The Economic Burden of Vision Loss and Blindness in the United States

doi:10.1016/j.ophtha.2021.09.010

Ophthalmology

Volume 129, Issue 4, April 2022, Pages 369-378

https://doi.org/10.1016/j.ophtha.2021.09.010 Get rights and content

Purpose

To estimate the economic burden of vision loss (VL) in the United States and by state.

Design

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, and National Health Interview Survey [NHIS]) using attributable fraction, regression, and other methods to estimate the incremental direct and indirect 2017 costs of VL.

Participants

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.

Main Outcome Measures

We estimated the direct costs of medical, nursing home (NH), and supportive services and the indirect costs of absenteeism, lost household production, reduced labor force participation, and informal care by age group, sex, and state in aggregate and per person with VL.

Results

We estimated an economic burden of VL of $134.2 billion: $98.7 billion in direct costs and $35.5 billion in indirect costs. The largest burden components were NH ($41.8 billion), other medical care services ($30.9 billion), and reduced labor force participation ($16.2 billion), all of which accounted for 66% of the total. Those with VL incurred $16 838 per year in incremental burden. Informal care was the largest burden component for people 0 to 18 years of age, reduced labor force participation was the largest burden component for people 19 to 64 years of age, and NH costs were the largest burden component for people 65 years of age or older. 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 billion depending on the assumptions used in the model.

Conclusions

Self-reported VL imposes a substantial economic burden on the United States. Burden accrues in different ways at different ages, leading to state differences in the composition of per-person costs based on the age composition of the population with VL. Information on state variation can help local decision makers target resources better to address the burden of VL.

Section snippets

Methods

Using the societal perspective and following an analytic framework used previously for diabetes, we estimated the 2017 direct and indirect costs and Social Security payments associated with VL for each state and Washington, DC.⁷ Social Security payments are not included in the burden total and are reported as separate costs. We use a top-down approach for the direct costs of medical and NH services and the indirect costs of productivity losses, and we use bottom-up methods for the direct costs

Total Burden

We estimated the total economic burden of VL in the United States at $134.2 billion in 2017: $98.7 billion in direct costs and $35.5 billion in indirect costs (Table 2). The largest burden components were NH care ($41.8 billion), other medical care ($30.9 billion), and reduced labor force participation ($16.2 billion), all of which accounted for 66% of the total. Other medical care, which included the costs of eyeglasses, contact lenses, and home health care services, accounted for 23% of the

Discussion

We estimated an economic burden of VL of $134.2 billion ($98.7 billion in direct costs and $35.5 billion in indirect costs) for the United States population in 2017. State variations in total burden were driven primarily by state population size and age composition. Variations in per-person costs were associated with differences in NH costs and, to a lesser extent, medical and productivity costs. Our estimate was most sensitive to the specification of the econometric model to estimate

Acknowledgments

The authors thank Dr. Minchul Kim for his helpful review and comments.

References (32)

W.A. Monaco et al.
Prevalence of vision loss and associations with age-related eye diseases among nursing home residents aged ≥ 65 years
J Am Med Dir Assoc
(2021)
Vision and Eye Health Surveillance System (VEHSS)
A.D. Flaxman et al.
Prevalence of visual acuity loss or blindness in the US: a Bayesian meta-analysis
JAMA Ophthalmol
(2021)
J.S. Wittenborn et al.
Cost of vision problems: the economic burden of vision loss and eye disorders in the United States
D.B. Rein et al.
The economic burden of major adult visual disorders in the United States
Arch Ophthalmol
(2006)
K.D. Frick et al.
Economic impact of visual impairment and blindness in the United States
Arch Ophthalmol
(2007)
S. Vitale et al.
Prevalence of visual impairment in the United States
JAMA
(2006)
S.S. Shrestha et al.
Economic costs attributable to diabetes in each U.S. state
Diabetes Care
(2018)
Diabetes state burden toolkit technical report
M.K. Chapko et al.
Equivalence of two healthcare costing methods: bottom-up and top-down
Health Econ
(2009)

