For most of the last year I had the privilege of serving as director of the US Agency for Healthcare Research and Quality (AHRQ), the lead federal agency charged with improving the safety and quality of America’s health care system. AHRQ is not a payer or regulator. It develops the knowledge, tools, and data needed to improve the health care system and help Americans, health care professionals, and policymakers make informed health decisions.
Change is a reality of our political process. When the new administration took over last month, I reluctantly departed to return to my work as a primary care physician and a health services researcher at the University of California, San Francisco (UCSF). The completion of my work at AHRQ did nothing to dampen my excitement about AHRQ’s future and its readiness to support transformation to an improved health care system.
In meetings with staff at AHRQ, I described our challenge as bringing Moneyball to medicine. It was my way of pointing out how major league sports have integrated data analytics into their workflow to improve team performance. There is a parallel opportunity for us in health care.
Moneyball is a movie based on the true story of Billy Beane, the general manager of Major League Baseball’s Oakland A’s. The film tells the story of a ballplayer-turned-executive, played by Brad Pitt, who finds himself stuck with an underperforming team that makes roster choices based largely on the opinions of “expert” scouts. While these scouts know a lot more than the average person does about the star potential of young players, they also have a remarkable number of misfires, leading the team to spend money on players who don’t pan out.
Radical Use of Clinical Data
The organization’s fortunes shift dramatically, however, when Beane takes a radical new approach. With a limited budget compared to richer teams in bigger markets, he adopts the predictive lessons of big data instead of relying on the opinions and intuition of scouts to select players for his team.
The data analytics that guided Beane and his staff in the 2002 season weren’t obscure or particularly hard to understand, nor did they invent them. What was truly revolutionary was his commitment to use them. In the process, he fielded a team that set the American League record for consecutive wins (20), won an impressive 103 regular season games, and made it into the postseason playoffs. His success led to a rapid transformation in the use of data not only among other baseball teams, but across all professional sports.
For the most part, clinicians function like baseball scouts. We bring a special knowledge to improving health informed by our experience. We are underperforming, however, by not making a stronger commitment to a data-driven, evidence-based approach. We have not mustered the courage Billy Beane showed in running his organization. Like him, we need to base our decisionmaking less on limited direct experience and more on data analytics that can be applied to our routine clinical workflow. It is scary to take this leap, because the stakes are higher for health than they are for baseball. But then again, so are the rewards if we do.
With the growing availability of digitized clinical data and an emerging cadre of sophisticated statistical approaches developed by health services researchers, health care organizations have a golden opportunity to make a transformational change that can improve the quality and safety of care. When a health care organization incorporates these approaches into its routine workflow of care, it takes an important step toward becoming a learning health care system. The learning health care system is a model in which clinical practices systematically participate in the generation, adoption, and application of evidence. During my time at AHRQ, we significantly increased efforts to support the transformation of health care organizations into continuously learning health care systems, which hold great promise.
Hitting Home Runs for Patients
While patients are the ultimate beneficiaries of increased reliance on evidence, AHRQ has focused its efforts on demonstrating the benefits to the clinical leaders of health care organizations. We believe these leaders can become the Billy Beane change agents who can support local efforts to ensure that evidence becomes a routine part of everyday practice. I envision the establishment of a learning network between AHRQ and clinical leaders within health care organizations to co-create the tools and approaches that are most likely to be of help.
It was a privilege to serve as the director of AHRQ, and I’m grateful to have had the opportunity. I was impressed from day one by agency staff members’ breadth of talent, their commitment to scientific rigor, and their passion for improving the quality and safety of patient care. I remain gratified by the gains we made at AHRQ and deeply optimistic about the agency’s prospects for advancing its mission.
No doubt about it, Moneyball was a great film. And AHRQ could contribute to an even greater story by helping to incorporate data analytics and evidence into the practice of medicine. Who knows, maybe Brad Pitt will someday star in the sequel — Medicineball.
Andy Bindman is professor of medicine, epidemiology, and biostatistics and an affiliated faculty member within the Philip R. Lee Institute for Health Policy Studies at the University of California, San Francisco. He served as director of the US Agency for Healthcare Research and Quality (AHRQ) from May 2016 until the conclusion of the Obama administration. He is a primary care physician who has practiced and taught clinical medicine at Zuckerberg San Francisco General Hospital while also conducting health services research to improve care within the health care safety net. In 2009/10, he was a Robert Wood Johnson health policy fellow on the staff of the US House Energy and Commerce Committee and helped draft legislative language for the Affordable Care Act. From 2011 to 2014, Dr. Bindman served as a senior adviser to the US Department of Health and Human Services (HHS) within the Office of the Assistant Secretary for Planning and Evaluation, and later was a senior adviser to the Centers for Medicare & Medicaid Services. He received his medical degree from Mount Sinai School of Medicine.