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Quality Measurement and Improvement |

Generic Health Measurement: Past Accomplishments and a Measurement Paradigm for the 21st Century

Colleen A. McHorney, PhD
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From the University of Wisconsin-Madison Medical School and the William S. Middleton Memorial Veterans Hospital, Madison, Wisconsin. Note: This article is one of a series of articles comprising an Annals of Internal Medicine supplement entitled “Measuring Quality, Outcomes, and Cost of Care Using Large Databases: The Sixth Regenstrief Conference.” To see a complete list of the articles included in this supplement, please view its Table of Contents. Acknowledgments: The author thanks Fredric Wolinsky, PhD, and Earl Bricker, MA, for thoughtful comments on earlier versions of this manuscript; David Kindig, MD, PhD, and Mark Linzer, MD, for intellectual support; and Jody McIntyre and Amy Maloney for contributions as research staff. Grant Support: By the Department of Veterans Affairs (HSR&D HFP #96-001, RR&D C-2016, and IIR #95-033) and by the University of Wisconsin-Madison Medical School. Work on this paper was completed while Dr. McHorney was a 1996 Picker/Commonwealth Scholars Program Finalist. Requests for Reprints: Colleen A. McHorney, PhD, William S. Middleton Memorial Veterans Hospital, 2500 Overlook Terrace, Madison, WI 53705.

Copyright ©2004 by the American College of Physicians

Ann Intern Med. 1997;127(8_Part_2):743-750. doi:10.7326/0003-4819-127-8_Part_2-199710151-00061
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Generic health surveys have been proposed for use in increasingly diverse applications and populations. This paper describes the history of generic tools in the past 30 years and suggests a more modern measurement platform for advances in the 21st century. Many generic tools lack the precision required for effective health care decision making. A meaningful goal for the next era of development of generic measures should be the generation of equiprecise measurement for generic health concepts. Equiprecise tests yield measures of equal precision at all levels of the underlying construct. Equiprecise measurement can be achieved through conjoint use of computerized-adaptive testing as the survey platform and item response theory as the measurement theory.


Grahic Jump Location
Figure 1.
Timeline of the evolution of generic health measures with respect to broader developments in health policy and health status assessment.

ARA = American Rheumatoid Association Functional Class; COOP = Dartmouth COOP Poster Charts; Duke = Duke-UNC Health Profile; Duke-17 = Duke Health Profile; FSQ = Functional Status Questionnaire; HIE = Health Insurance Experiment; HPL = Human Population Laboratory; HPQ = Health Perceptions Questionnaire; HSI = Health Status Index; KPS = Karnofsky Performance Status; Katz = Katz Index of Activities of Daily Living; LF-149 = Medical Outcomes Study 149-Item Functioning and Well-Being Profile; M-M = morbidity and mortality; MHIQ = McMaster Health Index Questionnaire; NHIS = National Health Interview Survey; NHP = Nottingham Health Profile; PGWB = Psychological General Well-Being Scale; QWB = Quality of Well-Being Scale; SF-6 = Medical Outcomes Study 6-Item Health Survey; SF-12 = Medical Outcomes Study 12-Item Health Survey; SF-20 = Medical Outcomes Study 20-Item Health Survey; SF-36 = Medical Outcomes Study 36-Item Health Survey; SIP = Sickness Impact Profile; WHO = World Health Organization.

Grahic Jump Location
Grahic Jump Location
Figure 2.
Physical functioning scores for chronically ill patients.[54]

SF-6 = Medical Outcomes Study 6-Item Health Survey; SF-36 = Medical Outcomes Study 36-Item Health Survey. Data obtained from the Medical Outcomes Study .

Grahic Jump Location




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