The study sought to identify research gaps and propose recommendations for maximizing the outcomes, value, and impact of HSR and PCR investments, including strategies for better coordination and potential realignment of research agendas.This document provides the final report of the study to the U.S. House and Senate Committees on Appropriations. The document should be of interest to health services and primary care researchers, other stakeholders-including health care delivery leaders, consumers, purchasers, insurers, and improvement organizations-as well as congressional and other policymakers concerned with the role of federally funded research in advancing the fields of HSR and PCR.This research was funded by the Agency for Healthcare Research and Quality under Contract No. HHSA290201800002G and carried out within the Payment, Cost, and Coverage Program in RAND Health Care.RAND Health Care, a division of the RAND Corporation, promotes healthier societies by improving health care systems in the United States and other countries. We do this by providing health care decisionmakers, practitioners, and consumers with actionable, rigorous, objective evidence to support their most complex decisions.For more information, see www.rand.org/health-care, or contact

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Research into using artificial intelligence (AI) in health care is growing and several observers predicted that AI would play a key role in the clinical response to the COVID-19. Many AI models have been proposed though previous reviews have identified only a few applications used in clinical practice. In this study, we aim to (1) identify and characterize AI applications used in the clinical response to COVID-19; (2) examine the timing, location, and extent of their use; (3) examine how they relate to pre-pandemic applications and the U.S. regulatory approval process; and (4) characterize the evidence that is available to support their use. We searched academic and grey literature sources to identify 66 AI applications that performed a wide range of diagnostic, prognostic, and triage functions in the clinical response to COVID-19. Many were deployed early in the pandemic and most were used in the U.S., other high-income countries, or China. While some applications were used to care for hundreds of thousands of patients, others were used to an unknown or limited extent. We found studies supporting the use of 39 applications, though few of these were independent evaluations and we found no clinical trials evaluating any application’s impact on patient health. Due to limited evidence, it is impossible to determine the extent to which the clinical use of AI in the pandemic response has benefited patients overall. Further research is needed, particularly independent evaluations on AI application performance and health impacts in real-world care settings.

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