According to the National Academy of Medicine (formerly the Institute of Medicine), the U.S. health care system spends almost a third of its resources — $750 billion annually — on unnecessary services and inefficient care. New predictive analytics tools promise to reduce waste and improve care by forecasting the likelihood of an event — for example, a patient being readmitted to a hospital or developing a life-threatening infection — and allowing providers to tailor treatments and services accordingly. These tools are now being used across the continuum of care, from disease surveillance to chronic disease prevention to identifying patients who are at risk of deterioration.
Getting Buy-In for Predictive Analytics in Health Care
The lack of adoption is not about technology.
June 20, 2017
Summary.
New predictive analytics tools in health care promise to reduce waste and improve care by forecasting the likelihood of an event — for example, that a patient will be readmitted to hospital or develop a life-threatening infection – and allowing providers to tailor treatments and services accordingly. But despite the tools’ power to improve care, most health care institutions are not yet using them. A study of key figures from leading US health systems, policy makers, and predictive analytics vendors finds that success depends less on the tool itself than on getting buy-in at all levels from the start.
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Accelerate your career with Harvard ManageMentor®. HBR Learning’s online leadership training helps you hone your skills with courses like Change Management. Earn badges to share on LinkedIn and your resume. Access more than 40 courses trusted by Fortune 500 companies.
Change may be the only constant in today's organizations. Here's how to lead through it.