Evaluating a Model to Predict Primary Care Physician-Defined Complexity in a Large Academic Primary Care Practice-Based Research Network.

ABSTRACT:

Background

Improving the ability to risk-stratify patients is critical for efficiently allocating resources within healthcare systems.

Objective

The purpose of this study was to evaluate a physician-defined complexity prediction model against outpatient Charlson score (OCS) and a commercial risk predictor (CRP).

Design

Using a cohort in which primary care physicians reviewed 4302 of their adult patients, we developed a predictive model for estimated physician-defined complexity (ePDC) and categorized our population using ePDC, OCS and CRP.

Participants

143,372 primary care patients in a practice-based research network participated in the study.

Main measures

For all patients categorized as complex in 2007 by one or more risk-stratification method, we cal

SUBMITTER: Hong CS 

PROVIDER: S-EPMC4636571 | biostudies-literature | 2015 Dec

REPOSITORIES: biostudies-literature