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Primary care physicians are likely both excited and apprehensive at the prospects for artificial intelligence (AI) and machine learning (ML). Complexity science may provide insight into which AI/ML applications will most likely affect primary care in the future. AI/ML has successfully diagnosed some diseases from digital images, helped with administrative tasks such as writing notes in the electronic record by converting voice to text, and organized information from multiple sources within a health care system. AI/ML has less successfully recommended treatments for patients with complicated single diseases such as cancer; or improved diagnosing, patient shared decision making, and treating patients with multiple comorbidities and social determinant challenges.
As academic institutions are facing increasingly fierce competition for a highly skilled workforce, support for caregivers could be a key selling point, committee member Robert Phillips Jr., founding executive director of the Center for Professionalism and Value in Health Care, pointed out during today’s webinar. “Our universities, our science settings, could really enhance their competitiveness within the country—for funding, for success—by creating a workplace that not just accommodates caregiving, but that embraces it and makes it possible.”
In this survey study of 2088 physicians, 70% indicated being at least somewhat satisfied with access to outside information. However, only 23% indicated that it was very easy to use outside information, and very few (8%) indicated that it was very easy to use information from different electronic health record systems.
