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. 2021 Dec;10(4):703-713.
doi: 10.1007/s40123-021-00405-7. Epub 2021 Oct 12.

A Proposed Framework for Machine Learning-Aided Triage in Public Specialty Ophthalmology Clinics in Hong Kong

Yalsin Yik Sum Li  1 , Varut Vardhanabhuti  2 , Efstratios Tsougenis  3 , Wai Ching Lam  1 , Kendrick Co Shih  4
Affiliations

A Proposed Framework for Machine Learning-Aided Triage in Public Specialty Ophthalmology Clinics in Hong Kong

Yalsin Yik Sum Li et al. Ophthalmol Ther. 2021 Dec.

Abstract

The public specialty ophthalmic clinics in Hong Kong, under the Hospital Authority, receive tens of thousands of referrals each year. Triaging these referrals incurs a significant workload for practitioners and the other clinical duties. It is well-established that Hong Kong is currently facing a shortage of healthcare workers. Thus a more efficient system in triaging will not only free up resources for better use but also improve the satisfaction of both practitioners and patients. Machine learning (ML) has been shown to improve the efficiency of various medical workflows, including triaging, by both reducing the workload and increasing accuracy in some cases. Despite a myriad of studies on medical artificial intelligence, there is no specific framework for a triaging algorithm in ophthalmology clinics. This study proposes a general framework for developing, deploying and evaluating an ML-based triaging algorithm in a clinical setting. Through literature review, this study identifies good practices in various facets of developing such a network and protocols for maintenance and evaluation of the impact concerning clinical utility and external validity out of the laboratory. We hope this framework, albeit not exhaustive, can act as a foundation to accelerate future pilot studies and deployments.

Keywords: Machine learning; Ophthalmic specialty clinics; Public health care system; Triage.

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Figures

Fig. 1
Fig. 1
Overview of the proposed framework
Fig. 2
Fig. 2
Development flow chart
Fig. 3
Fig. 3
Proposed network architecture
See this image and copyright information in PMC

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