NIOSHTIC-2 Publications Search

Quality-of-life weights for the US population: self-reported health status and priority health conditions, by demographic characteristics.

Nyman JA; Barleen NA; Dowd BE; Russell DW; Coons SJ; Sullivan PW

Med Care 2007 Jul; 45(7):618-628

https://doi.org/10.1097/mlr.0b013e31803dce05

20037550

BACKGROUND: Many of the large ongoing national surveys of the US population contain a question that asks for the respondent's self-reported health status: "excellent," "very good," "good," "fair," or "poor." These surveys could be used to conduct cost-utility analyses of health care policies, treatments or other interventions if quality-of-life (QOL) weights for the self-reported health statuses were also available. OBJECTIVE: The objective of this study was to produce nationally representative QOL weights for self-reported health status and for 10 "priority" health conditions, by a series of demographic variables. RESEARCH DESIGN: The Medical Expenditure Panel Survey contains the questions from the EQ-5D health status measure. A recent study has calculated time-trade-off-derived QOL weights corresponding to the EQ-5D health states for a large sample of Americans. We use these data to construct QOL weights for the 5 self-reported health status categories and 10 priority health conditions, by a series of demographic variables. RESULTS: Mean and median QOL weights were produced for self-reported health status, the 10 priority health conditions, and the demographic variables. We also report mean QOL weights for the self-reported health state and priority health conditions, by the demographic variables. Finally, ordinary least squares and censored least absolute deviation regression equations were used to estimate adjusted QOL weights for these variables. CONCLUSIONS: By providing nationally representative QOL weights for self-reported health status and 10 priority health conditions, by demographic variable, we have facilitated the use of large national surveys for conducting cost-utility analysis and increased their value to researchers and policy makers.

Environmental-factors; Epidemiology; Exposure-assessment; Exposure-levels; Exposure-methods; Health-standards; Health-surveys; Mathematical-models; Medical-care; Medical-services; Medical-surveys; Qualitative-analysis; Quantitative-analysis; Questionnaires; Risk-analysis; Risk-factors; Standards; Statistical-analysis; Surveillance-programs; Demographic-characteristics; Author Keywords: quality-of-life; cost-effectiveness analysis; cost-utility analysis; preference weights; economic evaluation

John A. Nyman, PhD, Division of Health Policy and Management, School of Public Health, University of Minnesota, 420 Delaware St. SE, Box 729, Minneapolis, MN 55455-0392

MDLCBD

20070701

Journal Article

nyman001@umn.edu

Grant

2007

Grant-Number-T42-OH-008434

7

0025-707

Medical Care

MN; IA; AZ; CO

University of Minnesota Twin Cities