Abstract
According to recent studies, visual problems represent one of the top contributors to economic health burden in the United States. This burden is divided nearly equally between direct expenditures for the care and treatment of visual problems, and the indirect costs of outcomes caused by low vision, including productivity losses, the cost of care, and incremental nursing home placements. A large amount of academic research is devoted to visual science, the biology of the visual system, and the medical treatment of visual disorders. Compared to the burden, a disproportionate share of this research is devoted to the study of retinal disorders and glaucoma. This is understandable, as research into the retina and optic nerve has the potential to unlock fundamental insights into the nature of sight and visual cognition. However, population visual health and the functionality that depends upon it also may benefit greatly from additional research into areas of prevention, rehabilitation, and adaptation. In addition, comparative research into the benefits of resource allocation across prevention, treatment, and rehabilitative resources could lead to improvements in population health.
Visual disorders represent one of the most important sources of economic medical costs in the United States. A recent study released by Prevent Blindness America (PBA) estimated the burden of visual problems at $139 billion annually in 2013, with direct medical costs representing $65.1 billion of the total burden. According to this estimate, the direct medical costs of visual problems is one of the leading sources of medical expenditures in the United States, possibly exceeded only by heart conditions, trauma, cancer, and mental health disorders.
1,2 Visual problems also are associated with substantial indirect costs, many of which may be preventable through earlier or better detection and treatment, or through efforts to provide rehabilitative and support services to those with visual impairment and blindness.
The new estimation of the size of the economic impact of visual problems provides the opportunity to evaluate options and methods to focus research, treatment, and rehabilitative efforts to ameliorate the impact of visual impairment in the US population. The fields of health economics, outcomes, and operations research can help with decision making and resource prioritization by relating choices and investments to the potential quality and quantity of vision they produce, the degree of independent functioning they enable, or the insights and scientific information they may generate.
To suggest possible directions for future economic work in the field of visual health, this article reviews new estimates of the burden of visual problems and the causes of this burden. It then relates this burden to research efforts in the field to compare how current research maps to burden. Next, the article discusses the different uses of economic studies at different phases of the policy process, and compares existing economic research in the visual health field to those categories. Finally, the article concludes with some possible suggestions for prioritizing future economic research.
The most comprehensive estimate of the burden of visual disorders comes from a recently released Prevent Blindness America study that estimated the economic burden of visual problems in the United States. According to this study, the burden of visual disorders represents one of the largest health care expenditure categories in the country, costing the US economy approximately $139 billion annually.
1 Of these costs, direct costs accounted for 48% of the economic burden of visual problems and indirect costs accounted for 52%. It is instructive to consider what conditions and services were responsible for the majority of this burden. The study was able to allocate only the $65.1 billion associated with direct medical costs (the majority of direct costs) to individual disorders. Of direct medical costs, the study found that refractive error produced the greatest aggregate direct medical burden (24.7%), followed by cataract (16.4%), diagnosed visual impairment and blindness (16.0%), physical disorders (13.7%), disorders of the retina (13.4%), glaucoma and disorders of the optic nerve (8.9%), and other visual problems (6.9%). The major drivers of indirect costs, which the study did not allocate to individual disorders, were incremental nursing home placements and productivity losses.
Understanding how scientific research maps to the drivers of burden can help us understand how current research priorities roughly map to areas of economic consequence. To develop a measure of scientific volume, I compiled PubMed search results related to the visual sciences and used these results to estimate the number of articles in each general visual health condition area. I then compared research volume to drivers of direct medical costs as estimated in the PBA study.
