electronic health records (EHRs) and compiled into quality measures, a necessary but time-consuming process that erodes face time with patients and contributes to burnout.9–11

Turning data into knowledge is a challenge across all fields, and many have turned to computer science. In primary care, AI/ML can ensure that EHRs are updated in real-time, conversations are accurately and efficiently converted into notes, patients receive the preventive services they need, and high-risk individuals are connected to appropriate interventions. However, in the absence of input from end-users, including patients and clinicians, AI/ML will not automatically lead to better outcomes. Critics warn that AI/ML could increase costs, magnify biases, and disrupt relationships.

To avoid this fate, the primary care and AI/ML communities need to work in a transdisciplinary manner to create new frameworks and methods tailored to the complexity and longitudinality of primary care. To do so, they must collaboratively answer the questions critical to this field. For example, given scarce resources, how should key questions be prioritized? What are the most promising applications of primary care AI/ML? What investments in primary care AI/ML partnerships will yield the greatest returns? What infrastructure is needed to facilitate connections between primary care and AI/ML researchers?

TTo address these gaps, the American Board of Family Medicine plans to convene a virtual meeting titled “Setting a Research Agenda for the use of Artificial Intelligence & Machine Learning in Primary Care” in February 2020. Over two days, a small group of experts with combined knowledge of AI/ML, large datasets, policy, and primary care research will convene to discuss the state of AI/ML techniques and their use in the primary care setting, identify barriers and opportunities for further use, declare an agenda for future research and a priority list of questions.

The specific aims of the meeting will be to:
  1. Review a summary of ongoing efforts to incorporate AI/ML techniques into primary care research.
  2. Identify barriers to be addressed, assets to be leveraged in pursuit of greater integration between AI/ML and primary care.
  3. Develop consensus around a research agenda for the application of these techniques in primary care.
  4. Declare priority domains where the techniques may offer the most-needed insights and priority questions that need the most immediate attention.
  5. Discuss a plan for engaging the primary care research community, funding community, data, and policy stakeholders in advancing both the agenda and priority research questions.

A report will summarize these discussions and serve as fodder for peer-reviewed publications to follow.

Developing a shared language and standardizing definitions are important as we bring together disparate stakeholders. For example, primary care has been defined differently by organizations. The World Health Organization defines primary health care as “essential health care based on practical, scientifically sound and socially acceptable methods and technology made universally accessible to individuals and families in the community through their full participation and at a cost that the community and country can afford to maintain.” Its Declaration of Alma Ata goes on to state that “[primary health care] forms an integral part both of the country’s health system, of which it is the central function and main focus, and of the overall social and economic development of the community. It is the first level of contact of individuals, the family and community with the national health system bringing health care as close as possible to where people live and work, and constitutes the first element of a continuing health care process.” Finally, “[It] addresses the main health problems in the community, providing promotive, preventive, curative and rehabilitative services accordingly.” 12 Barbara Starfield echoed some of these ideas when she characterized primary care as first-contact, continuous, comprehensive, and coordinated care provided to populations undifferentiated by gender, disease, or organ system.13 Similarly, the Institute of Medicine defined primary care as “the provision of integrated, accessible health care services by clinicians who are accountable for addressing a large majority of personal health care needs, developing a sustained partnership with patients, and practicing in the context of family and community.”14

John McCarthy coined the term AI, calling it the idea of getting a computer to do things which, when done by people, are said to involve intelligence.15 Marvin Minsky added to this definition by calling it “the study of ideas to bring into being machines that respond to stimulation consistent with the traditional response from humans, given the human capacity for contemplation, judgment, and intention.”16 These tasks include problem-solving, reasoning, understanding language, and learning. A subset of AI – machine learning – focuses on the learning aspect of intelligence. In his book Machine Learning, Tom Mitchell defined the field as “concerned with the question of how to construct computer programs that automatically improve with experience.” He goes on to describe machine learning as a computer program that can “learn from experience E with respect to some class of tasks T and performance measure P, if its performance at tasks in T, as measured by P, improves with experience E.”17

Primary Care research, like the enterprise itself, is complex, with questions that lend themselves to approaches with commensurate complexity. Yet the use of AI in family medicine and primary care research is limited. In their recent commentary “Family Medicine & AI: Better Together”, Liaw et al note:

Without our input, AI risks following the path of EHRs. When the Health Information Technology for Economic and Clinical Health (HITECH) Act was passed, policy makers believed that EHRs would lead to care that was more efficient, effective, and equitable,15 and EHRs have led to important advances in population health and quality.16 However, with increasing burnout and decreasing time with patients, many lament that EHRs cater to the needs of administrators and EHR vendors rather than physicians and patients.17 The usability and interoperability failures underlying these complaints are not the result of gaps in technological expertise. Instead, these failures emerged, in part, because end-users like ourselves have been insufficiently engaged in relevant design, policy, and implementation decisions.

