The trend of rising medical costs is a concern for 21st-century ophthalmologists. By 2030, the youngest Baby Boomers will be 65 years or older.1 Approximately 1 in 10 Americans age 50 and over have at least an early form of age-related macular degeneration (AMD). Additionally, 1 out of every 100 Americans age 50 and older have the vision-threatening late-stage form of AMD. A growing aging population represents an increase in the prevalence of AMD, which has grown 2.75 times faster than predictions from 2011.2 AMD is associated with many cost burdens, including time, money, and quality of life. Financial costs of AMD start from around $8,814 to $23,400 per year, or $32,491 to $70,200 after 3 years of treatment.3
Early Detection
One way of minimizing the cost burdens of vision loss from AMD is through early detection of the conversion of dry (nonexudative) AMD to wet (exudative) AMD. Early detection allows for timely treatment interventions, which have been clinically shown to slow the progression of vision loss and preserve vision.4 Whether teacher, police, or accountant, nearly every societal occupation heavily depends on vision to fulfill its role. Thus, by improving methods for detecting early AMD and conversion from dry to wet macular degeneration, ophthalmologists may better preserve the collective vision to help reduce the economic burden caused by the disease.
Cost Effectiveness
Fluorescein angiography (FA) is considered the gold standard for detecting neovascular age-related macular degeneration (nAMD). Although using the most effective methods for detecting nAMD may seem logical, rising medical costs motivate ophthalmologists to think otherwise. The famous phrase, “getting the best bang for your buck,” comes to mind. In other words, accuracy and costs are equally crucial factors when choosing a diagnostic test.
In a typical ophthalmology clinic, various diagnostic tests are readily available to help detect conversion, including optical coherence tomography, fundus examination, Amsler grid, best-corrected visual acuity, and self-reported subjective visual changes. Quality-adjusted life years (QALYs) are commonly used to determine the cost-effectiveness of these tests.5
Besides only considering the quantitative cost of diagnostic tests, such as imaging and interpretations, QALYs also include hidden qualitative costs, such as patient’s subjective experience, daily activities, and mental wellness. A patient during a 25-year horizon may have perfect 20/20 vision; in that case, we assume the patient to have a QALY value of 25.
This is not the case for patients with vision deficits such as a scotoma secondary to AMD, which lead to lower QALYs. Analysts multiply the time horizon with the average utility value to account for this. This utility value is between 0 and 1, where a 1 may represent a patient with perfect vision, while a 0 may be used in cases of severe vision loss and blindness.
Detection of Wet Age-related Macular Degeneration
Hernandez et al estimated the expected QALYs and costs of 5 different index tests to evaluate which modality of detecting early conversion is the most cost effective.6 A Monte Carlo computational model, including 200,000 simulated patients, was used to replicate real-life monitoring, detection, and treatment of those with unilateral wet AMD. Each step was probabilistically determined using parameters based on past databases and studies, including the Early Detection of Neovascular Age-related Macular Degeneration (EDNA) study.7
Results showed spectral-domain optical coherence tomography (SD-OCT) generated a higher QALY (5.830) followed by fundus assessment (5.787), Amsler grid (5.736), patients’ subjective vision (5.630), and visual acuity (5.600). Healthcare-associated costs were also lower compared to other forms of detection, with SD-OCT costing a yearly average of £19,406 per patient ($24,681 in 2024 USD). This is likely due to the high sensitivity of SD-OCT to detect nAMD, allowing for earlier initiation of treatment.
Early initiation of treatment and continued monitoring by an ophthalmologist allows for preserving vision and reducing severe vision loss. Blindness is often associated with high social care costs and lower quality of life.
Limitations
Many computer-simulated studies, including Hernandez’s, heavily depended on prior data to emulate real-world systems. One challenge posed in these studies was determining the rate of vision loss after conversion without treatment. Given that most clinicians in the EDNA study treated patients before significant vision loss, extrapolated visual acuity loss for untreated patients was based on minimal data. However, this was acknowledged using conservative forecasting models to reduce the risk of overestimating vision loss in untreated eyes.
Clinical Implications
Hernandez’s study suggests that monitoring with SD-OCT, compared to the other monitoring tests available in the office, may reduce patient health-care costs by significantly reducing the time it takes to detect and treat conversion of dry AMD for those with unilateral nAMD. However, it is essential to note that the best method may include performing a fluorescein angiogram to confirm conversion in the event the OCT shows evidence of conversion of nonexudative AMD to exudative AMD. This was more cost effective and of equal efficacy compared to the initiation of anti-VEGF in the case of any positive OCT. Studies have supported the use of FA when OCT results do not clearly suggest conversion to wet AMD to reduce the risk of treating false positive OCT results.8,9
An earlier study also supported multimodality monitoring. The Medical Advisory Secretariat aimed to look at the cost-effectiveness of SD-OCT in detecting age-related macular degeneration in Ontario, Canada. Their model looked solely at the estimated difference in direct costs of AMD monitoring between physicians who use only FA vs multimodality monitoring with the addition of OCT. This study suggested the addition of OCT increased the direct cost by $1.2 million but is offset by savings of $8.3 million thanks to reducing the conventional need of 5 FA per year to only 3.10
Virtual Monitoring
Home monitoring devices have also been shown to be a cost-effective option for nAMD detection.11 Wittenborn et al evaluated the cost effectiveness of the first FDA-approved device, ForeseeHome, which conducts interactive 3-minute tests per eye to detect subtle visual field distortions caused by potential early choroidal neovascularization.12 Results suggested monitoring with ForeseeHome was more cost effective for patients with high-risk unilateral nAMD, because a reduction in adverse blindness or severe vision loss offset the monitoring cost.
