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. 2007 Apr;45(4):315-21.
doi: 10.1097/01.mlr.0000254582.85666.01.

Predicted quality-adjusted life years as a composite measure of the clinical value of diabetes risk factor control

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Predicted quality-adjusted life years as a composite measure of the clinical value of diabetes risk factor control

Julie Schmittdiel et al. Med Care. 2007 Apr.

Abstract

Background: Control of blood pressure, low-density lipoprotein cholesterol (LDL-c), and A1c can lower the risk for diabetes complications. These quality indicators often are examined separately and weighted equally in performance measurement, potentially discarding important information.

Objectives: We sought to create a composite indicator of the clinical benefit, or value, of diabetes risk factor control that appropriately weights the clinical importance of A1c, LDL-c, and blood pressure, and to test its usability for quality measurement.

Methods: The combined value of control for 3 diabetes risk factors, measured by predicted quality-adjusted life years (QALYs), was compared in diabetes patients (n = 129,236 in 2001; n = 185,006 in 2003) in Kaiser Permanente Northern California across 16 medical center populations in 2001 and 2003 using hierarchical linear regression to adjust for case-mix differences. Patient-level QALYs, simulated from risk factor and case-mix variables in a Markov model, was the main outcome variable.

Results: There was significant cross-sectional variability in average case-mix adjusted QALYs for diabetes patients across centers in 2003. QALYs increased from 2001 to 2003 as the result of improved risk factor control; longitudinal improvements in QALYs also showed variation across centers. Regression analyses demonstrated the greater impact of blood pressure versus LDL-c or A1c control on QALYs, and the greater value of risk factor control in those with poor versus near or in-control blood pressure.

Conclusion: Using predicted QALYs to measure value holds promise as a sensitive composite indicator for quality measurement. Complex, evidence-based quality indicators such as these can potentially provide accurate and useful information to health plans, providers, and consumers.

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