INSIGHTS
CHEW ON THIS BY KEITH CHEW
HEALTH CARE CAN LEARN FROM CREDIT CARD COMPANIES
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ealth care has long struggled with detecting and addressing medical errors. It’s been more than 20 years since the groundbreaking U.S. Institute of Medicine’s piece To Err is Human and, as an industry, we’re far from achieving zero errors. However, there are things that we can learn from a most unexpected place, the credit card in your pocket. Credit card companies have been making significant advancements in finding and managing anomalous activity, which the industry refers to as “fraud.” While the issue of detecting medical errors is quite different from detecting credit card fraud, both fields face similar challenges – the detection of behaviors that stray from the norm. Credit card companies have risen to the challenge and are investing in what will be a $63 billion global fraud detection and prevention market. These new programs have led to recent and projected decreases in existing credit card fraud claims in the United States. As these efforts develop, what can health care leaders learn from the work being done by credit card companies? REVIEW EVERYTHING, SMARTLY Fraud detection systems have been around since the 1990s. In the past, the systems heavily depended on static rules that only reviewed a small sample of credit card transactions. For a long time, the promise of new technology
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failed to deliver, like the health care industry’s experience with EHRs. The root of the problem for credit card companies was a high technology infrastructure barrier, coupled with the fact that automation and algorithms had yet to reach a level of maturity that could deliver scalable value. In addition, early fraud warning systems were simplistic, relying on human-coded rules which failed to account for the myriad of situations in the real world. This combination of factors led to incorrect approvals on unlawful activity while blocking legitimate transactions, and costing, according to some estimates, $118 billion in lost revenue. Rules-based checking led to inaccurate and costly consequences that no credit card company nor hospital wants. A corollary to this in today’s EHR age are the constant warnings coming from EHR systems based on limited data streams. Unfortunately, this has led to the widespread problem of alert fatigue in many health care systems, wasting time and frustrating health care practitioners. Today, the credit card industry’s modern solutions are addressing both problems. Leading fraud detection systems can review every transaction and use state-of-the-art artificial intelligence models with higher sensitivity and specificity. This new paradigm of analysis detects fraud in a way that hand-written rules could not and, equally important, does not trigger as many distracting false positives. In health care, clinicians and leaders know the pain of hearing and seeing a multitude of alarms from the EHR and other medical devices,
ADVANCING THE IMAGING PROFESSIONAL
