Health related quality of life: A comparison of indices derived from health status questionnaires.

摘要

It is often important to characterize the health of a population using single index numbers in order to compare the average health of groups at one point in time, or to track the change in health over time. If health is measured using self-report surveys where results are reported as scores in several domains and/or persons who die are excluded, a method to convert the scores to one index would be useful.; I used responses to health status surveys to (1) compare ten methods to convert the SF-36 to a preference-weighted index (PRF), (2) expand an approach to transform health status measures to the probability of being healthy in the future, PHF, to include a full age range and gender and (3) calculate projected years of healthy life (YHL), conditional on starting age and health.; Data for the PRF comparison came from over 20,000 respondents in the ACQUIP project, a quality improvement trial conducted in Veterans Health Administration settings across the country. For the PHF and YHL projections, I used over 221,000 year-apart measures of health status from the Medical Expenditure Panel Survey (MEPS) of the U.S. non-institutionalized civilian population.; The results confirmed that the PRF based transformations are very method dependent with different values obtained for the same persons. Mean values for each transformation are provided, with adjustments for age, gender, socio-economic status and health problems. Criteria are suggested for selecting among the approaches. I provide equations to convert four health status variables to the PHF by age and gender, and confirmed equations previously published for persons over 65 years old. Finally, I provide YHL projections for persons at ten year age intervals, conditional on starting health. Women have more expected years of life, but also more sick years than men.; This research confirms, with caution, the construct validity of two approaches to transforming health status variables to an index value that includes death. The second approach allows one to project health prospects for all persons in a cohort over time, not just those who survive, conditional on their level of health at baseline.