Sue S. Feldman, Scott E. Buchalter, and Leslie W. Hayes 

Introduction It has long been known and accepted that healthcare in the United States is too expensive and its outcomes are less than predictable (Marmor, Oberlander, and White 2009). The turn of the century brought with it a realization that healthcare, like other industries, could use data to increase our awareness of seemingly uncontrollable costs and unpredictable outcomes. After almost two decades of compiling, analyzing, and mashing up data and trying to make sense of how the data inform multiple layers of healthcare, the time has come to look beyond the awareness that the data provide and instead develop an understanding of how to use the data for predictable and actionable purposes, especially with regard to healthcare quality and safety.

 The literature is mixed on the degree to which the tools, applications, and systems of health information technology (IT) contribute to actual savings and efficiencies (Buntin et al. 2011; Goldzweig et al. 2009; Marmor, Oberlander, and White 2009; Karsh et al. 2010). However, the area of healthcare quality and safety lends itself to many of the same business intelligence and predictability advantages that have been seen in the credit card industry (Jamal, McKenzie, and Clark 2009; McCullough et al. 2010; Parente and McCullough 2009).

 Much as healthcare has its Triple Aim of per capita cost, population health, and experience of care (Institute for Healthcare Improvement 2018), the credit card industry strives for decreased costs (fraud), increased quality (better transactions), and increased satisfaction (happier merchants and happier cardholders). The credit card industry has used business intelligence to predict behavior that suggests fraud, developed process maps for transaction processing, and offered perks to merchants and cardholders. These parallels suggest an opportunity for healthcare to learn from the credit card industry to use healthcare intelligence for prevention, identification, and action related to quality and safety events.