Predicting Healthcare Costs in a Population of Veterans Affairs Beneficiaries Using Diagnosis-Based Risk Adjustment and Self-Reported Health Status

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 R(2), 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 R by 0.007 in the prospective model. The 8 scales reduced the MAPE by 236 US dollars 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

Environmental health · Family medicine · Health care · Political science · Population · Veterans Affairs · Chronic Disease Management Strategies · Healthcare Policy and Management · Medicine · Primary Care and Health Outcomes · Gerontology

• Comparison of the information provided by electronic health records data and a population health survey to estimate prevalence of selected health conditions and multimorbidity

  Open Access•Concepción Violán, Quintí Foguet‐Boreu et al.•BMC Public Health•2013

  Incluir item

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• A Review on Methods of Risk Adjustment and their Use in Integrated Healthcare Systems

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  Incluir item

• Risk Adjustment Using Administrative Data-Based and Survey-Derived Methods for Explaining Physician Utilization

  Lyn M Sibley, Rahim Moineddin et al.•Medical Care•2010

  Incluir item

• The Effect of Complementary and Alternative Medicine Claims on Risk Adjustment

  Bonnie K Lind, Chad Abrams et al.•Medical Care•2006

  Incluir item

• Predicting Healthcare Utilization Using a Pharmacy-based Metric With the WHO’s Anatomic Therapeutic Chemical Algorithm

  Raymond N Kuo, Yaa-Hui Dong et al.•Medical Care•2011

  Incluir item

• Explaining Prescription Drug Use and Expenditures Using the Adjusted Clinical Groups Case-Mix System in the Population of British Columbia, Canada

  Grace E Hanley, Gillian E Hanley et al.•Medical Care•2010

  Incluir item

• Predicting Unplanned Health Care Utilization and Cost

  Suzanne Kinsky, Qingfeng Liang et al.•Medical Care•2021

  Incluir item

• Diagnostic, Pharmacy-Based, and Self-Reported Health Measures in Risk Equalization Models

  Piet Stam, Pieter J A Stam et al.•Medical Care•2010

  Incluir item

• Using the SF-12 Health Status Measure to Improve Predictions of Medical Expenditures

  John A Fleishman, Joel W Cohen et al.•Medical Care•2006

  Incluir item

• The reliability of self-assessed health status

  Open Access•Thomas F Crossley, Steven Kennedy•Journal of Health Economics•2002

  Incluir item

• Evaluating Diagnosis-Based Case-Mix Measures

  Amy K Rosen, Susan Loveland et al.•Medical Care•2001

  Incluir item

• Health Status and Severity of Illness as Predictors of Outcomes in Primary Care

  George R Parkerson, W Eugene Broadhead et al.•Medical Care•1995

  Incluir item

• Health Perceptions of Primary Care Patients and the Influence on Health Care Utilization

  Julia E Connelly, John T Philbrick et al.•Medical Care•1989

  Incluir item

• Performance of the ACG Case-Mix System in Two Canadian Provinces

  Robert J Reid, Leonard Macwilliam et al.•Medical Care•2001

  Incluir item

• Cost Analysis in the Department of Veterans Affairs

  Ralph Swindle, Joan Carles Gomis Corell et al.•Medical Care•1999

  Incluir item

• Risk Adjustment Using Automated Ambulatory Pharmacy Data

  Paul Fishman, Paul A Fishman et al.•Medical Care•2003

  Incluir item

• Differences in Patient Characteristics Between Veterans Administration and Community Hospitals

  Malcom Randall, Kerry E Kilpatrick et al.•Medical Care•1987

  Incluir item

• Multiyear Diagnostic Information from Prior Hospitalizations as a Risk-Adjuster for Capitation Payments

  Leida M Lamers, RENÉ CJA VAN VLIET•Medical Care•1996

  Incluir item

• The MOS 36-Item Short-Form Health Survey (SF-36)

  Colleen A Mchorney, WARE JOHNE et al.•Medical Care•1993

  Incluir item