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HSR&D 2004 National Meeting Abstracts


2030. Depression Free Day to QALY Conversions: Are They Valid?
Shanti P Tripathi, MS, University of Arkansas for Medical Sciences, JM Pyne, Central Arkansas Veterans Healthcare System and University of Arkansas for Medical Sciences, DK Williams, University of Arkansas for Medical Sciences

Objectives: Recent cost-effectiveness analyses for depression interventions have used the concept of depression free days (DFDs) to calculate quality-adjusted life years (QALYs) to be used in cost per QALY ratios. To our knowledge, the conversion formulas used have never been tested against a gold standard QALY measure.

Methods: We compared QALYs calculated from the Quality of Well-Being scale (QWB) and QALYs calculated from Hamilton Rating Scale for Depression (HRSD) and Beck Depression Inventory (BDI) DFDs. The QALY calculations used an area under the curve method from ratings at baseline, 1 week, 1, 4, 6, 9, and 12 months. Subjects were all diagnosed with major depression (N=77) and were divided into responder (50% improvement in HRSD from 4-months on), partial-responder (50% HRSD improvement, but not maintained), and non-responder groups. The QALY scores were compared using a repeated measures model.

Results: Mean QALYs were in the following order: HRSD>BDI>QWB. Differences in response group mean QALYs were ordered BDI>QWB>HRSD. Response group differences ranged from 0.0036 (responder and partial-responder difference for QWB and HRSD) to 0.047 (responder and non-responder difference for BDI and HRSD). QALY differences greater than 0.02 are typically considered clinically significant. The only statistically significant difference found was between HRSD and BDI responder and non-responder (p=0.02).

Conclusions: HRSD QALY estimates are consistent with the gold standard QWB QALY estimates, whereas BDI QALY estimates may overestimate QALYs.

Impact: Adjustment in the published formula used for converting BDI DFDs to QALYs is indicated in order to produce more accurate QALY estimates and ultimately more accurate cost-effectiveness ratios for depression interventions.