Data-Driven Decision Making in Healthcare Systems


September 27, 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.