Assessing the Value of Unsupervised Clustering in Predicting Persistent High Health Care Utilizers: Retrospective Analysis of Insurance Claims Data.

ABSTRACT:

Background

A high proportion of health care services are persistently utilized by a small subpopulation of patients. To improve clinical outcomes while reducing costs and utilization, population health management programs often provide targeted interventions to patients who may become persistent high users/utilizers (PHUs). Enhanced prediction and management of PHUs can improve health care system efficiencies and improve the overall quality of patient care.

Objective

The aim of this study was to detect key classes of diseases and medications among the study population and to assess the predictive value of these classes in identifying PHUs.

Methods

This study was a retrospective analysis of insurance claims data of patients from the Johns Hopkins Health Care system. We

SUBMITTER: Ramachandran R 

PROVIDER: S-EPMC8663459 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature