The Veterans RAND 12-Item Health Survey (VR-12) is currently the major endpoint used in the Medicare managed care outcomes measure in the Healthcare Effectiveness Data and Information Set (HEDIS®), referred to as the Health Outcomes Survey (HOS). The purpose of this study is to adapt the Brazier SF-6D utility measure to the VR-12 to generate a single utility index.
We used the HOS cohorts 2 and 3 for SF-36 data and 9 for VR-12 data. We calculated SF-6D scores from the SF-36 using the algorithms developed by Brazier and colleagues. The values of the Brazier SF-6D were used to estimate utility scores from the VR-12 using a mapping approach based on a 2-stage mapping procedure, named as VR-6D.
The VR-6D derived from the VR-12 has similar distributional properties as the SF-6D. The change in VR-6D showed significant variations across disease groups with different levels of morbidity and mortality.
This study produced a utility measure for the VR-12 that is comparable to the SF-6D and responsive to change. The VR-6D can be used in evaluations of health care plans and cost-effectiveness analysis to compare the health gains that health care interventions can achieve.
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Short form 36-Item Health Survey
Veterans RAND 36-Item Health Survey
Modified regression estimate
Veterans RAND 12-Item Health Survey
Healthcare Effectiveness Data And Information Set
Health Outcomes Survey
Modified regression estimation
Quality adjusted life years
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The research in this article was supported in part by the Centers for Medicare and Medicaid Services and the National Committee for Quality Assurance (NCQA) under contract number HHSM-500-2009-00051C; the Center for the Assessment of Pharmaceutical Practices (CAPP) Boston University School of Public Health, Boston MA and the Center for Health Quality, Outcomes and Economic Research (CHQOER), Veterans Administration Medical Center, Bedford MA.
SF-36® and SF-12® are registered trademarks of the Medical Outcomes Trust.
In the figure below, the Y-axis is the actual value. The X-axis is the predicted value. The red curve is the regression of the SF-6D on 7 SF-36 scales (without General Health scale). The blue curve is the regression of the SF-6D on 8 SF-36 scales (with General Health). The dark green curve is the Ara and Brazier SF-6D . The orange line is the line from (0,0) to (1,1). For each type of prediction, the predicted values were lumped into buckets 0.4% wide and the actual SF-6D values are averaged within them. The lines represent the non-linear regression lines organized by predicted values. The values by the original SF-6D algorithm and the regression method tracked each other in the mean utility up to about .8, and from there, the Brazier SF-6D goes up to 1 at roughly twice the rate of the linear version. The curvature in the values reflected the non-linearity of the SF-6D.
We estimated the transformation (T) coefficients using variables defined as follows utility prediction (p) estimated from step 1 and sf6dhat:
p2 = p^2;
p3 = p^3;
p4 = Max(p-86, 0);
p42 = p4^2;
p5 = Min(p-42, 0);
and a constraint in place that the maximum predicted value should yield a utility of 1.
P > |t| [95% Conf. Interval]
0.000 3.958 4.045
0.000 −.0579 −.056
0.000 .000 .001
0.000 1.813 1.977
0.000 .156 .218
0.000 −.062 −.042
0.000 −48.425 −46.647
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Selim, A.J., Rogers, W., Qian, S.X. et al. A preference-based measure of health: the VR-6D derived from the veterans RAND 12-Item Health Survey. Qual Life Res 20, 1337–1347 (2011). https://doi.org/10.1007/s11136-011-9866-y