Journal article
Cost-effectiveness of AI for pediatric diabetic eye exams from a health system perspective
NPJ digital medicine, Vol.8(1), 3
01/02/2025
DOI: 10.1038/s41746-024-01382-4
PMCID: PMC11697205
PMID: 39747639
Abstract
Autonomous artificial intelligence (AI) for pediatric diabetic retinal disease (DRD) screening has demonstrated safety, effectiveness, and the potential to enhance health equity and clinician productivity. We examined the cost-effectiveness of an autonomous AI strategy versus a traditional eye care provider (ECP) strategy during the initial year of implementation from a health system perspective. The incremental cost-effectiveness ratio (ICER) was the main outcome measure. Compared to the ECP strategy, the base-case analysis shows that the AI strategy results in an additional cost of $242 per patient screened to a cost saving of $140 per patient screened, depending on health system size and patient volume. 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.
Details
- Title: Subtitle
- Cost-effectiveness of AI for pediatric diabetic eye exams from a health system perspective
- Creators
- Mahnoor Ahmed - Johns Hopkins UniversityTinglong Dai - Johns Hopkins UniversityRoomasa Channa - University of Wisconsin–MadisonMichael D Abramoff - Iowa City VA Medical CenterHarold P Lehmann - Johns Hopkins UniversityRisa M Wolf - Johns Hopkins University School of Medicine
- Resource Type
- Journal article
- Publication Details
- NPJ digital medicine, Vol.8(1), 3
- DOI
- 10.1038/s41746-024-01382-4
- PMID
- 39747639
- PMCID
- PMC11697205
- NLM abbreviation
- NPJ Digit Med
- ISSN
- 2398-6352
- eISSN
- 2398-6352
- Publisher
- NATURE PORTFOLIO
- Grant note
- 5K23EY030911-03 / U.S. Department of Health & Human Services | NIH | National Eye Institute (NEI) R01EY033233 / U.S. Department of Health & Human Services | NIH | National Eye Institute (NEI)
- Language
- English
- Date published
- 01/02/2025
- Academic Unit
- Electrical and Computer Engineering; Fraternal Order of Eagles Diabetes Research Center; Ophthalmology and Visual Sciences
- Record Identifier
- 9984770891902771
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