Evaluation Summary: Clinical Decision Support for Outpatient High-Cost Radiology Ordering

With health care spending accounting for almost one-fifth of the U.S. economy and an even larger share of public sector budgets, policymakers are very interested in reducing spending on health care that provides minimal value to patients. High-cost diagnostic scans, such as magnetic resonance imaging and computed tomography scans, account for about $10 billion in annual Medicare spending. Research suggests that up to 30 percent of these scans, which expose patients to potentially harmful radiation, are unnecessary.

Beginning in 2017, Medicare will no longer reimburse providers for high-cost scans unless they are ordered using a qualifying “clinical decision support system”  – an automated tool that notifies physicians in real time when they have ordered a diagnostic scan that is inconsistent with current professional guidelines. Are these systems the answer to reducing the number of expensive, unnecessary scans ordered?

Bruce Darrow (Mount Sinai), J-PAL affiliate Joseph Doyle (MIT), J-PAL research manager Laura Feeney (MIT), J-PAL affiliate Amy Finkelstein (MIT), Joseph Kannry (Mount Sinai), Madhu Mazumdar (Mount Sinai), David Mendelson (Mount Sinai), and Jesse Shapiro (Brown University) are conducting a randomized evaluation to study the impact of these systems on the ordering of high-cost scans in the Mount Sinai Health System – an internationally acclaimed integrated health care system based in New York City.  More than 2,000 physicians are participating in the study. About half were randomly selected to receive the clinical decision support intervention, with the other half serving as a control group. Will the scan ordering of the physicians who receive the clinical decision support system be different from those who do not? Stay tuned…

For more information on the ongoing study, please read the full evaluation summary on the J-PAL North America website.

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