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US Valuation of the EQ-5D Health States: Development and Testing of the D1 Valuation Model
Abstract
PURPOSE: The EQ-5D is a brief, multiattribute, preference-based health status measure. This article describes the development of a statistical model for generating US population-based EQ-5D preference weights. METHODS: A multistage probability sample was selected from the US adult civilian noninstitutional population. Respondents valued 13 of 243 EQ-5D health states using the time trade-off (TTO) method. Data for 12 states were used in econometric modeling. The TTO valuations were linearly transformed to lie on the interval [-1, 1]. Methods were investigated to account for interaction effects caused by having problems in multiple EQ-5D dimensions. Several alternative model specifications (eg, pooled least squares, random effects) also were considered. A modified split-sample approach was used to evaluate the predictive accuracy of the models. All statistical analyses took into account the clustering and disproportionate selection probabilities inherent in our sampling design. RESULTS: Our D1 model for the EQ-5D included ordinal terms to capture the effect of departures from perfect health as well as interaction effects. A random effects specification of the D1 model yielded a good fit for the observed TTO data, with an overall R of 0.38, a mean absolute error of 0.025, and 7 prediction errors exceeding 0.05 in absolute magnitude. CONCLUSIONS: The D1 model best predicts the values for observed health states. The resulting preference weight estimates represent a significant enhancement of the EQ-5D's utility for health status assessment and economic analysis in the US.
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Citations
Cites
Specification Tests in Econometrics
Hausman, J. A. (1978) · Econometrica · doi:10.2307/1913827 · Cited by 18,820
EuroQol: a new facility for the measurement of health-related quality of life
(1990) · Health Policy · doi:10.1016/0168-8510(90)90421-9 · Cited by 15,736
On the Variances of Asymptotically Normal Estimators from Complex Surveys
Binder, D. A. (1983) · International Statistical Review / Revue Internationale de Statistique · doi:10.2307/1402588 · Cited by 982
Furlong, W. J., Feeny, D. H., Torrance, G. W., & Barr, R. D. (2001) · Annals of Medicine · doi:10.3109/07853890109002092 · Cited by 751
Comparison of the EQ-5D and SF-12 Health Surveys in a General Population Survey in Alberta, Canada
Johnson, J. A., & Pickard, A. S. (2000) · Medical Care · doi:10.1097/00005650-200001000-00013 · Cited by 274
Self-citation
Cited by
Hays, R. D., Bjorner, J. B., Revicki, D. A., Spritzer, K. L., & Cella, D. (2009) · Quality of Life Research · doi:10.1007/s11136-009-9496-9 · Cited by 1,957
Patients’ expectations about effects of chemotherapy for advanced cancer
Weeks, J. C., Catalano, P. J., Cronin, A., Finkelman, M. D., Mack, J. W., Keating, N. L., & Schrag, D. (2012) · New England Journal of Medicine · doi:10.1056/nejmoa1204410 · Cited by 1,149
Dutch Tariff for the Five-Level Version of EQ-5D
M. Versteegh, M., M. Vermeulen, K., M. A. A. Evers, S., de Wit, G. A., Prenger, R., & A. Stolk, E. (2016) · Value in Health · doi:10.1016/j.jval.2016.01.003 · Cited by 1,113
