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Table 1.  Mean Vision Utilities for Snellen Visual Acuities in the Better-Seeing Eye (BSE) From Different Cohort Respondents
Mean Vision Utilities for Snellen Visual Acuities in the Better-Seeing Eye (BSE) From Different Cohort Respondents
Table 2.  Comparison of Patient Value, Ophthalmic Health Care Cost, Perspective, and Cost-Utility Ratios Associated With and Without Patient Utilities and Systemic Comorbidity Integration for Better-Seeing Eye Cataract Surgery
Comparison of Patient Value, Ophthalmic Health Care Cost, Perspective, and Cost-Utility Ratios Associated With and Without Patient Utilities and Systemic Comorbidity Integration for Better-Seeing Eye Cataract Surgery
Table 3.  Comparison of Patient Value, Ophthalmic Health Care Cost Perspective, and Cost-Utility Ratios Associated With and Without Patient Utilities and Systemic Comorbidity Integration for Neovascular Age-Related Macular Degeneration Therapy With Vascular Endothelial Growth Factor Inhibitor Ranibizumab
Comparison of Patient Value, Ophthalmic Health Care Cost Perspective, and Cost-Utility Ratios Associated With and Without Patient Utilities and Systemic Comorbidity Integration for Neovascular Age-Related Macular Degeneration Therapy With Vascular Endothelial Growth Factor Inhibitor Ranibizumab
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Brown  GC, Brown  MM, Rapuano  SB, Boyer  DA.  A cost-benefit analysis of VEGF-inhibitor therapy for neovascular age-related macular degeneration in the United States.   Am J Ophthalmol. Published online July 16, 2020.PubMedGoogle Scholar
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    Original Investigation
    February 4, 2021

    Opportunities to Reduce Potential Bias in Ophthalmic Cost-Utility Analysis

    Author Affiliations
    • 1Center for Value-Based Medicine, Hilton Head, South Carolina
    • 2Wills Eye Hospital, Thomas Jefferson Medical University, Philadelphia, Pennsylvania
    • 3Department of Ophthalmology, Emory University School of Medicine, Atlanta, Georgia
    • 4Department of Ophthalmology, Aria-Jefferson Health, Philadelphia, Pennsylvania
    • 5Glaucoma Service, University of Michigan Kellogg Eye Center, Ann Arbor
    JAMA Ophthalmol. 2021;139(4):389-397. doi:10.1001/jamaophthalmol.2020.6591
    Key Points

    Question  Does using vision utilities acquired from surrogate (nonpatient) individuals and/or vision utility gains limited by systemic comorbidity utility affect preference-based comparative effectiveness and cost-effectiveness of ophthalmic interventions?

    Findings  In this economic evaluation, cost-utility analyses of cataract surgery and neovascular age-related macular degeneration therapy using nonpatient vision utilities and/or vision utility gain limited to the systemic comorbidity utility level decreased preference-based comparative effectiveness and cost-effectiveness, potentially biasing against disabled, elderly, and minority populations.

    Meaning  Bias against ophthalmic interventional comparative effectiveness and cost-effectiveness can theoretically limit advantageous patient interventions, decrease cost-utility analysis acceptance in US public policy, reduce ophthalmic research dollars, diminish interventional reimbursement, and lessen therapeutic advances.

    Abstract

    Importance  Select research methods in cost-utility analysis (incremental cost-effectiveness analysis) might potentially bias against patient value (quality-adjusted life-year [QALY]) gain and cost-effectiveness associated with common ophthalmic interventions in disabled, elderly, and African American populations.

    Objective  To ascertain whether using nonpatient vision utilities and/or a maximum limit model constraining vision utility gain to the systemic comorbidity utility level biases against ophthalmic cost-utility outcomes.

    Design, Setting, and Participants  This economic evaluation predominantly used data from the Center for Value-Based Medicine database to perform preference-based comparative effectiveness and cost-utility analyses for cataract surgery and intravitreal ranibizumab therapy for neovascular age-related macular degeneration (NVAMD) using vision utilities acquired from patients with ophthalmic disease (ophthalmic patient utilities) and from surrogate individuals (nonophthalmic patient vision utilities) with and without integrating systemic comorbidity utility limits on vision utility gain. Ophthalmic patient data were collected from January 1, 2000, to December 31, 2016, and analyzed from April 1 to July 1, 2020.

