
By ZEESHAN SYED
Tens of millions of Americans rely on consumer experience apps to help them find the best new restaurant or the right hairdresser. But while relying on customer opinion might make sense for figuring out where to get dinner tonight, when it comes to picking which doctor is best for you, AI might be more trustworthy than the wisdom of the crowd.
Consumer apps provide us with rich data categories that often take into account preferences, from location to free wi-fi, to help users narrow down choices. Navigating your health insurer’s network of physicians is a different proposition, and some of the popular ranking systems reportedly have significant limitations. Doctors are often categorized by specialty, insurance, hospital, or location, which may be effective for logistics, but fail to take into account a patient’s unique health conditions and say very little about what an individual patient can expect in terms of health outcomes. Research from my company Health at Scale shows that 83% of Medicare patients seeking cardiology care and 88% of cases seeking orthopedic care may not be choosing providers that are highly rated for best predicted outcomes based on each patient’s individual health conditions.
Deep personalization is exactly what physicians, health systems, and insurers need to offer patients to improve outcomes and lower costs across the board. A study using our data recently published in the Journal of Medical Internet Research sought to quantify how consumer, quality and volume metrics may be associated with outcomes. Researchers analyzed data from 4,192 Medicare fee-for-service beneficiaries undergoing elective hip replacements between 2013-2018 in the greater Chicago area, comparing post-procedure hospitalization rate, emergency department visits, and total costs of care at hospitals ranked highly by popular consumer ratings systems and CMS star ratings as well as those ranked highly by a machine intelligence algorithm for personalized provider navigation.
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