1,3
To do so, I first created a list of search terms associated with the topic areas of “Cataract,” “Glaucoma,” “Ocular Physical Disorders,” “Other Vision Problems,” “Refractive Error,” “Retinal Disorders,” and “Vision Problems and Blindness” (
Supplementary Appendix A), and their associated Medical Subject Headings (MeSH), and created an inclusive search for articles referenced by PubMed using these terms over the last five years (July 5, 2008 to July 3, 2013). This search resulted in an aggregate total of 134,582 articles related to visual science over the last five years. A cursory quality check of these results indicated that, while a few references were tangential or unrelated, the majority of articles did include some reference to or research regarding a visual science topic. As a further limitation, this search likely also omitted some relevant articles that were not captured directly by one of the search terms. However, given the review and commentary nature of this article, this study accepted the list of 134,582 articles as an adequate, if rough, measure of visual science research priorities over the last five years.
To allocate these articles to individual conditions, I next searched within this restricted list to identify the number of articles that referenced each condition. Article identification was not mutually exclusive in that a single article could be counted in more than one topic area if it contained references to multiple condition categories. This generated a list of the aggregate number of articles that discussed each condition area over the last five years (
Table 1). Following article identification, the number of articles in each topic area was divided by the total number of articles identified using all terms to identify the percentage of total articles in which the topic was mentioned.
Table 1 compares each visual condition's percentage contribution to direct medical costs to its percentage contribution to scientific articles over the last five years.
Table 1 also shows the ratio of the percentage of articles to the percentage of direct medical costs. When viewed in this manner, the areas of refractive error and cataract generated a lower proportion of scientific articles compared to what would be expected if articles were driven purely proportionally by direct medical costs. Likewise, the areas of retinal disorders and glaucoma generated a larger proportion of articles as did “Other vision problems,” which included all ocular research other than the visual disorders listed. Vision problems and ocular physical disorders generated articles in proportion to their burden.
This rough measure is descriptive in nature and is not meant to be taken as a proscriptive recommendation to study more or less in certain areas. Studies directed toward the retina, the causes of glaucoma, and the functioning and impairment of the optic nerve represent fundamental areas of remaining mystery in the visual sciences. Unlocking the secrets of these systems may result in paradigm shifting breakthroughs in our understanding of vision, aging, and cognition. At the same time, the results are suggestive that certain areas of visual dysfunction may warrant additional attention. Also clear is that the indirect consequences of visual disorders often are overlooked within these articles on visual health. For example, searching within the 134,582 articles for the term “Rehabilitation” resulted in 3191 articles, searching within these articles for “Productivity” resulted in 1935 articles, and searching within these results for “Long Term Care,” “Nursing Home,” or “Skilled Nursing Facility” resulted in only 670 articles.
A number of types of health economic studies potentially could help rationalize and direct the flow of visual health resources towards the areas that are most likely to increase the quality of visual health, and to mitigate or reduce the burden of visual disease. Different types of economic studies are appropriate at different stages of the health care policy process (
Table 2). In the formative stage of policy, economic burden studies can help describe the magnitude of a condition compared to other problems, health valuation studies can assign comparative utility values to morbidity from a condition, and value of information research can help identify where specific research investments potentially can yield the greatest benefits.
Several excellent examples of each type of work have been reported over the last five years. For example, Wittenborn and Rein estimated the burden of visual disorders among those in the United States who were younger than age 40.
4 Wittenborn et al. also estimated the PBA study discussed above.
1 In an extremely important study, Tahhan et al. established and quantified the utility impact of uncorrected refractive error, a finding that should elevate the importance of interventions for this condition.
5 Although value of information research has been used rarely in the visual sciences, Karnon et al. demonstrated its potential in an analysis of how additional research on the utility impact of monocular visual impairment could alter decisions to disinvest in amblyopia screening programs in the United Kingdom.
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In the deliberative stage of policy analysis, cost–utility and cost–benefit studies are of use in determining the relative value of new interventions or health technologies to address visual problems; actuarial or insurance studies illustrate how changes in medical recommendations can impact payers, and how these costs can be managed over time; and resource allocation studies can be used to optimize desired outcomes (e.g., days of healthy vision) given several cost-effective, but also costly visual interventions. As with formative studies, excellent work has been conducted in these areas over the last five years, primarily in the area of cost–utility analysis. Crane et al. used an advanced simulation and primary data sources to provide objective evidence on the relative cost-effectiveness of different treatment decisions for patients with glaucoma in Australia.
7 Gower et al. used cost–utility analysis to demonstrate that ranibizumab was a cost-effective alternative to either pegaptanib or photodynamic therapy in the treatment of AMD-related choroidal neovascularization.
8 Rein et al. used an agent-based model of six different eye disorders to argue that universal dilated eye evaluations at Medicare entry was a cost-effective policy that should be pursued.
9 Compared to cost–utility work, work on financing care for visual conditions or on allocating resources across visual interventions was sparse, although a few good examples were identified.
10,11
In the action stage of policy, economic research can assist with the identification of best practices across divergent implementation methods, to identify the aggregate and marginal production costs of health services, and to determine the financial return on investments in new practices or technologies to different payers. Many strong examples of economic evaluations of implementation work have been published over the last five years. For example, Li et al. estimated the implementation cost of telemedicine monitoring for diabetic retinopathy in a federally qualified health center compared to the costs that would have been experienced if the same patients had received a retinal exam by an eye care professional.
12 Beauchamp et al. used a return on investment approach to argue for the value and importance of investments to improve childhood amblyopia screening programs.
13 Also in the field of amblyopia screening, Rein et al. estimated the implementation costs of three state screening programs,
14 and Longmuir et al. used cost-assessment methods to measure the programmatic costs of photo screening methods.
15 Vinekar et al. collected primary data on the implementation costs of retinopathy of prematurity screening in India to demonstrate best practices and the feasibility of expanded implementation of simple programs that can save vision in the developing world.
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Current Needs and Future Directions for Economic Research in the Field of Visual Science
Despite the outstanding economic work that has been published in the field of visual sciences, opportunities exist to expand the generalized uses of economic and financial concepts in the management of research and prevention dollars related to visual health. Primary areas of opportunity include using value of information (VOI) methods to prioritize research, taking a portfolio perspective to funding research, and finally developing resource allocation models around visual objective functions of interest in an effort to prioritize research, prevention, and treatment dollars. In addition, efforts to use systematic reviews to determine best practices and preferred practice patterns to standardize care around quality standards have the potential to improve the quality of care and lower costs.
VOI refers to a series of methods developed in the decision sciences and used to quantify the value of additional research to reduce uncertainty regarding specific decisions. In generalized terms, VOI methods account for the size or economic burden of a problem, the degree to which a problem could be mitigated through action, and the cost of that action, and the level of uncertainty regarding a decision to take action. Several factors contribute to a larger VOI for a specific problem, action, or decision. For example, problems with higher burden, problems that currently or potentially can be solved, problems with costlier solutions, and problems where the outcome of a treatment or intervention is uncertain all are more likely to result in a higher VOI gained from research conducted in the area.
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VOI calculations could be used to justify the need for research much in the same way power calculations are now used to justify that research has the ability to capture the relevant effect size. Research could be prioritized based on objective criteria regarding the nature of information sought, its uses to other scientists or policy makers, the level of uncertainty in specific parameters regarding the phenomena, and the burden of a phenomenon to be studied.
For example, in the visual sciences, in 2009 a Cochrane Review concluded that no systematic evidence existed to demonstrate the utility impact of amblyopic monocular blindness on patient utility, and without such evidence the cost-effectiveness of widely adopted amblyopia school screening programs could not be established.
18 Cost-effectiveness analyses identified utility losses from monocular visual loss as the driving factor in determining the cost-effectiveness of amblyopia screening programs and recommended additional research into this parameter.
14,19 Concurrent VOI analyses estimated that research on utility losses from monocular vision loss were valued at as much as £45 million in England and Wales (equivalent 2012 value of $355 million in the United States after adjusting this figure for inflation, currency exchange rates, and larger population size in the United States) in terms of the information's ability to guide optimal policy decisions.
