Reallocating Work in Ophthalmology: A Health Economic Agenda in Anticipation of a Future Workforce Shortfall

Ophthalmology has become one of the highest-value areas in health care. Cataract surgery, refractive correction, and management of diabetic eye disease and age-related macular degeneration (AMD) yield large gains in quality of life at relatively low cost. Global analyses estimate median benefit–cost ratios of roughly 20 to 36:1 for basic eye health interventions, especially refractive services and cataract surgery in low- and middle-income countries.¹ Yet in many health systems, the ability to realize that value is constrained less by technology than by people.

In the United States, ophthalmology is projected to have the second-worst workforce adequacy among 38 medical specialties over the coming decade. Using a federal workforce simulation model, Berkowitz et al² estimated that by 2035, ophthalmology supply will have declined 12%, whereas demand will have risen 24%, resulting in a workforce adequacy of about 70% overall and roughly 30% in nonmetropolitan areas. This is not only a numerical shortfall but also a distribution problem: even modest national gains can leave rural and underserved communities behind if clinicians and diagnostic infrastructure remain concentrated in urban centers. In parallel, vision impairment in the United States is estimated to generate over $130 billion annually in societal costs, including both supportive services and reduced productivity, underscoring the macroeconomic stakes of failing to deliver proven eye care at scale.³

Taken together, these data suggest that the central economic question for ophthalmology is not only which drugs or devices are cost-effective, but also how we design teams so that ophthalmologists can deliver high-value care at scale. Any effort to redesign care teams must also protect the physician–patient relationship: continuity, clear accountability, and trust are inputs into adherence and outcomes, not optional extras.

In most economic evaluations, the ophthalmologist appears only as an implicit input—a generic “provider cost” folded into fee schedules or time-driven activity-based costing. In practice, an ophthalmologist’s productivity and the value they generate are heavily contingent on the composition and deployment of the care team. Emerging evidence shows that trained ophthalmic technicians, nurses, and optometrists routinely perform pretesting, imaging, elements of counseling, and protocolized follow-up, whereas digital tools can help support triage, monitoring, and patient education. When these roles are well organized, 1 ophthalmologist can safely supervise care for many more patients than in a physician-centric model; when they are absent or underused, ophthalmologists may spend large portions of clinic time on tasks that others could perform. In doing so, they also cede bandwidth for surgery and complex decision-making, limiting access and blunting the value of new therapies.

At the same time, delegation can fragment care if patients experience a revolving door of personnel or unclear responsibility for decisions. High-value teams, therefore, need relational safeguards: explicit “named clinician” accountability, warm handoffs, and low-friction escalation back to an ophthalmologist when uncertainty, high-stakes choices, or distress are present.

From a health economic standpoint, treating personnel as a fixed backdrop misses this opportunity cost: with a constrained workforce, the marginal value of adding 1 more ophthalmologist depends critically on the team into which they are deployed. Moreover, given the favorable benefit–cost ratios of ophthalmic interventions and because workforce shortages are projected to disproportionately affect nonmetropolitan areas,² failing to organize teams effectively is not just a staffing problem but a misallocation of one of the health system’s highest-value resources. Technology-enabled and team-based models could extend specialty oversight into underserved settings, but they could also widen disparities if broadband access, clinic staffing, language support, and referral completion are uneven; equity effects should be measured rather than assumed.

Although the evidence base is still limited and context-specific, empirical work shows that reallocating standardized tasks can maintain outcomes while freeing specialist time and, in some cases, reduce costs.

Diabetic retinopathy screening offers a clear example. Building on earlier teleophthalmology programs, Hu et al⁴ modeled multiple scenarios for artificial intelligence–based diabetic retinopathy screening in Australian primary care. Across all scenarios, artificial intelligence–enabled screening was more effective and less costly than current practice, preventing thousands of cases of vision impairment; ophthalmologist time was reserved for patients flagged as needing treatment or complex evaluation.

Similar dynamics appear in AMD and glaucoma. In an economic evaluation of home-based AMD monitoring for high-risk patients, Wittenborn et al⁵ reported incremental cost-effectiveness ratios around $35 663 per quality-adjusted life year gained, whereby earlier detection of choroidal neovascularization and fewer unnecessary in-person visits shifted costs from clinic-based encounters to remote technology without sacrificing visual outcomes. In glaucoma, technician- or optometrist-led virtual clinics with consultant “back-end” review have shown that many low-risk patients can be managed safely without face-to-face visits; at one UK tertiary center, a technician-delivered triage clinic discharged 62% of new referrals after virtual review, with a negative predictive value of 96% for those deemed safe to discharge.⁶

• If workforce configuration is a first-class determinant of value in eye care, what should researchers, clinicians, and policymakers prioritize?

First, economic evaluations should make team composition explicit. Cost-effectiveness studies of new diagnostics, treatments, and service innovations should specify the assumed mix of ophthalmologists, optometrists, technicians, and nurses; estimate the impact of that mix on throughput (patients or procedures per ophthalmologist full-time equivalent); and explore regional scenarios reflecting differences in workforce adequacy. Sensitivity analyses should compare physician-centric models with technician- or optometrist-heavy models and report how incremental cost-effectiveness ratios or benefit–cost ratios change under each assumption. The key point is that the same intervention can appear more or less cost-effective depending on team composition. Journals and health technology assessment bodies could accelerate this shift by asking authors to report staffing assumptions and, where possible, to present sensitivity analyses as mentioned earlier.

Second, health systems should prioritize trials and implementation studies that compare delivery models, not just therapies, with embedded economic evaluation. Diabetic retinopathy screening programs, home AMD monitoring, and glaucoma virtual clinics already demonstrate the feasibility of comparing different team and technology configurations.4, 5, 6 Future studies should capture detailed personnel time, training, and infrastructure costs and, where feasible, patient and caregiver time, not just clinic-level budgets. Because these models change who patients interact with, studies should also include patient-reported experience measures (communication, trust, and perceived continuity) alongside utilization and safety outcomes. Implementation studies should report access and outcomes stratified by rurality and socioeconomic status (and, where possible, race/ethnicity and insurance type), including wait times, travel burden, and treatment uptake. These analyses could then inform payment models—such as bundled episodes of eye care and quality measures that are agnostic to internal staffing—so that reimbursement rewards high-value team configurations rather than physician volume alone.

Third, the allied workforce and patient time should be treated as explicit economic levers. Social return-on-investment analyses of nonprofit cataract surgery services, for example, have estimated benefit–cost ratios well above 10:1 for programs that restore vision and productivity.⁷ Given the long lead time for ophthalmologist training and the projected workforce deficit, training pipelines for ophthalmic technicians and optometrists, as well as redesign of workflows to reduce travel and waiting time, deserve the same economic scrutiny as new drugs or devices. Practically, this can be approached with (1) time-driven costing of personnel inputs (minutes per role per visit, plus training/overhead amortized across volume) and (2) explicit nonmedical time costs estimated from travel distance, visit frequency, and waiting time (using wage-based valuation or replacement-cost assumptions), reported alongside 1-way and probabilistic sensitivity analyses so readers can see how results change under different time-value assumptions. In a field where much of the burden falls on patients’ and caregivers’ time,^3,5 delivery models that reduce nonmedical costs are likely to be strongly favored when evaluated from a societal perspective. The goal is not to eliminate assumptions, but to surface them transparently so that decision makers can judge whether a model’s conclusions are robust to plausible ranges of patient and caregiver time burden.

Ophthalmology is at an inflection point where value is constrained less by new science than by how we deploy the people we already have. Proven interventions such as cataract surgery, spectacle correction, diabetic retinopathy treatment, and AMD management are among the best buys in health, yet workforce constraints mean many patients still cannot access them in time. The next generation of health economic work in ophthalmology should therefore investigate not only whether a therapy is cost-effective but which team configuration of a given care model yields the greatest health and economic gain per ophthalmologist full-time equivalent.

Answering that question will require closer collaboration among ophthalmologists, health economists, workforce planners, and patient advocates. The payoff is substantial: more vision preserved, more independence maintained, and more societal benefit created per unit of scarce specialist time.