Precision of Health-Related Quality-of-Life Data Compared with Other Clinical Measures

Published in: Mayo Clinic Proceedings, v. 82, no. 10, Oct. 2007, p. 1244-1254

Posted on RAND.org on January 01, 2007

by Elizabeth A. Hahn, David Cella, Olivier Chassany, Diane L. Fairclough, Gilbert Y. Wong, Ron D. Hays

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To many clinicians, the assessment of health-related quality of life (HRQL) seems more art than science. This belief is due in part to the lack of formal training available to clinicians regarding HRQL measurement and interpretation. When HRQL is used systematically, it has been shown to improve patient-physician communication, clinical decision making, and satisfaction with care. Nevertheless, clinicians rarely use formal HRQL data in their practices. One major reason is unfamiliarity with the interpretation and potential utility of the data. This unfamiliarity causes a lack of appreciation for the reliability of data generated by formal HRQL assessment and a tendency to regard HRQL data as having insufficient precision for individual use. This article discusses HRQL in the larger context of health indicators and health outcome measurement and is targeted to the practicing clinician who has not had the opportunity to understand and use HRQL data. The concept and measurement of reliability are explained and applied to HRQL and common clinical measures simultaneously, and these results are compared with one another. By offering a juxtaposition of common medical measurements and their associated error with HRQL measurement error, the authors note that HRQL instruments are comparable with commonly used clinical data. They further discuss the necessary requirements for clinicians to adopt formal, routine HRQL assessment into their practices.

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