title: Morbidity trajectories as predictors of utilization: multi-year disease patterns in Taiwan's national health insurance program.
abstract: BACKGROUND
  Little is known about how morbidity levels progress over time and the implications of these morbidity trajectories for healthcare utilization.
  
  
  OBJECTIVE
  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.
  
  
  METHODS
  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.
  
  
  METHODS
  A random sample of Taiwanese National Health Insurance beneficiaries continuously enrolled from 2002 to 2005 (n=147,892).
  
  
  METHODS
  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.
authors.affiliation: Department of Health Policy and Management, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD 21205, USA. hchang2@jhsph.edu
authors.forename: Hsien-Yen
authors.initials: HY
authors.lastname: Chang
authors.forename: Jeanne M
authors.initials: JM
authors.lastname: Clark
authors.forename: Jonathan P
authors.initials: JP
authors.lastname: Weiner
mesh_terms: D003710:Demography; D005260:Female; D005544:Forecasting; D005102:Health Expenditures; D006296:Health Services / Q000706:statistics & numerical data; D006801:Humans; D016014:Linear Models; D008137:Longitudinal Studies; D008297:Male; D009017:Morbidity / Q000639:trends*; D009313:National Health Programs / Q000706:statistics & numerical data*; D020379:Risk Adjustment; D013624:Taiwan / Q000453:epidemiology; D014600:Utilization Review