    Interventions  Cost-utility analysis with 3% discount rate in 2018 US dollars.

    Main Outcomes and Measures  QALY gains and dollars expended per QALY gain (the cost-utility ratio).

    Results  A total of 309 participants in the nonophthalmic patient cohort and 505 patients in the ophthalmic patient cohort were included. A reference case of first-eye cataract surgery using ophthalmic patient vision utilities and no systemic comorbidity utility limits yielded a 2.574 (34.2%) QALY gain vs observation. Substituting nonophthalmic patient utilities resulted in a 1.502 (15.5%) QALY gain, whereas using the 0.76 patient systemic comorbidity utility to limit cataract surgery vision utility gain yielded a 1.337 (17.8%) QALY gain. Using both nonophthalmic patient utilities and systemic comorbidity utility limits yielded a 0.839 (8.7%) QALY gain. The substitutions decreased cataract surgery cost-effectiveness by 71.3% (95% CI, 70.6%-72.1%) for nonophthalmic patient utilities, 92.5% (95% CI, 51.9%-133.1%) for patient systemic comorbidity utility, and 206.8% (95% CI, 202.6%-211.2%) for both. The NVAMD ranibizumab therapy reference case yielded a 1.339 (26.1%) QALY gain. Similar substitutions resulted in QALY gains of 1.164 (22.7%) for nonophthalmic patient utilities while reducing cost-effectiveness by 16.4%, 1.001 (19.5%) for systematic-limiting comorbidity utility while reducing cost-effectiveness by 33.8%, and 0.971 (18.9%) for both while reducing cost-effectiveness by 37.9%.

    Conclusions and Relevance  Using nonophthalmic patient vision utilities and/or the maximum limit model of limiting patient utility gains to the population systemic comorbidity utility level resulted in large decreases in patient value (QALY) gain and cost-effectiveness for common ophthalmic interventions. Ophthalmologists should realize these phenomena and consider correcting the potential discrimination against disabled, elderly, and African American populations. This negative potential bias could theoretically result in beneficial intervention denial, less research dollars, curbed therapeutic advances, and decreased interventional reimbursement.

    Introduction

    Cost-utility analysis (incremental cost-effectiveness analysis) evaluates health care interventions by integrating objective improvement in patient quality of life (QOL) and/or length of life with costs using the cost-utility ratio of dollars expended per quality-adjusted life-year (QALY) gained.1 Quality of life is quantified by utilities.2

    Utilities typically quantify the QOL associated with a health state on a scale ranging from 0.00 (death) to 1.00 (normal health or normal vision permanently). Utilities can be acquired from patients or surrogate respondents, such as physicians, the general community (society), researchers, family members, or others.3 Vision utilities have been shown to be unaffected by systemic comorbidities or accompanying diseases by some researchers,4,5 whereas others6,7 believe comorbidities should be integrated to avoid overestimation of the utility gain conferred by interventions in multimorbid populations.

    Examples of mean patient utilities include 0.80 associated with a moderate myocardial infarction or an ocular disease with a visual acuity of 20/40 in the better-seeing eye.8 The analogous mean utility associated with ocular diseases causing a visual acuity of 20/40 in the better-seeing eye in a community population was 0.96, demonstrating the disparity compared with patients with ocular disease.3

    From 20 years each of performing cost-utility analysis (G.C.B., M.M.B., and J.D.S.), we note 2 scenarios that potentially bias against ophthalmic cost-utility analyses to yield less utility gain, less QALY gain, and diminished cost-effectiveness. These scenarios are using vision utilities acquired from individuals without ophthalmic disease (nonophthalmic patient [community] vision utilities) instead of those acquired from patients with ophthalmic disease (ophthalmic patient utilities)1,3,9,10 and limiting interventional vision utility gain to an associated systemic comorbidity utility level. The latter has been called the maximum limit model.6,7 The Second Panel on Cost-Effectiveness in Health and Medicine (Second Panel), although preferring community utilities, stated that performing cost-utility analysis using patient preferences (utilities) as well is reasonable.1 The Second Panel also recommended explicitly explaining in a sensitivity analysis how potentially discriminating methods alter cost-utility outcomes.2