Physical Complications in Acute Lung Injury Survivors: A Two-Year Longitudinal Prospective Study
Fan, E., Dowdy, D. W., Colantuoni, E., Mendez-Tellez, P. A., Sevransky, J. E., Shanholtz, C., Dennison Himmelfarb, C. R., Desai, S. V., Ciesla, N., Herridge, M. S., et al. (2014) · Critical Care Medicine · doi:10.1097/ccm.0000000000000040 · Cited by 615
Lee, Y.-K., Nam, H.-S., Chuang, L.-H., Kim, K.-Y., Yang, H.-K., Kwon, I.-S., Kind, P., Kweon, S.-S., & Kim, Y.-T. (2009) · Value in Health · doi:10.1111/j.1524-4733.2009.00579.x · Cited by 474
Luo, N., Johnson, J. A., Shaw, J. W., Feeny, D., & Coons, S. J. (2005) · Medical Care · doi:10.1097/01.mlr.0000182493.57090.c1 · Cited by 383
Self-citationA National Catalog of Preference-Based Scores for Chronic Conditions in the United States
Sullivan, P. W., Lawrence, W. F., & Ghushchyan, V. (2005) · Medical Care · doi:10.1097/01.mlr.0000172050.67085.4f · Cited by 388
Reynolds, M. R., Magnuson, E. A., Wang, K., Thourani, V. H., Williams, M., Zajarias, A., Rihal, C. S., Brown, D. L., Smith, C. R., Leon, M. B., et al. (2012) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2012.03.075 · Cited by 295
Quality of Life after PCI with Drug-Eluting Stents or Coronary-Artery Bypass Surgery
Cohen, D. J., Van Hout, B., Serruys, P. W., Mohr, F. W., Macaya, C., den Heijer, P., Vrakking, M. M., Wang, K., Mahoney, E. M., Audi, S., et al. (2011) · New England Journal of Medicine · doi:10.1056/nejmoa1001508 · Cited by 288
Ahmed, S., Berzon, R. A., Revicki, D. A., Lenderking, W. R., Moinpour, C. M., Basch, E., Reeve, B. B., & Wu, A. W. (2012) · Medical Care · doi:10.1097/mlr.0b013e318268aaff · Cited by 272
Sullivan, P. W., & Ghushchyan, V. (2006) · Medical Decision Making · doi:10.1177/0272989x06290496 · Cited by 249
Consequences of false-positive screening mammograms
Tosteson, A. N. A., Fryback, D. G., Hammond, C. S., Hanna, L. G., Grove, M. R., Brown, M., Wang, Q., Lindfors, K., & Pisano, E. D. (2014) · JAMA Internal Medicine · doi:10.1001/jamainternmed.2014.981 · Cited by 217
Italian population-based values of EQ-5D health states
Scalone, L., Cortesi, P. A., Ciampichini, R., Belisari, A., D’Angiolella, L. S., Cesana, G., & Mantovani, L. G. (2013) · Value in Health · doi:10.1016/j.jval.2013.04.008 · Cited by 145
Combining multiple imputation and bootstrap in the analysis of cost‐effectiveness trial data
Brand, J., van Buuren, S., le Cessie, S., & van den Hout, W. (2019) · Statistics in Medicine · doi:10.1002/sim.7956 · Cited by 131
Physical Therapy Interventions for Knee Pain Secondary to Osteoarthritis: A Systematic Review
Wang, S.-Y., Olson-Kellogg, B., Shamliyan, T. A., Choi, J.-Y., Ramakrishnan, R., & Kane, R. L. (2012) · Annals of Internal Medicine · doi:10.7326/0003-4819-157-9-201211060-00007 · Cited by 108
Schackman, B. R., Leff, J. A., Polsky, D., Moore, B. A., & Fiellin, D. A. (2012) · Journal of General Internal Medicine · doi:10.1007/s11606-011-1962-8 · Cited by 100
Sun, V., Dumitra, S., Ruel, N., Lee, B., Melstrom, L., Melstrom, K., Woo, Y., Sentovich, S., Singh, G., & Fong, Y. (2017) · JAMA Surgery · doi:10.1001/jamasurg.2017.1519 · Cited by 98