Consumer price index (CPI) databases

American Community Survey response rates

2017 National Health Interview Survey (NHIS) public use data release, survey description

MEPS-HC panel design and collection process

MEPS-HC response rates by panel

National Health Expenditure Accounts: methodology paper, 2019: definitions, sources, and methods

Cited by (38)

Modeling complex age-related eye disease
2024, Progress in Retinal and Eye Research
Modeling complex eye diseases like age-related macular degeneration (AMD) and glaucoma poses significant challenges, since these conditions depend highly on age-related changes that occur over several decades, with many contributing factors remaining unknown. Although both diseases exhibit a relatively high heritability of >50%, a large proportion of individuals carrying AMD- or glaucoma-associated genetic risk variants will never develop these diseases. Furthermore, several environmental and lifestyle factors contribute to and modulate the pathogenesis and progression of AMD and glaucoma.
Several strategies replicate the impact of genetic risk variants, pathobiological pathways and environmental and lifestyle factors in AMD and glaucoma in mice and other species. In this review we will primarily discuss the most commonly available mouse models, which have and will likely continue to improve our understanding of the pathobiology of age-related eye diseases. Uncertainties persist whether small animal models can truly recapitulate disease progression and vision loss in patients, raising doubts regarding their usefulness when testing novel gene or drug therapies. We will elaborate on concerns that relate to shorter lifespan, body size and allometries, lack of macula and a true lamina cribrosa, as well as absence and sequence disparities of certain genes and differences in their chromosomal location in mice.
Since biological, rather than chronological, age likely predisposes an organism for both glaucoma and AMD, more rapidly aging organisms like small rodents may open up possibilities that will make research of these diseases more timely and financially feasible. On the other hand, due to the above-mentioned anatomical and physiological features, as well as pharmacokinetic and -dynamic differences small animal models are not ideal to study the natural progression of vision loss or the efficacy and safety of novel therapies. In this context, we will also discuss the advantages and pitfalls of alternative models that include larger species, such as non-human primates and rabbits, patient-derived retinal organoids, and human organ donor eyes.
Prevalence and Risk Factors of Blindness Among Primary Angle Closure Glaucoma Patients in the United States: An IRIS Registry Analysis
2024, American Journal of Ophthalmology
To assess the prevalence and risk factors of blindness among patients newly diagnosed with primary angle closure glaucoma (PACG) in the United States.
Retrospective cross-sectional study.
Eligible patients from the American Academy of Ophthalmology (AAO) Intelligent Research in Sight (IRIS) Registry had newly diagnosed PACG, defined as: 1) observable during a 24-month lookback period from index date of PACG diagnosis; 2) no history of eye drops, laser, or cataract surgery unless preceded by a diagnosis of anatomical narrow angle (ANA); and 3) no history of glaucoma surgery. Logistic regression models were developed to identify risk factors for any (one or both eyes) or bilateral (both eyes) blindness (visual acuity ≤20/200) at first diagnosis of PACG.
Among 43,901 eligible patients, overall prevalence of any and bilateral blindness were 11.5% and 1.8%, respectively. Black and Hispanic patients were at higher risk of any (odds ratios [ORs] 1.42 and 1.21, respectively; P < .001) and bilateral (ORs 2.04 and 1.53, respectively; P < .001) blindness compared with non-Hispanic White patients adjusted for ocular comorbidities. Age <50 or >80 years, male sex, Medicaid or Medicare insurance product, and Southern or Western practice region also conferred a higher risk of blindness (OR > 1.28; P ≤ .01).
Blindness affects 1 of 9 patients with newly diagnosed PACG in the IRIS Registry. Black and Hispanic patients and Medicaid and Medicare recipients are at significantly higher risk. These findings highlight the severe ocular morbidity among patients with PACG and the need for improved disease awareness and detection methods.
Vision Need Profiles for the City of Richmond, Virginia: A Pilot Application of Calibration Methods to Vision Surveillance
2024, Ophthalmology Science
People with vision problems (VPs) have different needs based on their age, economic resources, housing type, neighborhood, and other disabilities. We used calibration methods to create synthetic data to estimate census tract-level community need profiles (CNPs) for the city of Richmond, Virginia.
Cross-sectional secondary data analysis.
Anonymized respondents to the 2015 to 2019 American Community Survey (ACS).
We used calibration methods to transform the ACS 5-year tabular (2015–2019) and Public Use Microdata estimates into a synthetic data set of person-level records in each census tract, and subset the data to persons who answered yes to the question “Are you blind or do you have serious difficulty seeing even when wearing glasses?” To identify individual need profiles (INPs), we applied divisive clustering to 17 variables measuring individual demographics, nonvision disability status, socioeconomic status (SES), housing, and access and independence. We labeled tracts with CNP names based on their predominant INPs and performed sensitivity analyses. We mapped the CNPs and overlayed information on the number of people with VP, the National Walkability Index, and an uncertainty measure based on our sensitivity analysis.
