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The MoneyBall solution to the healthcare crisis

Many recent articles have suggested different reforms for healthcare to reduce costs. These spanned the integration of digital health with clinical care, the widespread use of genetic and genomic tests to differentiate high-risk from low-risk patients and to inform drug development and prescribing decisions, and the use of artificial intelligence (AI) and cognitive computing like IBM’s Watson or Google’s DeepMind. Others have suggested tackling health insurance by repealing the ACA or moving to a single-payer system with the hope of substantial cost savings. But to significantly tackle out-of-control health spending, we need to motivate organizations by making the business case for change and implement data-driven methods that can make a substantial impact on the healthcare crisis—what we call MoneyBall Medicine.

Data analytics and technology has changed the way consumers buy merchandise, handle banking needs, and even how sports teams scout for their player rosters. Although the healthcare industry has long claimed exceptionalism due to regulatory challenges and the special nature of the field, paying more for healthcare hasn’t led to better patient outcomes in the U.S., as numerous healthcare analysts have found. But we’ve come a long way in the past several decades. The Human Genome Project resulted in an explosion of genetic testing companies and insight into human diseases while technological advancements now generate terabytes of data daily at a substantially reduced cost from even a decade ago. Pharmaceutical companies are designing new treatments based on computational modeling of molecules. Patients can email questions or concerns to their doctors after office hours and see lab results via portals to the medical record.

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