In the early 2000s, the Oakland Athletics were the measuring stick for how to win ballgames. The A’s won more than 100 games in both 2002 and 2003. They made the playoffs four consecutive years. And the team did it with the sixth-smallest payroll in Major League Baseball.
General manager Billy Beane was the mastermind behind a strategy famously documented in the book and the adapted film, Moneyball. Beane used readily available data to identify ball players who got on base more often, meaning they were in position to score. Using analytics commonly known in the baseball world as “sabermetrics,” Oakland brought in players it believed gave them the best chance to win.
Payers and providers are using their own version of “moneyball” to pave their way from fee-for-volume business models to value-based health care. Insurance companies have used data analytics for decades to assess population risk. As value-based care takes hold and providers take on more population risk, providers can leverage their own clinical data, along with predictive analytics, to better manage health and improve quality of care.
Health care organizations are well-positioned to leverage data. Traditionally, claims information was used to chronicle the cost of care and find retrospective patterns of care. Think of claims data as the stats on the back of a baseball card. However, claims data can be fragmented, untimely and generic in their description.
Due to the proliferation of electronic medical records (EMRs), providers are able to augment claims data with clinical data. With some up-front effort invested in normalization, analytics systems can readily pull clinical data — often only days or even seconds old — from EMRs, building a more actionable profile than achievable with claims information alone. Clinical data are the “new stats” that offer much greater detail than claims data, resulting in a more complete picture of a patient’s health history.
Moneyball made winners of the Oakland Athletics. Health care’s “moneyball” — using data and analytics to lower costs and increase quality — makes the patient the true winner. They are able to access care faster and benefit from treatments that take into account their personal strengths and weaknesses. For providers and payers, victory is the ability to keep costs down, better allocate budgets to address population health needs and deliver the highest quality care possible.
For more information on how to leverage data for health care wins, download Optum’s eBook “Moneyball Analytics” by clicking here.
In our next post, we’ll discuss how Beane used data to identify players deemed high-risks but were gems in disguise, and how health care organizations can take the same approach in managing high-risk populations.
About the Author:
Alejandro Reti, MD, MBA
Chief Medical Officer, Optum Analytics
With responsibility for the Office of the CMO, Alejandro is accountable for the clinical integrity and relevance of Optum Analytics’ provider solutions and contributes to thought leadership and clinical product innovation for the organization. Alejandro came to Optum from Premier, where he served as Vice President, Population Health Products with general management responsibility for Premier’s organically developed population health suite. Prior to Premier, Alejandro served as Senior Vice President, Clinical Informatics at Verisk Health, where he led development of a provider analytics solution that achieved top 4 in market share nationally. Previously, Alejandro held positions of increasing responsibility at Avalere Health and The Advisory Board Company. Alejandro received a bachelor’s degree in Psychology from Amherst College, magna cum laude and his MD and MBA degrees from Yale University.