Matcham, F., Rayner, L., Hutton, J., Monk, A., Steel, C., & Hotopf, M. (2014) · Clinical Psychology Review · doi:10.1016/j.cpr.2014.01.005 · Cited by 85
McCoy, R. G., Van Houten, H. K., Ziegenfuss, J. Y., Shah, N. D., Wermers, R. A., & Smith, S. A. (2013) · Endocrine Practice · doi:10.4158/ep12382.or · Cited by 76
Rangaraju, S., Frankel, M., & Jovin, T. G. (2015) · Interventional Neurology · doi:10.1159/000443801 · Cited by 69
The Economic Value of Improving the Health of Disadvantaged Americans
Schoeni, R. F., Dow, W. H., Miller, W. D., & Pamuk, E. R. (2011) · American Journal of Preventive Medicine · doi:10.1016/j.amepre.2010.09.032 · Cited by 55
Kaplan, R. M., Tally, S., Hays, R. D., Feeny, D., Ganiats, T. G., Palta, M., & Fryback, D. G. (2011) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2010.04.010 · Cited by 55
Cost-effectiveness of telehealth with remote patient monitoring for postpartum hypertension
Niu, B., Mukhtarova, N., Alagoz, O., & Hoppe, K. (2022) · The Journal of Maternal-Fetal & Neonatal Medicine · doi:10.1080/14767058.2021.1956456 · Cited by 52
Kelkar, A. H., Cliff, E. R. S., Jacobson, C. A., Abel, G. A., Dijk, S. W., Krijkamp, E. M., Redd, R., Zurko, J. C., Hamadani, M., Hunink, M. G. M., et al. (2023) · Annals of Internal Medicine · doi:10.7326/m22-2276 · Cited by 31
Lacy, B., Piotrowski, H. J., Dewey, R. B., & Husain, M. M. (2023) · Clinical Parkinsonism & Related Disorders · doi:10.1016/j.prdoa.2022.100180 · Cited by 27
“The EQ-5D is a brief self-complete health-status measure assessing the degree to which participants encounter difficulties with mobility, self-care, usual activities, pain/discomfort, and anxiety/depression [27].”
BackgroundMaking Sense of Recent Cost-of-Foodborne-Illness Estimates
Hoffmann, S., Anekwe, T. D., Hoffmann, S., & Anekwe, T. D. (2013) · Unknown · doi:10.22004/ag.econ.262123 · Cited by 23
Differences Between Individual and Societal Health State Valuations: Any Link With Personality?
Chapman, B. P., Franks, P., Duberstein, P. R., & Jerant, A. (2009) · Medical Care · doi:10.1097/mlr.0b013e3181a8112e · Cited by 20
Rozenbaum, M. H., Large, S., Bhambri, R., Stewart, M., Young, R., Doornewaard, A. V., Dasgupta, N., Masri, A., & Nativi-Nicolau, J. (2021) · Journal of Comparative Effectiveness Research · doi:10.2217/cer-2021-0071 · Cited by 19
Richards, C., Iosifescu, D. V., Mago, R., Sarkis, E., Reynolds, J., Geibel, B., & Dauphin, M. (2017) · Journal of Psychopharmacology · doi:10.1177/0269881117722998 · Cited by 14
Karim, J. N., Campbell, H., Pandya, P., Wilson, E. C. F., Alfirevic, Z., Chudleigh, T., Duff, E., Fisher, J., Goodman, H., Hinton, L., et al. (2025) · Health Technology Assessment · doi:10.3310/nltp7102 · Cited by 5
Chattot, C., Deffieux, X., Lucot, J.-P., Fritel, X., & Fauconnier, A. (2020) · International Urogynecology Journal · doi:10.1007/s00192-019-03953-6 · Cited by 4
Metadata
- Authors
- Shaw, J. W., Johnson, J. A., & Coons, S. J.
- Venue
- Medical Care
- Published
- 2005-03
- Volume
- 43
- Issue
- 3
- Pages
- 203-220
- ISSN
- 0025-7079 (ISSN-L)
- OpenAlex
- W2096782143
- Cited by
- 1,274
- References
- 5
- FWCI
- 116.32
- Type
- journal article
- Language
- en
- Open access
- closed
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