Original Article
A cohort study found the RAND-12 and Health Utilities Index Mark 3 demonstrated construct validity in high-risk primary care patients

https://doi.org/10.1016/j.jclinepi.2004.08.005Get rights and content

Abstract

Objective

The Short Form 12 (SF-12) is widely used in primary care settings. The RAND-12 Health Status Inventory (HSI) and the Health Utilities Index Mark 3 (HUI3) have not been as widely used in such settings. The objective of this study was to examine the construct validity of the RAND-12 and HUI3 in the context of high-risk primary care patients.

Study design and setting

The SF-12, HUI2, and HUI3 were administered to a cohort of high-risk primary care patients. RAND-12 summary scores for physical and mental health were generated. Single-attribute utility scores for each dimension of health status and overall health in HUI3 were computed. A priori hypotheses were specified.

Results

In general, the relationships among RAND-12 and HUI3 scores were consistent with construct validity. Twelve of 24 a priori predictions were confirmed. However, predictions about the correlations between the number of medical conditions and the number of medications and the measures of health-related quality of life were, in general, not confirmed.

Conclusions

The RAND-12 and HUI3 seem to be useful among primary care patients with diverse chronic conditions. Further investigation is warranted.

Introduction

The Medical Outcomes Study Short-Form (SF) set of measures (SF-36, SF-12) have been widely used in research studies and routine clinical care [1]. To date the RAND-12 Health Status Inventory (HSI) [2] and Health Utilities Index Mark 3 (HUI3) [3] have not been as extensively used in primary-care settings. It is important to assess the construct validity of these generic measures in such settings. Because patients seen in primary-care settings have diverse problems, disease-specific measures do not permit comparisons among patients.

In the field of health-related quality of life (HRQOL), there are no gold standard measures. The assessment of validity depends on assessing the extent to which a measure performs as it should if it measures what it says it does (i.e., construct validity, which involves the accumulation of results from application in a variety of settings) [4]. The purpose of this study was to assess the construct validity of two widely used generic measures, RAND-12 and HUI3, in the context of high-risk primary care patients (results for SF-12 and HUI2 are reported in [5]).

Section snippets

RAND-12 HIS

The RAND-12 uses the same health-status assessment questionnaire as the SF-12 [2]. The scoring system for the RAND-12 differs in two important ways. First, RAND-12 permits correlation between physical and mental health (oblique factor rotation). Second, scores are based on weights derived from item-response theory. The RAND-12 generates two summary scores: the physical health composite (PHC) and the mental health composite (MHC) scores.

HUI3

HUI3 includes a health-status classification system and

Results

Complete RAND-12 and HUI3 data were available for 154 of the 199 patients evaluated at baseline. Detailed demographic and clinical characteristics have been presented elsewhere [5]. Briefly, the mean age of patients was 67 years (standard deviation [SD] 17 years), 49% were male, 30% were hypertensives, 26% had osteoarthritis, 20% has osteoporosis, and 20% had depressive disorder. Available information for the 45 patients excluded because of missing data indicates that those excluded had

Discussion

Generic measures are especially relevant for application in groups of patients with diverse physical and mental health problems, such as those in primary care. Results from this study provide evidence that the RAND-12 and HUI3 have reasonable construct validity in such settings.

The correlations of RAND summary scores and overall HUI scores with the number of medical conditions and number of medications were negligible or weak. The number of medical conditions and number of prescription

Acknowledgments

The authors gratefully acknowledge the input of Sherry L. Dieleman, Sandra Brilliant, Ross Bayne, Leslie Gardiner, Dr. David Moores, and Marj Sandilands to the primary care study. The authors gratefully acknowledge the comments made by two anonymous reviewers.

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David Feeny has proprietary interest in Health Utilities Incorporated, which distributes copyrighted Health Utilities Index materials.

Financial support for the study of primary healthcare teams was provided by a grant from the Health Transition Fund Alberta Health and Wellness. Financial support for the analyses presented in this paper was provided by a grant from the Merck Company Foundation to the Institute of Health Economics. The HTF, Merck Company Foundation, and IHE played no role in the design, interpretation, or analysis of the project reported here and have not reviewed or approved of this manuscript.

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