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Harvard Business Review: Using Behavioral Nudges To Treat Diabetes

“Health care practitioners and payer organizations increasingly use big data to overcome what might be called a “flaw of averages” in traditional medicine: a treatment that has been tested at a population level might in fact work better for some individuals than others. The goal of precision medicine is therefore to identify treatments appropriate to an individual — rather than a population — based on granular genotype and phenotype data from his or her medical records. The individual data-driven nature of such treatment protocols improves the odds that a specific treatment will work for a specific patient. But both traditional and precision medicine confront a “last mile problem” involving patient behavior change: even the most appropriate medical treatment will be effective only if the patient follows through on it. The cost of medication non-adherence is conservatively estimated at more than $250 billion a year in the US, and the majority of hospital readmissions after surgery are due to non-adherence to discharge protocols.” Read more at Harvard Business Review