Approximately 8 million Americans self-report vision loss and blindness (VL), potentially resulting in a significant economic burden.
Estimate the economic burden of VL in the US and by state.
Analysis of secondary data sources (American Community Survey (ACS), American Time Use Survey, Bureau of Labor Statistics, Medical Expenditure Panel Survey (MEPS), National and State Health Expenditure Accounts (N/SHEA), National Health Interview Survey (NHIS)) using attributable fraction, regression, and other methods to estimate the incremental direct and indirect 2017 costs of VL.
People with a yes response to a question asking if they are blind or have serious difficulty seeing even when wearing glasses in the ACS, MEPS, or NHIS.
We estimated the direct costs of medical, nursing home (NH), and supportive services; and indirect costs of absenteeism, lost household production, reduced labor force participation, and informal care by age group (0-18 years, 19-64 years, 65+ years), sex (male, female), and state in aggregate and per person with VL.
We estimated an economic burden of VL of $134.2bn, $98.7 bn in direct costs, and $35.5 bn in indirect costs. The most substantial burden components were NH ($41.8 bn), medical care services other than inpatient, ambulatory, and prescription care ($30.9 bn), and reduced labor force participation ($16.2 bn) which accounted for 66% of the total. Persons with VL incurred $16,838 per year in incremental burden. Informal care was the largest burden component for people ages 0-18 years, reduced labor force participation for people ages 19-64 years, and NH costs for people ages 65+ years. New York, Connecticut, Massachusetts, Rhode Island, and Vermont experienced the highest costs per person with VL. Sensitivity analyses indicate total burden may range between $76 and $218 bn depending on assumptions used in the model.
Self-reported VL imposes a substantial economic burden on the US. Burden accrues in different ways at different ages, leading to state differences in the composition of per-person costs based on their VL population’s age composition. Information on state variation can help local decision-makers better target resources to address the burden of VL.

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