They further note the natural ability of AI wed itself to integrate multiple data sources including geographic, EHR, claims, and pharmacy data to identify those individuals at high risk for multiple chronic diseases, to facilitate timely referral and appropriate treatment, to streamline and facilitate quality measurement and to enhance primary care of patients directly.

APubMed search conducted in 2019 revealed no AI/ML papers in Family Medicine, Annals of Family Medicine, or the Journal of the American Board of Family Medicine. For comparison, AI/ML papers number 18, 77, and 8 for Academic Medicine, JAMA, and the Journal of General Internal Medicine, respectively. For context, a bibliometric analysis conducted in the same year identified 1,473 AI-related health care papers using Web of Science.18

In the summer editions of Annals of Family Medicine & Family Medicine, however, four relevant papers emerged:

  • Kueper JK, Terry AL, Zwarenstein M, Lizotte DJ. Artificial Intelligence and Primary Care Research: A Scoping Review. Ann Fam Med. 2020;18(3):250-258. doi:10.1370/afm.2518
  • Wingrove P, Liaw W, Weiss J, Petterson S, Maier J, Bazemore A. Using Machine Learning to Predict Primary Care and Advance Workforce Research. Ann Fam Med. 2020;18(4):334-340. doi:10.1370/afm.2550
  • Liaw W, Kakadiaris IA. Artificial Intelligence and Family Medicine: Better Together. Fam Med. 2020;52(1):8-10. https://doi.org/10.22454/FamMed.2020.881454.
  • Liaw W, Kakadiaris IA. Primary Care Artificial Intelligence: A Branch Hiding in Plain Sight. Annals of Family Medicine. May 2020; 18(3): 194-195.

Kueper et al. found 405 primary care AI articles since 1986.1 Two thirds of these articles focused on developing or modifying AI methods while the remaining supported diagnostic or treatment recommendations. Papers were included if they referenced primary care data, settings, or personnel. As previously noted, only 1 in 7 included an author with a primary care appointment. Noting that few tools were ready for widespread implementation, the authors called for the inclusion of frontline clinicians in these studies and the evaluation of these tools in primary care settings.

Partnerships and Planning Committee

A Planning Committee will guide the development of this Conference. Prior to the meeting date, Committee members will meet monthly to provide direction for the Conference, give feedback on Conference materials, select and recruit participants, and interpret participant responses to pre-conference prompts. Committee members will consist of representatives from the American Board of Family Medicine, Stanford University, the University of Houston, and federal agencies.

Conference Format

Before the meeting, the Planning Committee will engage in activities that will enhance the effectiveness of the time spent communicating synchronously. First, a Conference intern will conduct 60-minute interviews with participants (Table 1). During this interview, the intern will ask questions related to primary care AI/ML exemplars, opportunities, challenges, assets, and priority domains/questions. This interview will also touch on why participants are attending and what they hope to accomplish. The intern will record field notes that will inform the virtual conversation. Prior to the meeting, participants will receive relevant readings and a synthesis of the interviews.

In this 2-day, virtual meeting, we will have panels and small group breakouts to maximize participant engagement. The discussion will cover four themes: Current Landscape, Research Agenda, Infrastructure, and Dissemination. Each small group will include a student reporter, who will present back to the large group.

We plan to recruit 20 national experts to participate. To select these individuals, we will consider diversity in expertise, gender, race/ethnicity, and region. Attendees will include stakeholders from primary care, artificial intelligence, research, frontline practice, industry, insurance, government, community-based organizations, and law.

Related Conferences

Multiple associations and conferences bring together health care and AI/ML stakeholders. For example, Datapalooza, the Healthcare Information and Management Systems Society Conference, and Ai4 Healthcare provide content at the intersection of health care and technology, though each targets different audiences. Despite these opportunities, these meetings neither focus on primary care specifically nor address the aims documented in this proposal.

