Machine Learning and the Pursuit of High-Value Health Care

Abstract

The United States faces unsustainable growth in health care costs despite limited return on this investment in the form of health outcomes, prompting efforts to improve the value of health care. Artificial intelligence has the potential to enable high-value decision-making from the perspectives of the patient, clinician, and health system, but it also could worsen value. This article assesses these opportunities and challenges, separates reality from hype, and proposes policy approaches for contemporary artificial intelligence — specifically, machine learning — to contribute to rather than detract from high-value care. The conclusion is that it is critical to consider value — in particular, the cost component — in all machine-learning work and to let humans and algorithms each do what they do best.

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