In Asia-Pacific journal of ophthalmology (Philadelphia, Pa.)
PURPOSE : The health care industry is an inherently resource-intense sector. Emerging technologies such as artificial intelligence (AI) are at the forefront of advancements in health care. The health economic implications of this technology have not been clearly established and represent a substantial barrier to adoption both in Australia and globally. This review aims to determine the health economic impact of implementing AI to ophthalmology in Australia.
METHODS : A systematic search of the databases PubMed/MEDLINE, EMBASE, and CENTRAL was conducted to March 2022, before data collection and risk of bias analysis in accordance with preferred reporting items for systematic ceviews and meta-analyses 2020 guidelines (PROSPERO number CRD42022325511). Included were full-text primary research articles analyzing a population of patients who have or are being evaluated for an ophthalmological diagnosis, using a health economic assessment system to assess the cost-effectiveness of AI.
RESULTS : Seven articles were identified for inclusion. Economic viability was defined as direct cost to the patient that is equal to or less than costs incurred with human clinician assessment. Despite the lack of Australia-specific data, foreign analyses overwhelmingly showed that AI is just as economically viable, if not more so, than traditional human screening programs while maintaining comparable clinical effectiveness. This evidence was largely in the setting of diabetic retinopathy screening.
CONCLUSIONS : Primary Australian research is needed to accurately analyze the health economic implications of implementing AI on a large scale. Further research is also required to analyze the economic feasibility of adoption of AI technology in other areas of ophthalmology, such as glaucoma and cataract screening.
Pietris James, Lam Antoinette, Bacchi Stephen, Gupta Aashray K, Kovoor Joshua G, Chan WengOnn