{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T00:56:56Z","timestamp":1772067416929,"version":"3.50.1"},"reference-count":32,"publisher":"SAGE Publications","issue":"2","license":[{"start":{"date-parts":[[2004,3,1]],"date-time":"2004-03-01T00:00:00Z","timestamp":1078099200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Med Decis Making"],"published-print":{"date-parts":[[2004,3]]},"abstract":"<jats:p> Purpose. To predict the EuroQoL EQ-5D utility index from the SF-12 Health Survey for a US national sample of adults. Methods. The authors used the 2000 Medical Expenditure Panel Survey to examine the relationship between instruments. Linear regression was used to predict EQ-5D scores from Physical Component Summary (PCS) and Mental Component Summary (MCS) scores of the SF-12. A prediction model was derived in one half of the sample and validated in the other half. Results. Complete responses to both measures were available for 14,580 adults; 7313 (50.2%) surveys were used for the derivation set. The 2-variable model predicted 61% of the variance in EQ-5D scores and provided reasonable ability to predict mean EQ-5D scores from mean PCS and MCS scores. Confidence intervals are dependent on sample size and variance of PCS and MCS scores. Conclusions. EQ-5D scores can be reasonably predicted from the SF-12. This model allows researchers to estimate utility data for use in decision and cost-utility analyses. <\/jats:p>","DOI":"10.1177\/0272989x04264015","type":"journal-article","created":{"date-parts":[[2004,4,22]],"date-time":"2004-04-22T01:01:24Z","timestamp":1082595684000},"page":"160-169","source":"Crossref","is-referenced-by-count":81,"title":["Predicting EuroQoL EQ-5D Preference Scores from the SF-12 Health Survey in a Nationally Representative Sample"],"prefix":"10.1177","volume":"24","author":[{"given":"William F.","family":"Lawrence","sequence":"first","affiliation":[{"name":"Center for Outcomes and Evidence, Agency for Healthcare Research and Quality, Rockville, Maryland"}]},{"given":"John A.","family":"Fleishman","sequence":"additional","affiliation":[{"name":"Center for Financing, Access, and Cost Trends, Agency for Healthcare Research and Quality, Rockville, Maryland"}]}],"member":"179","published-online":{"date-parts":[[2004,3,1]]},"reference":[{"key":"atypb1","doi-asserted-by":"crossref","unstructured":"1. Gold MR, Siegel JE, Russell LB, Weinstein MC, eds. Cost-Effectiveness in Health and Medicine. New York: Oxford University Press; 1996.","DOI":"10.1093\/oso\/9780195108248.001.0001"},{"key":"atypb2","doi-asserted-by":"crossref","unstructured":"2. Bell CM, Chapman RH, Stone PW, Sandberg EA, Neumann PJ. An off-the-shelf help list: a comprehensive catalog of preference scores from published cost-utility analyses. Med Decis Making. 2001;21(4):288-294.","DOI":"10.1177\/0272989X0102100404"},{"key":"atypb3","doi-asserted-by":"publisher","DOI":"10.1097\/00005650-200006000-00004"},{"key":"atypb4","unstructured":"4. Kind P. The EuroQoL instrument: an index of health-related quality of life. In: Spilker B, ed. Quality of Life and Pharmacoeconomics in Clinical Trials. 2nd ed. Philadelphia: Lippincott-Raven; 1996."},{"key":"atypb5","doi-asserted-by":"publisher","DOI":"10.3109\/07853890109002092"},{"key":"atypb6","unstructured":"6. Feeny DH, Torrance GW, Furlong WJ. Health Utilities Index. 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