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

Overview

Journal Med Decis Making

Publisher Sage Publications

Date 2006 Jul 21

PMID 16855129

Citations 297

Authors

Patrick W Sullivan

Vahram Ghushchyan

Affiliations

Soon will be listed here.

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, community-based 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.

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References

Bell C, Chapman R, Stone P, Sandberg E, Neumann P . An off-the-shelf help list: a comprehensive catalog of preference scores from published cost-utility analyses. Med Decis Making. 2001; 21(4):288-94. DOI: 10.1177/0272989X0102100404. View

Hwang W, Weller W, Ireys H, Anderson G . Out-of-pocket medical spending for care of chronic conditions. Health Aff (Millwood). 2002; 20(6):267-78. DOI: 10.1377/hlthaff.20.6.267. View

Feeny D, Furlong W, Torrance G, Goldsmith C, Zhu Z, DePauw S . Multiattribute and single-attribute utility functions for the health utilities index mark 3 system. Med Care. 2002; 40(2):113-28. DOI: 10.1097/00005650-200202000-00006. View

Austin P . Bayesian extensions of the Tobit model for analyzing measures of health status. Med Decis Making. 2002; 22(2):152-62. DOI: 10.1177/0272989X0202200212. View

Wu A, Jacobson K, Frick K, Clark R, Revicki D, Freedberg K . Validity and responsiveness of the euroqol as a measure of health-related quality of life in people enrolled in an AIDS clinical trial. Qual Life Res. 2002; 11(3):273-82. DOI: 10.1023/a:1015240103565. View

Macran S, Weatherly H, Kind P . Measuring population health: a comparison of three generic health status measures. Med Care. 2003; 41(2):218-31. DOI: 10.1097/01.MLR.0000044901.57067.19. View

Luo N, Chew L, Fong K, Koh D, Ng S, Yoon K . A comparison of the EuroQol-5D and the Health Utilities Index mark 3 in patients with rheumatic disease. J Rheumatol. 2003; 30(10):2268-74. View

Llewellyn-Thomas H, Sutherland H, Tibshirani R, Ciampi A, Till J, Boyd N . The measurement of patients' values in medicine. Med Decis Making. 1982; 2(4):449-62. DOI: 10.1177/0272989X8200200407. View

Berkanovic E, Telesky C . Mexican-American, black-American and white-American differences in reporting illnesses, disability and physician visits for illnesses. Soc Sci Med. 1985; 20(6):567-77. DOI: 10.1016/0277-9536(85)90395-8. View

10.

Torrance G . Measurement of health state utilities for economic appraisal. J Health Econ. 1986; 5(1):1-30. DOI: 10.1016/0167-6296(86)90020-2. View

11.

Fryback D, Dasbach E, Klein R, Klein B, Dorn N, Peterson K . The Beaver Dam Health Outcomes Study: initial catalog of health-state quality factors. Med Decis Making. 1993; 13(2):89-102. DOI: 10.1177/0272989X9301300202. View

12.

Sullivan P, Lawrence W, Ghushchyan V . A national catalog of preference-based scores for chronic conditions in the United States. Med Care. 2005; 43(7):736-49. DOI: 10.1097/01.mlr.0000172050.67085.4f. View

13.

Shaw J, Johnson J, Coons S . US valuation of the EQ-5D health states: development and testing of the D1 valuation model. Med Care. 2005; 43(3):203-20. DOI: 10.1097/00005650-200503000-00003. View

14.

Glick H, Polsky D, Willke R, Schulman K . A comparison of preference assessment instruments used in a clinical trial: responses to the visual analog scale from the EuroQol EQ-5D and the Health Utilities Index. Med Decis Making. 1999; 19(3):265-75. DOI: 10.1177/0272989X9901900305. View

15.

Gold M, Franks P, McCoy K, Fryback D . Toward consistency in cost-utility analyses: using national measures to create condition-specific values. Med Care. 1998; 36(6):778-92. DOI: 10.1097/00005650-199806000-00002. View

16.

Richardson J . Cost utility analysis: what should be measured?. Soc Sci Med. 1994; 39(1):7-21. DOI: 10.1016/0277-9536(94)90162-7. View

17.

Stewart A . Health-related quality-of-life assessments in diverse population groups in the United States. Med Care. 2000; 38(9 Suppl):II102-24. View

18.

Tengs T, Wallace A . One thousand health-related quality-of-life estimates. Med Care. 2000; 38(6):583-637. DOI: 10.1097/00005650-200006000-00004. View

19.

Bosch J, Hunink M . Comparison of the Health Utilities Index Mark 3 (HUI3) and the EuroQol EQ-5D in patients treated for intermittent claudication. Qual Life Res. 2001; 9(6):591-601. DOI: 10.1023/a:1008929129537. View