Home Research Research Library Data Transformation to Advance AI/ML Research and Implementation in Primary Care Data Transformation to Advance AI/ML Research and Implementation in Primary Care 2025 Author(s) Tsai, Timothy, Lee, Julie J, Phillips, Robert L, and Lin, Steven Topic(s) Role of Primary Care, Achieving Health System Goals, and What Family Physicians Do Keyword(s) Health Information Technology (HIT), and Practice Innovations Volume Annals of Family Medicine Source Annals of Family Medicine Artificial intelligence and machine learning (AI/ML) in health care is accelerating at a breathtaking pace. As the largest health care delivery platform, primary care is where the power, opportunity, and future of AI/ML are most likely to be realized in the broadest and most ambitious scale. However, there is a relative lack of organized, open, large-scale primary care datasets to attract industry and academia in primary care–focused research and development. This article proposes a set of high-level considerations around the data transformation that is needed to enable the growth of AI/ML applications in primary care. These considerations call for automation of data collection, organization of fragmented data, identification of primary care–specific use cases, integration of AI/ML into human workflows, and surveillance for unintended consequences. By unlocking the power of its data, primary care can play a leading role in advancing health care AI/ML to support patients, clinicians, and the health of the nation. ABFM Research Read all 2021 Uniting Public Health and Primary Care for Healthy Communities in the COVID-19 Era and Beyond Go to Uniting Public Health and Primary Care for Healthy Communities in the COVID-19 Era and Beyond 2025 Regional Variation in Scope of Practice by Family Physicians Go to Regional Variation in Scope of Practice by Family Physicians 2019 The Primary Care Spend Model: a systems approach to measuring investment in primary care Go to The Primary Care Spend Model: a systems approach to measuring investment in primary care 2022 How the Gender Wage Gap for Primary Care Physicians Differs by Compensation Approach : A Microsimulation Study Go to How the Gender Wage Gap for Primary Care Physicians Differs by Compensation Approach : A Microsimulation Study
Author(s) Tsai, Timothy, Lee, Julie J, Phillips, Robert L, and Lin, Steven Topic(s) Role of Primary Care, Achieving Health System Goals, and What Family Physicians Do Keyword(s) Health Information Technology (HIT), and Practice Innovations Volume Annals of Family Medicine Source Annals of Family Medicine
ABFM Research Read all 2021 Uniting Public Health and Primary Care for Healthy Communities in the COVID-19 Era and Beyond Go to Uniting Public Health and Primary Care for Healthy Communities in the COVID-19 Era and Beyond 2025 Regional Variation in Scope of Practice by Family Physicians Go to Regional Variation in Scope of Practice by Family Physicians 2019 The Primary Care Spend Model: a systems approach to measuring investment in primary care Go to The Primary Care Spend Model: a systems approach to measuring investment in primary care 2022 How the Gender Wage Gap for Primary Care Physicians Differs by Compensation Approach : A Microsimulation Study Go to How the Gender Wage Gap for Primary Care Physicians Differs by Compensation Approach : A Microsimulation Study
2021 Uniting Public Health and Primary Care for Healthy Communities in the COVID-19 Era and Beyond Go to Uniting Public Health and Primary Care for Healthy Communities in the COVID-19 Era and Beyond
2025 Regional Variation in Scope of Practice by Family Physicians Go to Regional Variation in Scope of Practice by Family Physicians
2019 The Primary Care Spend Model: a systems approach to measuring investment in primary care Go to The Primary Care Spend Model: a systems approach to measuring investment in primary care
2022 How the Gender Wage Gap for Primary Care Physicians Differs by Compensation Approach : A Microsimulation Study Go to How the Gender Wage Gap for Primary Care Physicians Differs by Compensation Approach : A Microsimulation Study
