Predicting healthcare costs in a population of veterans affairs beneficiaries using diagnosis-based risk adjustment and self-reported health status

Kenneth Pietz, Carol M. Ashton, Mary McDonell, Nelda Wray

Research output: Contribution to journalReview article

32 Scopus citations

Abstract

Background: Many Healthcare organizations use diagnosis-based risk adjustment systems for predicting costs. Health self-report may add information not contained in a diagnosis-based system but is subject to incomplete response. Objective: The objective of this study was to evaluate the added predictive power of health self-report in combination with a diagnosis-based risk adjustment system in concurrent and prospective models of healthcare cost. Research Design: This was a cohort study using Department of Veterans Affairs (VA) administrative databases. We tested the predictive ability of the Adjusted Clinical Group (ACG) methodology and the added value of SF-36V (short form functional status for veterans) results. Linear regression models were compared using R2, mean absolute prediction error (MAPE), and predictive ratio. Subjects: Subjects were 35,337 VA beneficiaries at 8 VA medical centers during fiscal year (FY) 1998 who voluntarily completed an SF-36V survey. Measures: Outcomes were total FY 1998 and FY 1999 cost. Demographics and ACG-based Adjusted Diagnostic Groups (ADGs) with and without 8 SF-36V multiitem scales and the Physical Component Score and Mental Component Score were compared. Results: The survey response rate was 45%. Adding the 8 scales to ADGs and demographics increased the crossvalidated R2 by 0.007 in the prospective model. The 8 scales reduced the MAPE by $236 among patients in the upper 10% of FY 1999 cost. Conclusions: The limited added predictive power of health self-report to a diagnosis-based risk adjustment system should be weighed against the cost of collecting these data. Adding health self-report data may increase predictive accuracy in high-cost patients.

Original languageEnglish (US)
Pages (from-to)1027-1035
Number of pages9
JournalMedical Care
Volume42
Issue number10
DOIs
StatePublished - Oct 2004

Keywords

  • Case-mix
  • Health status
  • Risk adjustment

ASJC Scopus subject areas

  • Nursing(all)
  • Public Health, Environmental and Occupational Health
  • Health(social science)
  • Health Professions(all)

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