An approach to predicting patient experience through machine learning and social network analysis.

ABSTRACT:

Objective

Improving the patient experience has become an essential component of any healthcare system's performance metrics portfolio. In this study, we developed a machine learning model to predict a patient's response to the Hospital Consumer Assessment of Healthcare Providers and Systems survey's "Doctor Communications" domain questions while simultaneously identifying most impactful providers in a network.

Materials and methods

This is an observational study of patients admitted to a single tertiary care hospital between 2016 and 2020. Using machine learning algorithms, electronic health record data were used to predict patient responses to Hospital Consumer Assessment of Healthcare Providers and Systems survey questions in the doctor domain, and patients who are at risk

SUBMITTER: Bari V 

PROVIDER: S-EPMC7727354 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature