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K.D. Frick, A.L. Robin, J. Katz; Modeling the Net-Benefit of Screening for Glaucoma-Gauging the Best Alternative . Invest. Ophthalmol. Vis. Sci. 2003;44(13):172.
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Purpose: To develop a model assessing the net benefit of glaucoma screening methods that can vary by both device used and criterion indicating a "positive" screen. Methods: Data on sensitivity and specificity of glaucoma screening methods come from the literature. Medicare payment rates proxy for costs of screening for and diagnosing glaucoma. Net benefit is a function of costs, population size, prevalence of glaucoma, number screening positive, excess cost of care and the quality adjusted life year (QALY) gain for true positives (relative to what they would experience if they were not screened), and the QALY loss for false positives. Limited data exist on many parameters. The net benefit can be calculated with combinations of the QALY gain (range 0-2) and excess costs (range $0-$10,000) for true positive and the QALY loss for false positives (range 0-0.2). As there is not a fixed monetary value of a QALY, a range of $50,000-$500,000 was used. Results: In analyses of nine methods, we assumed a monetary value of QALYs of $50,000 and an excess cost of treatment of $10,000. At some combinations of QALYs gained and lost the FDT yielded the highest net benefit; at others the OCT yielded the highest net benefit; and at the remainder neither yielded a positive net benefit. At high QALY gains and low QALY losses the FDT had the highest net benefit (as high as $1,400 per person screened); at high values of both QALY changes, the OCT had the highest net benefit (as high as $1,100 per person screened). When the loss is large in comparison with the gain no method yielded a positive net benefit. At higher excess costs of treating cases found both screenings are less likely to yield positive net benefits; the opposite occurs at higher monetary values of a QALY. Conclusions: Some screening methods for glaucoma have the potential to provide a positive net benefit. Additional work is needed to narrow the ranges of unknown parameters and project the take-up rate for an operational screening program to determine whether a positive net benefit is more than a theoretical possibility.
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