    The International Society for Pharmacoeconomics and Outcomes Research recommends using societal utilities over patient utilities, although it notes that some agencies, such as the Swedish Dental and Pharmaceutical Benefits Agency, prefer patient utilities.11 The Swedish Dental and Pharmaceutical Benefits Agency believes in the human dignity principle that “all individuals have equal value.”12 We agree, especially because societal utilities for the same health state can differ dramatically from patient utilities.3,9,10,13

    Our experience suggests that mean vision utilities acquired from patients with diverse vision levels are typically lower than respective vision utilities acquired from surrogate respondents, such as the general community, medical students, nonophthalmic physicians, and even ophthalmologists.3,9,10,13 These higher surrogate utilities can result in lower QALY gains associated with an intervention and therefore less favorable cost-utility ratios. When interventional vision utility gain is limited by systemic comorbidity utility,6,7 QALY gains (comparative effectiveness) and cost-effectiveness ratios can also be adversely affected.

    Utilities obtained with different instruments (time trade-off [TTO], standard gamble, and multiple attribute) are well known to yield different utilities for the same health state.2,13-16 Thus, all utilities herein were acquired by direct interview using the same TTO utility analysis format. We prefer TTO vision utilities rather than the EuroQol–5 Dimension (EQ-5D) and Health Utilities Index Mark 3 (HUI3) multiple-attribute vision utilities because the EQ-5D lacks a linear correlation with vision17,18 and the 6 HUI3 descriptive classifications are difficult to correlate with conventional acuity measurements.19

    To assess potential negative bias against ophthalmic interventions, we undertook cost-utility analyses to compare the QALY gains and cost-utility ratios associated with 2 common ophthalmic interventions: (1) cataract surgery and (2) intravitreal ranibizumab therapy for neovascular age-related macular degeneration (NVAMD). Cataract surgery is cost-effective,20 and intravitreal ranibizumab therapy is moderately cost-effective.21

    Methods

    Quiz Ref IDIn this economic evaluation, cost-utility analyses for each intervention were modeled using ophthalmic and nonophthalmic patient utilities, which can vastly differ for the same visual acuity,2,3,8-10,13,14 as well as limiting and not limiting vision utility gains to systemic comorbidity utility levels. Utility acquisition was approved by the Wills Eye Hospital institutional review board. Written permission was obtained for utility acquisition, and adherence to the Declaration of Helsinki22 was undertaken.

    Vision Utilities

    Vision utilities ranged from 0.00 (death) to 1.00 (bilateral 20/20 vision permanently).14 Bilateral visual acuity of no light perception was associated with a 0.26 TTO utility.14

    The TTO questionnaire first asked participants to estimate their remaining time of life and then asked what was the maximum proportion of that remaining time—if any—that they would theoretically trade to undergo an intervention guaranteed to restore normal bilateral visual acuity permanently.2,4,8-10,13-16 The proportion of time traded was subtracted from 1.00 to calculate the utility. These utilities have a linear correlation with better-eye visual acuity2,13,14 and are sensitive to small changes in visual acuity.2,13,14 These utilities also have excellent reliability15 and good to excellent construct validity.16

    Multiplying a utility by years living with that utility results in QALY accrual. Thus, living with a utility of 0.90 times 10 years results in 9.0 QALYs accrued.2 Living with a utility of 0.50 times 10 years results in 5.0 QALYs accrued. A utility gain of 0.20 times 14 years after an intervention results in a gain of 2.8 QALYs.

    TTO Utility Cohorts

    Our nonophthalmic patient vision utilities were taken from a prior analysis of 142 community participants without ocular disease3 and 167 preclinical first- and second-year medical students with no ophthalmic exposure.9 Ophthalmic patient utilities were derived from 505 consecutive participating patients with ophthalmic disease; utilities were predominantly published and taken from Center for Value-Based Medicine files2,4,5,8,13,14,23,24 (Table 1).

