April 2010
Volume 51, Issue 13
Free
ARVO Annual Meeting Abstract  |   April 2010
Estimating Potential QALYs Gained From Low Vision Rehabilitation: An Input Into a Cost-Effectiveness Analysis
Author Affiliations & Notes
  • K. D. Frick
    Health Policy and Management, JHBSPH, Baltimore, Maryland
  • R. W. Massof
    Ophthalmology, Johns Hopkins Wilmer Eye Inst, Baltimore, Maryland
  • J. E. Goldstein
    Ophthalmology, Johns Hopkins University, Baltimore, Maryland
  • Low Vision Rehabilitation Outcomes Study Group
    Health Policy and Management, JHBSPH, Baltimore, Maryland
  • Footnotes
    Commercial Relationships  K.D. Frick, None; R.W. Massof, None; J.E. Goldstein, None.
  • Footnotes
    Support  NIH Grant EY012045; Readers Digest Foundation
Investigative Ophthalmology & Visual Science April 2010, Vol.51, 3244. doi:
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      K. D. Frick, R. W. Massof, J. E. Goldstein, Low Vision Rehabilitation Outcomes Study Group; Estimating Potential QALYs Gained From Low Vision Rehabilitation: An Input Into a Cost-Effectiveness Analysis. Invest. Ophthalmol. Vis. Sci. 2010;51(13):3244.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose: : To estimate the potential gain in quality adjusted life years (QALYs) from low vision rehabilitation.

Methods: : As part of an ongoing multicenter collaborative low vision rehabilitation outcome study, patients were asked to respond to the EuroQol EQ5D instrument prior to treatment and again after treatment. The EQ5D asks about five attributes of health: mobility, pain, anxiety, self-care, and usual activities. Each attribute is at one of three levels. The EQ5D was scored using the algorithm developed from research on respondents in the United States. The difference in EQ5D scores was used as the health utility input for the calculation of the potential gain in QALYs. Life expectancy was calculated as a function of the patients' ages in years and months. The equation to predict life expectancy was developed by fitting a fourth-order polynomial to life tables that provided life expectancy as a function of years. Years of health utility improvement were discounted at 3% to calculate the present value of potential QALYs gained.

Results: : To date, 27 patients have responded to the EQ5D both before and after treatment. The average time to response after treatment is 171 days (SD 89). Of the 27 patients, 16 experienced health utility improvements. The maximum improvement was 0.543 units. The maximum loss was 0.430 units. The average health utility change was 0.033 (SD 0.220). The average age of patients was 76.2 years (SD 15.2). The average life expectancy was 11.8 years (SD 9.9). The average potential QALY gain was 0.359 (SD 2.229)

Conclusions: : Given an average potential QALY gain of 0.359, low vision rehabilitation could cost an average almost $18,000 and remain 'highly cost effective" if the standard used is $50,000/QALY. The estimated potential QALY gain may be somewhat optimistic as the gains from improvement in functions related to vision are not the only consideration of health utility for these patients. Eventually other conditions will affect individuals' health utility and may decrease the gap between the utility of individuals who have experienced rehabilitation and those who have not. However, even if the gains in QALYs were reduced by half, the cost could still be $9,000 or rehabilitation to be considered cost-effective.

Keywords: clinical (human) or epidemiologic studies: health care delivery/economics/manpower • low vision • quality of life 
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