Due to physician shortages, transportation burdens, and unmet needs in rural underserved communities, virtual monitoring with smartphones and artificial intelligence technology may become increasingly utilized by retinal specialists to monitor those with unilateral nAMD better.13
Ting et al developed a deep learning system to detect ocular diseases, including AMD, in a multiethnic population. Performance was compared against a panel of professional graders. Results were promising, showing the deep learning system had a 93.2% sensitivity and 88.7% specificity compared to the professional graders.14
Conclusions
The main takeaway of these studies highlights the cost-effectiveness of OCT for early detection of nAMD to reduce potential blindness or severe vision loss. Although FA remains the gold standard for identifying conversion to nAMD, OCT may be used adjunctly to reduce the need for invasive testing while increasing the amount of monitoring for unilateral nAMD. As the prevalence and costs of managing nAMD increase, artificial intelligence may support unmet needs in underserved communities by allowing for potential cost-effective ocular screening of various retinal diseases, including AMD, with relatively high sensitivity and specificity. Future studies may involve integrating such technology into real-world retina clinical practices. RP
Editor’s note: Hear discussion of this article on the Retina Podcast at www.retinapodcast.com.
References
1. Knickman JR, Snell EK. The 2030 problem: caring for aging baby boomers. Health Serv Res. 2002;37(4):849-884. doi:10.1034/j.1600-0560.2002.56.x
2. Prevent Blindness. Prevalence of age-related macular degeneration (AMD). November 3, 2022. Accessed January 26, 2024. https://preventblindness.org/amd-prevalence-vehss/#:~:text=Approximately%20one%20in%2010%20Americans
3. Medicare and macular degeneration injections: what to know. April 25, 2023. Accessed January 13, 2024. https://www.medicalnewstoday.com/articles/does-medicare-pay-for-macular-degeneration-injections#cost
4. Lövestam Adrian M, Vassilev ZP, Westborg I. Baseline visual acuity as a prognostic factor for visual outcomes in patients treated with aflibercept for wet age-related macular degeneration: data from the INSIGHT study using the Swedish Macula Register. Acta Ophthalmol. 2019;97(1):91-98. doi:10.1111/aos.13864
5. Owens DK. Interpretation of cost-effectiveness analyses. J Gen Intern Med. 1998;13(10):716-717. doi:10.1046/j.1525-1497.1998.00211.x
6. Hernandez R, Kennedy C, Banister K, et al. Early detection of neovascular age-related macular degeneration: an economic evaluation based on data from the EDNA study. Br J Ophthalmol. 2022;106(12):1754-1761. doi:10.1136/bjophthalmol-2021-319506
7. Chakravarthy U. EDNA: Early detection of neovascular age-related macular degeneration (AMD) PROTOCOL. 2018;Version 4.0. https://fundingawards.nihr.ac.uk/award/12/142/07
8. Castillo MM, Mowatt G, Elders A, et al. Optical coherence tomography for the monitoring of neovascular age-related macular degeneration: a systematic review. Ophthalmology. 2015;122(2):399-406. doi:10.1016/j.ophtha.2014.07.055
9. Schachat AP, Thompson JT. Optical coherence tomography, fluorescein angiography, and the management of neovascular age-related macular degeneration. Ophthalmology. 2015;122(2):222-223. doi:https://doi.org/10.1016/j.ophtha.2014.09.015
10. Medical Advisory Secretariat. Optical coherence tomography for age-related macular degeneration and diabetic macular edema: an evidence-based analysis. Ont Health Technol Assess Ser. 2009;9(13):1-22.
11. AREDS2-HOME Study Research Group, Chew EY, Clemons TE, et al. Randomized trial of a home monitoring system for early detection of choroidal neovascularization home monitoring of the Eye (HOME) study. Ophthalmology. 2014;121(2):535-544. doi:10.1016/j.ophtha.2013.10.027
12. Wittenborn JS, Clemons T, Regillo C, Rayess N, Liffmann Kruger D, Rein D. Economic evaluation of a home-based age-related macular degeneration monitoring system. JAMA Ophthalmol. 2017;135(5):452-459. doi:10.1001/jamaophthalmol.2017.0255
13. Vilela MAP, Arrigo A, Parodi MB, Mengue CDS. Smartphone eye examination: artificial intelligence and telemedicine. Telemed J E Health. Published online August 16, 2023. doi:10.1089/tmj.2023.0041
14. Ting DSW, Cheung CY, Lim G, et al. Development and validation of a deep learning system for diabetic retinopathy and related eye diseases using retinal images from multiethnic populations with diabetes. JAMA. 2017;318(22):2211-2223. doi:10.1001/jama.2017.18152