Conference Work Products and Dissemination Plan

Several products will come from this event. First, we will produce a white paper describing the event and lessons learned from this process (Table 2). This document will include the participants, agenda, bibliography, participant interviews, and themes. Second, we will submit a manuscript for peer-review that outlines the priority research domains and questions for primary care AI/ML.

  1. Kueper J, Terry AL, Zwarenstein M, Lizotte DJ. Artificial Intelligence and Primary Care Research: A Scoping Review. Ann Fam Med. Published online 2020.
  2. Institute of Medicine. Better Care at Lower Cost: The Path to Continuously Learning Health Care in America. National Academies Press; 2013.
  3. Case A, Deaton A. Rising morbidity and mortality in midlife among white non-Hispanic Americans in the 21st century. Proc Natl Acad Sci. 2015;112(49):15078-15083. doi:10.1073/pnas.1518393112
  4. Petterson S, McNellis R, Klink K, Meyers D, Bazemore A. The State of Primary Care in the United States. Robert Graham Center; 2018.
  5. Green LA, Fryer GE, Yawn BP, Lanier D, Dovey SM. The Ecology of Medical Care Revisited. N Engl J Med. 2001;344(26):2021-2025.
  6. Basu S, Berkowitz SA, Phillips RL, Bitton A, Landon BE, Phillips RS. Association of Primary Care Physician Supply With Population Mortality in the United States, 2005-2015. JAMA Intern Med. Published online February 18, 2019. doi:10.1001/jamainternmed.2018.7624
  7. Martin S, Phillips RL, Petterson S, Levin Z, Bazemore AW. Primary Care Spending in the United States, 2002-2016. JAMA Intern Med. 2020;180(7):1019. doi:10.1001/jamainternmed.2020.1360
  8. Westfall JM, Petterson S, Rhee K, et al. A New “PPE” For A Thriving Community–Public Health, Primary Care, Health Equity. Health Affairs Blog. Published September 25, 2020. Accessed October 2, 2020.
  9. Young RA, Burge SK, Kumar KA, Wilson JM, Ortiz DF. A Time-Motion Study of Primary Care Physicians’ Work in the Electronic Health Record Era. Fam Med. 2018;50(2):91-99. doi:10.22454/FamMed.2018.184803
  10. Casalino LP, Gans D, Weber R, et al. US Physician Practices Spend More Than $15.4 Billion Annually To Report Quality Measures. Health Aff (Millwood). 2016;35(3):401-406. doi:10.1377/hlthaff.2015.1258
  11. Shanafelt TD, Hasan O, Dyrbye LN, et al. Changes in Burnout and Satisfaction With Work-Life Balance in Physicians and the General US Working Population Between 2011 and 2014. Mayo Clin Proc. 2015;90(12):1600-1613. doi:10.1016/j.mayocp.2015.08.023
  12. World Health Organization. Declaration of Alma-Ata International Conference on Primary Health Care.; 1978:159-161. Accessed October 1, 2020.
  13. Starfield B. Primary Care: Balancing Health Needs, Services, and Technology. Oxford University Press; 1998.
  14. Institute of Medicine. Defining Primary Care: An Interim Report. The National Academies Press; 1994.
  15. McCarthy J, Minsky M, Rochester N, Shannon C. A Proposal for the Dartmouth Summer Research Project on Artificial Intelligence: August 31, 1955. AI Mag. 2006;27(4):12-14.
  16. Dean R & D Desh Bhagat University, Mandi Gobindgarh, India, Grewal PDS. A Critical Conceptual Analysis of Definitions of Artificial Intelligence as Applicable to Computer Engineering. IOSR J Comput Eng. 2014;16(2):09-13. doi:10.9790/0661-16210913
  17. Mitchell TM. Machine Learning. McGraw-Hill; 1997.
  18. Guo Y, Hao Z, Zhao S, Gong J, Yang F. Artificial Intelligence in Health Care: Bibliometric Analysis. J Med Internet Res. 2020;22(7):e18228. doi:10.2196/18228
  19. Yang Z, Silcox C, Sendak M, et al. Advancing primary care with Artificial Intelligence and Machine Learning [published online ahead of print, 2021 Dec 23]. Healthc (Amst). 2021;10(1):100594. doi:10.1016/j.hjdsi.2021.100594