19 Such concrete information on potential quantitative benefit of proposed research studies could be used to prioritize clinical trial development around policy needs and information gaps.
Some bench scientists may recoil in horror at the idea that new scientific research must always be judged based solely on its monetized value in shaping today's policies or treatment protocols. Many scientific questions may not be connected easily to immediate shifts in policy. Science directed at today's most pressing problems or questions will always appear to be a high priority, but without investments in basic science we may never achieve the breakthroughs that drive the evolution of visual science.
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Funders of research can address the conflict between immediate medical and decision-making needs, and investments in the future by taking a portfolio approach to their research funding. In the same way that smart financial investors will diversify their investments among different vehicles, funders of research can diversify their investments into research. Such funders can allocate research resources explicitly among a few large scale, established research investments likely to yield important, but incremental knowledge tied directly to current known policy or scientific needs, and many smaller more speculative investments in less orthodox ideas. Examples of criteria that can be used to evaluate appeals for scientific support include the potential near term impact on the quality and quantity of vision experienced by the population, the impact of the condition on economic burden, the relative need for research in an area, the level of innovation or novelty of a research idea, and finally the transformational potential of the research. By spreading money across these priority areas while making sure to invest in each, the funding agency can assure annual incremental progress through sound and safe investments, while also allowing opportunity for the development of new transformational information.
Resource allocation models offer another area of possible opportunity for the field of health economics to contribute to vision research. In general terms, resource allocation models refer to any system (usually a set of linear equations) that attempts to distribute finite resources among alternative uses in a manner that maximizes a given output. Resource allocation models can help policy makers in visual health think about investments that maximize one of several outcomes of relevance. Such models could focus on maximizing the quantity and quality of visual perception experienced across a target population, minimizing the functional impacts of visual impairments, or some combination of both outcomes.
Currently, medical resources in visual health are allocated across multiple conditions based primarily on disease prevalence and the availability of medical treatment technologies. Whether treated or untreated, these conditions result in visual consequences such as annual productivity losses and incremental nursing home placements whose annual costs exceed those of medical treatment.
1 Resource allocation models can help think through questions of new investments in resources and research in a way that minimizes the negative consequences of disease. Research allocation models have been developed in fields such as cancer, human immunodeficiency virus (HIV), and tuberculosis treatment and prevention, although their overall use in health care is rare.
21–23 Such models are ideal for visual health because multiple conditions and circumstances affect a common functional system; human vision and the activities that depend on it.
Recent economic research suggests that the cumulative direct medical costs of vision problems rival the burden of other major medical conditions, such as cancer, heart disease, diabetes, and mental health.
1,2 In addition to direct medical costs, visual problems also are responsible for an equal to slightly greater burden in the form of productivity losses, costs of informal care, and incremental nursing home placements. If the utility losses from visual losses could be monetized to reflect their personal toll on well-being and happiness, the costs of visual problems would be greater still.
Much of the burden of visual disorders potentially could be mediated through at least the three avenues: Prevention and diagnostic screening, medical treatment of diagnosed conditions, and rehabilitation and support services for those with visual impairment. Annually, tens of thousands of articles across these areas are published discussing medical, policy, and economic aspects of visual problems. Despite this excellent and growing body of work, insufficient research is directed toward comparative research across conditions and across domains of service. For example, research comparing the population benefits of investments in medical treatments for those with vision-threatening disease compared to rehabilitation and adaptive services for those who have previously-acquired impairment is virtually nonexistent. Research to determine comparatively which strategies and practices maximize the population's quality and quantity of vision, and minimize the personal and familial impacts of visual impairment is needed to inform future allocations of resources in visual health. Additionally, work to communicate scientific achievements in the visual sciences in terms of gains in vision and decrements in disability, outcomes that the public understands, may help boost external support for visual health research that is commensurate with the economic burden of the field.
Supported by an unrestricted honorarium from the Ocular Research Symposium Foundation (ORSF).
Disclosure: D.B. Rein, None