Individual need profiles and CNPs.
Compared with people without VP, people with VP exhibited higher rates of disabilities, having low incomes, living alone, and lacking access to the internet or private home vehicles. Among people with VP, we identified 7 INP clusters which we mapped into 6 CNPs: (1) seniors (≥ age 65); (2) low SES younger; (3) low SES older; (4) mixed SES; (5) higher SES; and (6) adults and children in group quarters. Three CNPs had lower-than-average walkability. Community need profile assignments were somewhat sensitive to calibration variables, with 18 tracts changing assignments in 1 sensitivity analysis, and 4 tracts changing assignments in ≥ 2 sensitivity analyses.
This pilot project illustrates the feasibility of using ACS data to better understand the support and service needs of people with VP at the census tract level. However, a subset of categorical CNP assignments were sensitive to variable selection leading to uncertainty in CNP assignment in certain tracts.
The author(s) have no proprietary or commercial interest in any materials discussed in this article.
Micromolded honeycomb scaffold design to support the generation of a bilayered RPE and photoreceptor cell construct
2023, Bioactive Materials
Age-related macular degeneration (AMD) causes blindness due to loss of retinal pigment epithelium (RPE) and photoreceptors (PRs), which comprise the two outermost layers of the retina. Given the small size of the macula and the importance of direct contact between RPE and PRs, the use of scaffolds for targeted reconstruction of the outer retina in later stage AMD and other macular dystrophies is particularly attractive. We developed microfabricated, honeycomb-patterned, biodegradable poly(glycerol sebacate) (PGS) scaffolds to deliver organized, adjacent layers of RPE and PRs to the subretinal space. Furthermore, an optimized process was developed to photocure PGS, shortening scaffold production time from days to minutes. The resulting scaffolds robustly supported the seeding of human pluripotent stem cell-derived RPE and PRs, either separately or as a dual cell-layered construct. These advanced, economical, and versatile scaffolds can accelerate retinal cell transplantation efforts and benefit patients with AMD and other retinal degenerative diseases.
Losing, preserving, and restoring vision from neurodegeneration in the eye
2023, Current Biology
The retina is a part of the brain that sits at the back of the eye, looking out onto the world. The first neurons of the retina are the rod and cone photoreceptors, which convert changes in photon flux into electrical signals that are the basis of vision. Rods and cones are frequent targets of heritable neurodegenerative diseases that cause visual impairment, including blindness, in millions of people worldwide. This review summarizes the diverse genetic causes of inherited retinal degenerations (IRDs) and their convergence onto common pathogenic mechanisms of vision loss. Currently, there are few effective treatments for IRDs, but recent advances in disparate areas of biology and technology (e.g., genome editing, viral engineering, 3D organoids, optogenetics, semiconductor arrays) discussed here enable promising efforts to preserve and restore vision in IRD patients with implications for neurodegeneration in less approachable brain areas.
Cost-effectiveness of Prophylactic Laser Peripheral Iridotomy in Primary Angle-Closure Suspects
2023, Ophthalmology Glaucoma
To investigate the cost-effectiveness (CE) of prophylactic laser peripheral iridotomy (LPI) in primary angle-closure (PAC) suspects (PACSs).
Cost-effectiveness analysis utilizing Markov models.
Patients with narrow angles (PACSs).
Progression from PACSs through 4 states (PAC, PAC glaucoma, blindness, and death) was simulated using Markov cycles. The cohort entered at 50 years and received either LPI or no treatment. Transition probabilities were calculated from published models, and risk reduction of LPI was calculated from the Zhongshan Angle Closure Prevention trial. We estimated costs of Medicare rates, and previously published utility values were used to calculate quality-adjusted life year (QALY). Incremental CE ratios (ICER) were evaluated at $50 000. Probabilistic sensitivity analyses (PSAs) addressed uncertainty.
Total cost, QALY, and ICER.
Over 2 years, the ICER for the LPI cohort was > $50 000. At 6 years, the LPI cohort was less expensive with more accrued QALY. In PSA, the LPI arm was cost-effective in 24.65% of iterations over 2 years and 92.69% over 6 years. The most sensitive parameters were probability of progressing to PAC and cost and number of annual office visits.
By 6 years, prophylactic LPI was cost-effective. The rate of progressing to PAC and differing practice patterns most impacted CE. With uncertainty of management of narrow angles, cost may be a decision management tool for providers.
The authors have no proprietary or commercial interest in any materials discussed in this article.