    Cataract Surgery

    Cataract surgery cost-utility analyses were based on a 2018 US cataract surgery cost-utility analysis using a reference case.20 The mean (SD) patient age at better-seeing eye surgery was 73 (13 [95% CI, 70-76]) years, mean preoperative Snellen visual acuity was 20/83 (utility, 0.699) in the better-seeing eye, and mean postoperative visual acuity was 20/27 (utility, 0.868).

    Vascular Endothelial Growth Factor Inhibitor Therapy for NVAMD

    Reference case data herein were taken from a 2018 cost-utility analysis of ranibizumab therapy for NVAMD21 based primarily on the Comparison of Age-related Macular Degeneration Treatments Trials Study.24 The posttreatment visual acuity in a patient with NVAMD at 11 years was 20/63 − 2, correlating with a TTO vision utility of 0.73.21 Control cohort data after 2 years came from a Lineweaver-Burke plot meta-analysis by Shah and Del Priore25 evaluating NVAMD natural history based on 6 randomized NVAMD clinical trial control cohorts in the Macular Photocoagulation Study. With 20/63 baseline visual acuity in an untreated control cohort, acuity decreased to 20/630 (utility, 0.528) at 9 years and remained so through 11 years.23

    Comorbidities

    Cost-utility comorbidities can be addressed several ways. The first is to ignore them because systemic comorbidities have been shown not to affect vision utilities.4,5 This protocol prevents discrimination against disabled, elderly, and African American populations; the latter have a greater systemic comorbidity burden than the average US population.1,2,6,7,26 Methods to integrate TTO, standard gamble, and multiple-attribute utilities include (1) the maximum limit approach, (2) the additive approach, and (3) the multiplicative approach.6,7 The method we discuss herein is the maximum limit approach, which uses the lowest systemic comorbidity utility as an upper limit for the vision utility gain associated with ophthalmic interventions.6

    Systemic Utility

    Systemic utility can be calculated with multiple-attribute utility instruments, such as the EQ-5D17,18 and HUI3.19 Nonetheless, a TTO utility analysis demonstrated that when more than 1 medical condition was present, overall QOL was determined by the disease associated with the lowest utility.5 We used this latter method to calculate the mean systemic utilities in the cataract and NVAMD treatment and control cohorts when using the maximum limit approach.

    To ascertain systemic utility associated with cataract and NVAMD, we reviewed consecutive cases with cataract and NVAMD in a Center for Value-Based Medicine 505 vision utility database for which all systemic comorbidities were also available.4,5,8,13,14,23 Data were gathered by direct interview from January 1, 2000, to December 31, 2016.5,7,8,13,14,23 Nonophthalmic patient systemic TTO utilities were taken from the Center for Value-Based Medicine database, which contains more than 55 000 utilities.2

    Mortality

    Christ and colleagues27 calculated the hazard ratio of premature mortality at 8 years associated with vision loss in the better eye in the 2542-participant Salisbury Evaluation Study, which included patients aged 65 to 74 years at baseline. Ranibizumab therapy for NVAMD prevented 1 year of life loss during 11 years compared with no treatment.21 With cataract surgery, 1 year of life loss during 14 years was prevented.20 Our cost-utility analyses integrated these length-of-life changes.2

    Cost-Utility Variables

    All QALY outcomes and costs were discounted at 3% annually.2 The cost basis was the average national Medicare Fee Schedule,28 and the third-party insurer or health cost perspective was used.1,2 All costs were in 2018 US dollars.20,21

    Statistical Analysis

    Data were analyzed from April 1 to July 1, 2020. Continuous utility variables were compared using the 2-sided t test without adjustments for multiple analyses. Most utilities associated with specific vision levels are normally distributed with the Kolmogorov-Smirnoff test. Significance was set at 2-sided α < .05. Excel software, version 10 (Microsoft Corporation), was used to perform the statistical analyses.

