Precision of health-related quality-of-life data compared with other clinical measures

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

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

82 Scopus citations

Abstract

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, we note that HRQL instruments are comparable with commonly used clinical data. We further discuss the necessary requirements for clinicians to adopt formal, routine HRQL assessment into their practices.

Original languageEnglish (US)
Pages (from-to)1244-1254
Number of pages11
JournalMayo Clinic Proceedings
Volume82
Issue number10
DOIs
StatePublished - Oct 2007

ASJC Scopus subject areas

  • Medicine(all)

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