Update on the Methods of the U.S. Preventive Services Task Force: Estimating Certainty and Magnitude of Net Benefit

  1. George F. Sawaya, MD;
  2. Janelle Guirguis-Blake, MD, MPH;
  3. Michael LeFevre, MD, MSPH;
  4. Russell Harris, MD, MPH;
  5. Diana Petitti, MD, MPH; and
  6. for the U.S. Preventive Services Task Force
  1. From the University of California, San Francisco, San Francisco, California; University of Washington, Tacoma, Washington; University of Missouri–Columbia, Columbia, Missouri; University of North Carolina School of Medicine, Chapel Hill, North Carolina; and University of Southern California, Los Angeles, California.

    Abstract

    The major goal of the U.S. Preventive Services Task Force (USPSTF) is to provide a reliable and accurate source of evidence-based recommendations on a wide range of preventive services. In this article, the USPSTF updates and reviews the process by which it evaluates evidence, determines the certainty and magnitude of net benefit, and gives a final letter grade to recommendations. Because direct evidence about prevention is often unavailable, the Task Force usually considers indirect evidence. To guide its selection of indirect evidence, a “chain of evidence” is constructed within an analytic framework. The Task Force examines evidence of various research designs that addresses the key questions within the framework. New terms have been added to describe the USPSTF's judgment about the evidence for each key question: “convincing,” “adequate,” or “inadequate.” For increased clarity, the USPSTF has changed its description of overall evidence of net benefit for the preventive service from “good,” “fair,” or “poor” quality to “high,” “moderate,” or “low” certainty. This rating considers the extent to which an uninterrupted chain of evidence exists across the analytic framework. Individual studies will continue to be judged as being of “good,” “fair,” or “poor” quality. Using outcomes tables, the USPSTF estimates the magnitude of benefits and the magnitude of harms, and synthesizes them into an estimate of the magnitude of net benefit. Although some judgment is required at all steps, the USPSTF strives to make the process as explicit and transparent as possible. The USPSTF anticipates that its methods for making evidence-based recommendations will continue to evolve.

    Article and Author Information

    • Disclaimer: Recommendations made by the USPSTF are independent of the U.S. government. They should not be construed as an official position of the Agency for Healthcare Research and Quality or the U.S. Department of Health and Human Services.

    • Acknowledgment: The authors thank Tracy Wolff, MD, MPH; Therese Miller, DrPH; and Mary B. Barton, MD, MPP, of the Agency for Healthcare Research and Quality Center for Primary Care, Prevention, and Clinical Partnerships for expert consultation on the innermost mechanics of the USPSTF; and Marion M. Torchia of the Agency for Healthcare Research and Quality Office of Communications and Knowledge Transfer for editorial assistance.

    • Potential Financial Conflicts of Interest: None disclosed.

    • Requests for Single Reprints: Reprints are available from the USPSTF Web site (http://www.preventiveservices.ahrq.gov).

    • Current Author Addresses: Dr. Sawaya: Department of Obstetrics, Gynecology and Reproductive Science, Epidemiology and Biostatistics, University of California, San Francisco, 3333 California Street, Suite 335, San Francisco, CA 94143-0856.

    • Dr. Guirguis-Blake: Department of Family Medicine, University of Washington Tacoma Family Medicine Residency Program, 521 Martin Luther King Jr. Way, Tacoma, WA 98403.

    • Dr. LeFevre: University of Missouri School of Medicine, M223 Medical Sciences Building, Columbia, MO 65212.

    • Dr. Harris: University of North Carolina School of Medicine, CB #7590 Sheps Center, 725 Airport Road, Chapel Hill, NC 27599-7590.

    • Dr. Petitti: Department of Preventive Medicine, Keck School of Medicine, University of Southern California, 299 East Laurel Avenue, Sierra Madre, CA 91023.

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