    Results
    Vision Utilities in Dissimilar Cohorts

    Ophthalmic patient and nonophthalmic patient vision utility effects on cost-utility analysis are addressed, followed by systemic comorbidity limiting effects. The ophthalmic patient cohort consisted of 505 patients with cataract or NVAMD. The mean (SD) TTO vision utility for the combined nonophthalmic patient cohort (n = 309), which consisted of participants from the general public (n = 142)3 and preclinical medical students (n = 167),10 for visual acuity of 20/40 in the better-seeing eye was 0.96 (0.07; 95% CI, 0.95-0.97) compared with 0.80 (0.20; 95% CI, 0.76-0.84) (P < .001) in the ophthalmic patient cohort (n = 87) (Table 1).13 For visual acuity of 20/200 in the nonophthalmic patient cohort (n = 309), mean (SD) vision utility was 0.87 (0.09 [95% CI, 0.85-0.87]) compared with 0.62 (0.21 [95% CI, 0.54-0.70]) (P < .001) in the ophthalmic patient cohort (n = 24).2,13,14,23 With bilateral visual acuity of no light perception, the nonophthalmic cohort (n = 167) had an estimated mean (SD) vision utility of 0.80 (0.12 [95% CI, 0.78-0.82])9 vs 0.26 (0.14 [95% CI, 0.19-0.33]) (P < .001) for the ophthalmic cohort (n = 16).14

    Interventional QALY Gains and Cost-Utility Ratios
    Cataract Surgery QALY Gains

    The reference case for first-eye cataract surgery (20/83 in the better-seeing eye) resulted in a 2.574 QALY gain during a mean life expectancy of 14 years, a 34.2% QALY gain over no surgery using ophthalmic patient utilities, and no systemic comorbidity utility limits (Table 2).20 Of the 34.2% QALY gain, 77.5% was attributable to QOL gain and 22.5% to length-of-life gain.

    Using nonophthalmic patient utilities yielded a 1.502 QALY gain, a 15.5% gain vs the 34.2% reference case gain. This result was 41.6% less than the reference case gain of 2.574 QALYs. When vision utility gain was limited to 0.76 by the cataract patient utility, systemic comorbidity utility (mean [SD] utility acquisition age, 72 [13] years; 95% CI, 69-75 years), the QALY gain was 1.337, a 17.8% gain vs the 34.2% gain with no utility limit or a 48.1% loss vs the 2.574 QALY reference case gain. The use of both nonpatient vision utilities and a 0.903 nonpatient systemic comorbidity utility to limit vision utility gain yielded a 0.839 QALY gain, equating to an 8.7% QALY gain compared with no treatment and a 1.735 QALY loss, or 67.4% loss, compared with the reference case.

    Cataract Surgery Cost-Utility Ratios

    Quiz Ref IDSubstituting nonophthalmic patient utilities for ophthalmic patient utilities decreased cataract surgery cost-effectiveness by 71.3% compared with the reference case, whereas the maximum limit approach decreased cost-effectiveness by 92.5% (95% CI, 51.9%-133.1%) (Table 2). Substituting nonophthalmic patient vision utilities and using a mean nonpatient systemic comorbidity utility analogue of 0.903 as the vision utility limit gain resulted in a 206.8% (95% CI, 202.6%-211.2%) cost-effectiveness decrease compared with the reference case.

    NVAMD Therapy QALY Gains

    Treatment of the average patient with NVAMD (integrating those with NVAMD in 1 eye and good vision in the fellow eye and those with NVAMD in 1 eye and visual loss in the fellow eye) with intravitreal ranibizumab during 11 years (mean life expectancy) resulted in a reference case QALY gain of 1.339, converting to a 26.1% QALY gain compared with no therapy (Table 3).21 The 26.1% QALY gain consisted of an 80.8% QOL gain and a 19.2% length-of-life gain.

    Substituting nonophthalmic patient utilities yielded a 1.164 QALY gain, a 22.7% QALY gain compared with no treatment or compared with the reference case 1.339 QALY gain (26.1%). This result was a 0.175 QALY loss, or a 13.1% loss, from the reference case. Using an ophthalmic patient systemic comorbidity (mean [SD] utility acquisition age, 76 [9] years; 95% CI, 75-77 years) utility gain limit of 0.70 for vision utility gain while using ophthalmic patient utilities yielded a 1.001 QALY gain, a 19.5% QALY gain compared with no treatment and 0.338 QALY loss or a 25.2% QALY loss compared with the reference case 1.339 QALY gain. When nonophthalmic patient utilities and a 0.899 nonpatient systemic comorbidity utility limit for vision utility gain were both integrated, the QALY gain was 0.971, an 18.9% QALY gain compared with no therapy and a 0.368 QALY loss (27.5% QALY loss) compared with the reference case.

