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Data-Driven Decision Making in Healthcare Systems

Duration  00:11:07

Date recorded  27 September 2011

Mohsen Bayati of Stanford University explains how machine learning could and is being examined and used to determine ways to make health care more cost-effective. One example is patient readmission rates, with the most common occurrences in from past studies being from elderly and Medicare patients. A variety of reasons persist, but the surprising fact is many of these readmissions could have been avoided with a small amount of preventive care in the first place. Medication mismanagement is among the top reasons, and heart failure also is listed. A patient’s lack of access to care outside of the hospital is also a major factor for readmissions.

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