Cost-effectiveness of AI pediatric eye screening

As artificial intelligence (AI) begins to establish a larger presence in medical care, questions surrounding cost arise. A recent study,¹ led by first author Mahoor Ahmed, MS, and colleagues found that “autonomous AI-based screening is a more effective screening strategy compared to the standard eye care provider (ECP)-performed eye examinations with greater cost-effectiveness for smaller health systems and cost-saving for larger ones.” She is from the Section on Biomedical Informatics and Data Science, Johns Hopkins University, Baltimore.

Autonomous AI already has been shown to be safe and effective for screening patients for pediatric diabetic retinal disease (DRD) and can potentially enhance health equity and clinician productivity.^2,3

However, the researchers pointed out that cost among other factors may deter patients from screening, especially in rural and low-resource settings.⁴ “With DRD screening rates as low as 20% nationwide,” they stated, “health systems and medical practices are considering alternative methods to increase screening access and adherence.⁴ Therefore, considering the financial expenditures associated with AI screening is an important step in determining if and how to implement these systems.

In this next-step study, Ahmed and colleagues examined the cost-effectiveness of an autonomous AI strategy versus a traditional ECP strategy during the initial year of implementation from a health system perspective in order to obtain some solid financial data. The incremental cost-effectiveness ratio was the main study outcome measure.

Cost-effectiveness data

The bottom line, according to Ms. Ahmed and colleagues, was that “The base-case analysis showed that the AI strategy resulted in an additional cost of $242 per patient screened to a cost saving of $140 per patient screened, depending on the health system size and patient volume, compared with the ECP strategy.

They also reported that the base-case analysis showed that the anticipated AI strategy cost was between $19,368 and $133,900, compared to that of the ECP strategy, which is between $8,927 and $357,072. “Thus, excluding insurance reimbursements, the AI strategy results in additional costs of up to $10,441 and potential cost savings of up to $240,972 depending on the size of the health system. Regarding effectiveness, the AI strategy consistently results in more patients being screened, ranging between 43 and 1,724 additional patients screened annually, depending on patient volume.”

They continued, “Notably, the AI screening strategy breaks even and demonstrates cost savings when a pediatric endocrine site screens 241 or more patients annually. Autonomous AI-based screening consistently results in more patients screened with greater cost savings in most health system scenarios.”

Their hope is that this analysis can assist providers in weighing the value proposition of implementing AI screening and support informed adoption decisions.

References:

1. Ahmed M, Dai T, Channa R, et al. Cost-effectiveness of AI for pediatric diabetic eye exams from a health system perspective. npj Digit Med. 2025;8:3. https://doi.org/10.1038/s41746-024-01382-4

2. Flaxel CJ, Adelman RA, Bailey ST, et al. Diabetic retinopathy preferred practice pattern®. Ophthalmology. 2020;127:66-145.

3. Draznin B, Aroda VR, Bakris G, et al. 14. Children and adolescents: standards of medical care in diabetes—2022. Diabetes Care. 2022;45.https://doi.org/10.2337/dc22-S014

4. Benoit SR, Swenor B, Geiss LS, Gregg EW, Saaddine JB. Eye care utilization among insured people with diabetes in the U.S., 2010–2014. Diabetes Care. 2019;42:427–433.

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