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Preference-Based EQ-5D Index Scores for Chronic Conditions in the United States

Author

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  • Patrick W. Sullivan

    (University of Colorado Department of Economics, Boulder, and University of Colorado School of Pharmacy, Pharmaceutical Outcomes Research Program; Patrick.Sullivan@UCHSC.edu.)

  • Vahram Ghushchyan

    (University of Colorado Department of Economics, Boulder, and University of Colorado School of Pharmacy, Pharmaceutical Outcomes Research Program)

Abstract

Background . The Panel on Cost-Effectiveness in Health and Medicine has called for an “off-the-shelf†catalogue of nationally representative, community-based preference scores for health states, illnesses, and conditions. A previous review of cost-effectiveness analyses found that 77% did not incorporate community-based preferences, and 33% used arbitrary expert or author judgment. These results highlight the necessity of making a wide array of appropriate, community-based estimates more accessible to cost-effectiveness researchers. Objective . To provide nationally representative EQ-5D index scores for chronic ICD-9 codes. Methods . The nationally representative Medical Expenditure Panel Survey (MEPS) was pooled (2000–2002) to create a data set of 38,678 adults. Ordinary least squares (OLS), Tobit, and censored least absolute deviations (CLAD) regression methods were used to estimate the marginal disutility of each condition, controlling for age, comorbidity, gender, race, ethnicity, income, and education. Results . Most chronic conditions, age, comorbidity, income, and education were highly statistically significant predictors of EQ-5D index scores. Homoskedasticity and normality assumptions were rejected, suggesting only CLAD estimates are theoretically unbiased. The magnitude and statistical significance of coefficients varied by analytic method. OLS and Tobit coefficients were on average 60% and 143% greater than CLAD, respectively. The marginal disutility of 95 chronic ICD-9 codes as well as unadjusted mean, median, and 25th and 75th percentiles are reported. Conclusion . This research provides nationally representative, communitybased EQ-5D index scores associated with a wide variety of chronic ICD-9 codes that can be used to estimate quality-adjusted life-years in cost-effectiveness analyses.

Suggested Citation

  • Patrick W. Sullivan & Vahram Ghushchyan, 2006. "Preference-Based EQ-5D Index Scores for Chronic Conditions in the United States," Medical Decision Making, , vol. 26(4), pages 410-420, July.
    • Handle: RePEc:sae:medema:v:26:y:2006:i:4:p:410-420
    DOI: 10.1177/0272989X06290495
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    References listed on IDEAS

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    1. Richardson, J., 1994. "Cost utility analysis: What should be measured?," Social Science & Medicine, Elsevier, vol. 39(1), pages 7-21, July.
    2. Torrance, George W., 1986. "Measurement of health state utilities for economic appraisal : A review," Journal of Health Economics, Elsevier, vol. 5(1), pages 1-30, March.
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