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Assessing CAHPS Surveys, Patient Satisfaction with Machine Learning

Written by SH
  • Sara Heath

“High patient satisfaction scores do not solely depend upon clinicians executing their job functions well. High scores also require clinicians and health plans to understand how their jobs meet the unique needs of different patient populations.”

A machine learning approach to understanding CAHPS survey responses may help health plans and organizations make targeted approaches to improving patient satisfaction, according to a recent report from Decision Point.

The report, “Impacting Perceptions of Healthcare Access & Satisfaction,” is a patient engagement playbook that guides insurance plans through using machine learning techniques that link certain parts of CAHPS surveys with different health system’s functions.

High patient satisfaction scores do not solely depend upon clinicians executing their job functions well. High scores also require clinicians and health plans to understand how their jobs meet the unique needs of different patient populations.

“High CAHPS ratings starts with having a high-quality healthcare organization, with excellent access to care and meaningful processes in place to promote satisfaction,” the playbook noted. “Even with all this, however, CAHPS is so dependent on the demographic, utilization and disease profile of the population, that having a high quality organization is simply not enough.”…