Data Transformation to Advance AI/ML Research and Implementation in Primary Care

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

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.

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