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Measuring Health-Related Quality of Life

Gordon H. Guyatt, MD; David H. Feeny, PhD; and Donald L. Patrick, PhD, MSPH
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From McMaster University, Hamilton, Ontario, Canada; and the University of Washington, Seattle, Washington. Requests for Reprints: Gordon H. Guyatt, MD, Room 2C12, McMaster University Health Sciences Centre, 1200 Main Street West, Hamilton, Ontario, Canada L8N 3Z5. Grant Support: Dr. Guyatt is a Career Scientist of the Ontario Ministry of Health.


Copyright 2004 by the American College of Physicians


Ann Intern Med. 1993;118(8):622-629. doi:10.7326/0003-4819-118-8-199304150-00009
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Clinicians and policymakers are recognizing the importance of measuring health-related quality of life (HRQL) to inform patient management and policy decisions. Self- or interviewer-administered questionnaires can be used to measure cross-sectional differences in quality of life between patients at a point in time (discriminative instruments) or longitudinal changes in HRQL within patients during a period of time (evaluative instruments). Both discriminative and evaluative instruments must be valid (really measuring what they are supposed to measure) and have a high ratio of signal to noise (reliability and responsiveness, respectively). Reliable discriminative instruments are able to reproducibly differentiate between persons. Responsive evaluative measures are able to detect important changes in HRQL during a period of time, even if those changes are small. Health-related quality of life measures should also be interpretablethat is, clinicians and policymakers must be able to identify differences in scores that correspond to trivial, small, moderate, and large differences.

Two basic approaches to quality-of-life measurement are available: generic instruments that provide a summary of HRQL; and specific instruments that focus on problems associated with single disease states, patient groups, or areas of function. Generic instruments include health profiles and instruments that generate health utilities. The approaches are not mutually exclusive. Each approach has its strengths and weaknesses and may be suitable for different circumstances. Investigations in HRQL have led to instruments suitable for detecting minimally important effects in clinical trials, for measuring the health of populations, and for providing information for policy decisions.

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