DOCUMENTS

papers

Morbidity trajectories as predictors of utilization: multi-year disease patterns in Taiwan’s national health insurance program

Published: October 1, 2011
Category: Papers
Authors: Chang HY, Clark JM, Weiner JP
Country: Taiwan
Language: null
Type: Care Management
Settings: Academic, Health Plan

Med Care 49:918-923.

Department of Health Policy and Management, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA

BACKGROUND: Little is known about how morbidity levels progress over time and the implications of these morbidity trajectories for healthcare utilization.

OBJECTIVES: To identify and compare characteristics of people in different morbidity trajectories and to evaluate how morbidity trajectories impact the performance of diagnostic risk-adjustment models.

RESEARCH DESIGN: Morbidity trajectories were derived from 3-year (2002 to 2004) of claims from a national insurance system. These trajectories, with or without 2004 claims-based risk adjusters developed from the Adjusted Clinical Group case-mix system, were used to explain medical utilization in 2005.

SUBJECTS: A random sample of Taiwanese National Health Insurance beneficiaries continuously enrolled from 2002 to 2005 (n=147,892).

MEASURES: Adjusted R of 5 types of healthcare expenditures.

RESULTS: On the basis of naturally occurring patterns, we identified 6 morbidity trajectory groups. People assigned to different trajectory groups have distinct demographics and medical utilization. The effect of adding morbidity trajectory indicators differed substantially by the comprehensiveness of baseline risk-adjustment models: the increase in adjusted R ranged from 0.3% in the most comprehensive model to 5.7% in the demographics model.

CONCLUSIONS: A simple morbidity trajectory classification over a 3-year period is almost as powerful a predictor of prospective medical utilization as more comprehensive baseline risk adjusters. It may be unnecessary to construct longitudinal morbidity trajectories if a comprehensive baseline model was adopted, especially for healthcare systems without the stability of continuous enrollment.

PMID: 21577165

Resource Utilization,Predictive Risk Modeling,Morbidity Patterns,United States,Demography,Gender,Forecasting,Health Services/utilization,Linear Models,Longitudinal Studies,Risk Adjustment,Taiwan Epidemiology

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