Improving Access & Satisfaction through Machine Learning & Holistic Member Engagement

Improving Access & Satisfaction through Machine Learning & Holistic Member Engagement

San Diego, CA | July 10-11, 2018

Elevating an individual’s perception captured in a survey response is one of the most difficult tasks in any industry. The task is even more challenging when the survey is anonymous, based on randomly selected individuals, and where the “product” is both deeply personal and intangible. That’s the case in healthcare.

High CAHPS ratings starts with having a high-quality healthcare organization, yet CAHPS is also very dependent on the demographic, utilization and disease profile of the population. In this session, Mr. Aminzadeh will discuss approaches to improving overall CAHPS performance while also impacting other critical metrics such as reduction in voluntary disenrollment and improvement in quality.

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