    NVAMD Therapy Cost-Utility Ratios

    Quiz Ref IDSubstituting nonophthalmic patient for ophthalmic patient utilities decreased cost-effectiveness by 16.4% (95% CI, 6.9%-25.9%) compared with the reference case, while using the 0.70 mean systemic comorbidity utility of ophthalmic patients as the limit of vision utility gain decreased cost-effectiveness by 33.8% (95% CI, 11.8%-55.8%). Substituting nonophthalmic patient vision utilities and using a mean nonpatient systemic comorbidity utility of 0.899 to limit NVAMD therapy vision utility gain yielded a 37.9% (95% CI, 28.7%-48.1%) cost-effectiveness decrease.

    Discussion

    This analysis demonstrated that substituting nonophthalmic patient vision utility estimates for ophthalmic patient utilities in cost-utility analysis for cataract surgery and NVAMD ranibizumab therapy resulted in decreased patient QALY gains (comparative effectiveness) and cost-effectiveness, as did limiting interventional vision utility gain to the systemic comorbidity utility level. Using a $100 000/QALY cost-effectiveness upper limit often quoted in the US,2 the NVAMD reference case was cost-effective ($79 600/QALY) (Table 3), whereas the cost-utility ratios integrating systemic comorbidity utility limits ($106 476/QALY) and comorbidity limits plus nonpatient vision utilities ($109 765/QALY) (Table 3) were not. Cataract surgery remained cost-effective under all scenarios despite a 206.8% decrease in cost-effectiveness when nonpatient utilities and comorbidity limits were used, which is not surprising because the reference case cost-utility ratio was only $1007/QALY (Table 2). Decreasing the comparative effectiveness and cost-effectiveness could theoretically constrain beneficial patient interventions, decrease ophthalmic research funds, limit interventional reimbursement, and curb therapeutic advances.

    Nonpatient vs Patient Utilities

    The National Institute for Health and Care Excellence,29 the International Society for Pharmacoeconomics and Outcomes Research,11 and the Second Panel1 advocate general community utilities for cost-utility analyses, whereas the Swedish Dental and Pharmaceutical Benefits Agency uses patient utilities,11,12 as do we.2-5,8,9,13,14,20,21,23,24 Nonpatient TTO Beaver Dam Health Outcomes Study utilities30 were a mean of 8.5% higher than patient utilities for 93% (26 of 28) of systemic diseases evaluated (P < .001).2 These utility underestimations were far less dramatic than our nonophthalmic patient vision utility underestimates, which ranged from 192% to 400%. These disparities all support the concept that those who best understand QOL associated with a health state are individuals who have experienced it personally.2

    One reason purported to justify use of community utilities is that the public ultimately pays for health care.31 We find this stance to be an unconvincing rationale for using public utilities that greatly differ from patient utilities. Another argument supporting use of public utilities is that patients may “game the system” by stating that their QOL is worse than it is to receive greater attention and/or funding for their condition.31 This stance is certainly at odds with increasing acceptance of patient-centered health outcomes.32 We encountered no patient self-interest questions during 5000 patient ophthalmic and/or systemic utility interviews.

    Utility Gain Limits

    Limiting vision utility gains to the systemic comorbidity utility biases cost-utility analysis against elderly, disabled, and African American populations; the latter group has been shown to have a higher chronic disease burden and to develop multimorbidity at an earlier age than White counterparts.26 Systemic comorbidity utility decreases with age owing to an increased number of and more serious diseases. Because ophthalmic interventions are often performed in the older population,20,21 utility limits can selectively decrease patient value gain (QALY gain) for ophthalmic interventions. Cost-utility analysis without the biases studied herein already theoretically discriminates against elderly patients because QALY gains from lifetime interventions are typically less in older than younger populations. In a disabled population with a low comorbidity utility of 0.49 encountered with end-stage kidney disease, a person with a 0.52 vision utility from cataracts with visual acuity of bilateral counting fingers would not incur any benefit from cataract surgery or even lose QOL using the comorbidity maximum limit approach.8 We find that outcome to be unacceptable.