View all citing articles on Scopus

: Supplemental material available at www.aaojournal.org.

: Disclosure(s):

: All authors have completed and submitted the ICMJE disclosures form.

: The author(s) have no proprietary or commercial interest in any materials discussed in this article.

: Supported by the Vision Health Initiative of the Centers for Disease Control and Prevention, Atlanta, Georgia (contract no.: 200-2014-61264-0006, “Developing an Online Toolkit to Estimate State Specific Economic Burdens Attributable to Vision Loss and Eye Diseases in the United States”). The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention.

: HUMAN SUBJECTS: No human subjects were included in this study. The NORC Institutional Review Board acknowledges that this study does not require IRB review. All research adhered to the tenets of the Declaration of Helsinki.

: No animal subjects were included in this study.

: Author Contributions:

: Conception and design: Rein, Wittenborn, Zhang, Ahmed, Saaddine

: Analysis and interpretation: Rein, Wittenborn, Zhang, Ahmed, Lundeen, Saaddine

: Data collection: Rein, Wittenborn, Ahmed, Lamuda

: Obtained funding: N/A; Study was performed as part of regular employment duties for the CDC coauthors; the NORC coauthors were under contract.

: Overall responsibility: Rein, Wittenborn, Zhang, Ahmed, Lundeen, Saaddine

View full text

Original ArticleThe Economic Burden of Vision Loss and Blindness in the United States

Purpose

Design

Participants

Main Outcome Measures

Results

Conclusions

Section snippets

Methods

Total Burden

Discussion

Acknowledgments

J Am Med Dir Assoc

Vision and Eye Health Surveillance System (VEHSS)

Prevalence of visual acuity loss or blindness in the US: a Bayesian meta-analysis

JAMA Ophthalmol

Cost of vision problems: the economic burden of vision loss and eye disorders in the United States

The economic burden of major adult visual disorders in the United States

Arch Ophthalmol

Economic impact of visual impairment and blindness in the United States

Arch Ophthalmol

Prevalence of visual impairment in the United States

JAMA

Economic costs attributable to diabetes in each U.S. state

Diabetes Care

Diabetes state burden toolkit technical report

Equivalence of two healthcare costing methods: bottom-up and top-down

Health Econ