Using information on clinical conditions to predict high-cost patients.

ABSTRACT:

Objective

To compare the ability of different models to predict prospectively whether someone will incur high medical expenditures.

Data source

Using nationally representative data from the Medical Expenditure Panel Survey (MEPS), prediction models were developed using cohorts initiated in 1996-1999 (N=52,918), and validated using cohorts initiated in 2000-2003 (N=61,155).

Study design

We estimated logistic regression models to predict being in the upper expenditure decile in Year 2 of a cohort, based on data from Year 1. We compared a summary risk score based on diagnostic cost group (DCG) prospective risk scores to a count of chronic conditions and indicators for 10 specific high-prevalence chronic conditions. We examined whether self-rated health and functional lim

SUBMITTER: Fleishman JA 

PROVIDER: S-EPMC2838159 | biostudies-literature | 2010 Apr

REPOSITORIES: biostudies-literature