    Compared with older patients with ophthalmic disease, the mean age of adults with severe asthma is 54 years.33 The mean age at presentation of autosomal dominant polycystic kidney disease, the most common inherited kidney disease, is 31.6 years,34 whereas systemic arterial hypertension presents at 53.2 years,35 and 4.9 million US citizens aged 18 to 44 years have type 1 or 2 diabetes.36 Interventions for these diseases likely occur at earlier ages, with less systemic comorbidity than associated with the ophthalmic interventions described herein.

    Second Panel

    The Second Panel recommends that researchers performing cost-utility analysis assess whether the analysis discriminates against various cohorts and how such discrimination can be avoided.1 Our data suggest that using patient utilities and not integrating systemic comorbidity utilities minimize discrimination. The Second Panel supports the use of patient utilities in select populations.1

    Limitations

    Quiz Ref IDSome investigators37 suggest that average cost-utility analysis comparing treatment with no treatment does not have a role in establishing cost-effectiveness standards and that only incremental cost-effectiveness analysis (comparing one intervention with another) should guide public policy. We disagree. The analysis variant is arbitrary for cataract surgery and vascular endothelial growth factor inhibitor therapy for NVAMD studied herein. The only reasonable alternative to cataract surgery is observation,20 whereas vascular endothelial growth factor inhibitor therapy for NVAMD has supplanted other forms of therapy for many years.21

    The US Patient Protection and Affordable Care Act1 currently forbids the Patient-Centered Outcomes Research Institute from using dollars-per-QALY instruments to establish health care recommendations. Thirty-one countries, however, including Japan, Germany, England, and France, require some form of pharmacoeconomic analysis for drug reimbursement.38 Medicare is currently using patient Health Outcomes Surveys data for Medicare Advantage quality bonus payments.39 We agree with patient-centered care1,32; patient QOL opinions are critical because patients are health care recipients.

    This study should not be considered anti–cost-utility analysis, a method we very much favor to improve quality of care and national wealth.2-5,8-10,13-16,20,21,23,39 Rather, we provide a constructive critique to improve the process. We are unaware of other methods that more effectively integrate subjective patient opinions into quantified objective data to identify the most patient-centered, beneficial, cost-effective health care interventions.2

    Conclusions

    In this economic evaluation using 2 cost-utility analysis methods, community nonophthalmic patient vision utilities and systemic comorbidity utility as an upper limit for vision gain utility discriminate against ophthalmic interventional comparative effectiveness and cost-effectiveness. Use of systemic comorbidity utilities potentially biases against older, disabled, and African American populations. These biases could disadvantage patients and ophthalmology by limiting beneficial interventions, discouraging cost-utility analysis adoption into US public policy, decreasing ophthalmic research dollars, minimizing interventional reimbursement, and curbing therapeutic advances.

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    Article Information

    Accepted for Publication: November 12, 2020.

    Published Online: February 4, 2021. doi:10.1001/jamaophthalmol.2020.6591

    Corresponding Author: Gary C. Brown, MD, MBA, Center for Value-Based Medicine, PO Box 3417, Hilton Head, SC 29928 (gbrown@valuebasedmedicine.com).

    Author Contributions: Dr G. C. Brown had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

    Concept and design: G. C. Brown, M. M. Brown.

    Acquisition, analysis, or interpretation of data: All authors.

    Drafting of the manuscript: G. C. Brown, M. M. Brown.

    Critical revision of the manuscript for important intellectual content: All authors.

    Statistical analysis: G. C. Brown.

    Administrative, technical, or material support: M. M. Brown.

    Supervision: M. M. Brown.

    Conflict of Interest Disclosures: Dr G. C. Brown reported being a shareholder in the Center for Value-Based Medicine. Dr M. M. Brown reported being a shareholder in the Center for Value-Based Medicine. No other disclosures were reported.

    Additional Contributions: Sharon L. Christ, PhD, MS, Department of Human Development and Family Studies at the College of Health and Human Sciences, Purdue University, calculated the life expectancy associated with different levels of visual loss in the best-seeing eye. Dr Christ received no compensation from the authors for this endeavor.

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