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Russell MK, Hsing YI. Evaluation of the Efficiency of a Digital Workflow for Cataract Planning in Patients with Astigmatism. Clin Ophthalmol 2024; 18:1441-1446. [PMID: 38813538 PMCID: PMC11135556 DOI: 10.2147/opth.s454549] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2023] [Accepted: 05/01/2024] [Indexed: 05/31/2024] Open
Abstract
Purpose To evaluate the efficiency and associated costs of a digital cataract workflow system and manual cataract workflow system for patients, with astigmatism presenting for cataract surgery in Brisbane, Australia. Patients and Methods Sixty patients with bilateral cataract requiring toric intraocular lenses (IOL) were sequentially assigned to a manual cataract workflow (n = 30) or digital workflow (n = 30) using EQ Workplace (SW v1.7.0) running on FORUM (SW v.4.2.1.66) (Carl Zeiss Meditec, Jena, Germany). Each step of preoperative data acquisition and analysis was timed. Steps in each workflow were divided into presurgical planning time and total workflow time, the latter including the time required to input toric data into CALLISTO eye (Carl Zeiss Meditec). Secondary outcomes included staff costs within each workflow. Results Median presurgical planning time using a digital workflow process was 6.51 ± 0.65 minutes, and using a manual workflow process, 12.32 ± 0.56 minutes (p < 0.001). Similarly, median total workflow time using a digital workflow process was 6.93 ± 0.57 minutes and using a manual workflow process, 13.49 ± 0.47 minutes (p < 0.001). Evaluating the staff remuneration during presurgical planning and the operating costs associated with running EQ Workplace, there was a cost-reduction of 35% per patient when using the digital cataract workflow process. Conclusion Using a digital cataract workflow process is more efficient and provides staff cost-savings compared to a manual workflow process when planning for toric IOL implantation.
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Elsawy A, Keenan TDL, Chen Q, Thavikulwat AT, Bhandari S, Quek TC, Goh JHL, Tham YC, Cheng CY, Chew EY, Lu Z. A deep network DeepOpacityNet for detection of cataracts from color fundus photographs. COMMUNICATIONS MEDICINE 2023; 3:184. [PMID: 38104223 PMCID: PMC10725427 DOI: 10.1038/s43856-023-00410-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Accepted: 11/21/2023] [Indexed: 12/19/2023] Open
Abstract
BACKGROUND Cataract diagnosis typically requires in-person evaluation by an ophthalmologist. However, color fundus photography (CFP) is widely performed outside ophthalmology clinics, which could be exploited to increase the accessibility of cataract screening by automated detection. METHODS DeepOpacityNet was developed to detect cataracts from CFP and highlight the most relevant CFP features associated with cataracts. We used 17,514 CFPs from 2573 AREDS2 participants curated from the Age-Related Eye Diseases Study 2 (AREDS2) dataset, of which 8681 CFPs were labeled with cataracts. The ground truth labels were transferred from slit-lamp examination of nuclear cataracts and reading center grading of anterior segment photographs for cortical and posterior subcapsular cataracts. DeepOpacityNet was internally validated on an independent test set (20%), compared to three ophthalmologists on a subset of the test set (100 CFPs), externally validated on three datasets obtained from the Singapore Epidemiology of Eye Diseases study (SEED), and visualized to highlight important features. RESULTS Internally, DeepOpacityNet achieved a superior accuracy of 0.66 (95% confidence interval (CI): 0.64-0.68) and an area under the curve (AUC) of 0.72 (95% CI: 0.70-0.74), compared to that of other state-of-the-art methods. DeepOpacityNet achieved an accuracy of 0.75, compared to an accuracy of 0.67 for the ophthalmologist with the highest performance. Externally, DeepOpacityNet achieved AUC scores of 0.86, 0.88, and 0.89 on SEED datasets, demonstrating the generalizability of our proposed method. Visualizations show that the visibility of blood vessels could be characteristic of cataract absence while blurred regions could be characteristic of cataract presence. CONCLUSIONS DeepOpacityNet could detect cataracts from CFPs in AREDS2 with performance superior to that of ophthalmologists and generate interpretable results. The code and models are available at https://github.com/ncbi/DeepOpacityNet ( https://doi.org/10.5281/zenodo.10127002 ).
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Affiliation(s)
- Amr Elsawy
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, 20894, USA
| | - Tiarnan D L Keenan
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, 20894, USA
| | - Qingyu Chen
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, 20894, USA
| | - Alisa T Thavikulwat
- Division of Epidemiology and Clinical Applications, National Eye Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Sanjeeb Bhandari
- Division of Epidemiology and Clinical Applications, National Eye Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Ten Cheer Quek
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
| | - Jocelyn Hui Lin Goh
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
| | - Yih-Chung Tham
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Ophthalmology & Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore
- Centre for Innovation and Precision Eye Health & Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Ching-Yu Cheng
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Ophthalmology & Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore
- Centre for Innovation and Precision Eye Health & Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Emily Y Chew
- Division of Epidemiology and Clinical Applications, National Eye Institute, National Institutes of Health, Bethesda, MD, 20892, USA.
| | - Zhiyong Lu
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, 20894, USA.
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Keay L, Ho KC, Rogers K, McCluskey P, White AJR, Morlet N, Ng JQ, Lamoureux E, Pesudovs K, Stapleton FJ, Boufous S, Huang‐Lung J, Palagyi A. The incidence of falls after first and second eye cataract surgery: a longitudinal cohort study. Med J Aust 2022; 217:94-99. [PMID: 35702892 PMCID: PMC9546129 DOI: 10.5694/mja2.51611] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2021] [Revised: 03/28/2022] [Accepted: 03/31/2022] [Indexed: 11/17/2022]
Abstract
OBJECTIVE To compare fall incidence, and visual acuity and refractive status, before surgery and after first and second eye cataract surgery. DESIGN, SETTING Prospective observational study in eight tertiary referral ophthalmology clinics in public hospitals in Sydney, Melbourne, and Perth. PARTICIPANTS People aged 65 years or more referred for bilateral age-related cataract surgery during 2013-16, followed for maximum of 24 months after study entry or until six months after second eye surgery, whichever was shorter. MAIN OUTCOME MEASURES Primary outcome: age- and sex-adjusted incidence of falls. SECONDARY OUTCOMES visual acuity and refractive error. RESULTS The mean age of the 409 included participants was 75.4 years (SD, 5.4 years); 220 were women (54%). Age- and sex-adjusted fall incidence prior to surgery was 1.17 (95% CI, 0.95-1.43) per year, 0.81 (95% CI, 0.63-1.04) per year after first eye surgery, and 0.41 (95% CI, 0.29-0.57) per year after second eye surgery. For the 118 participants who underwent second eye surgery and participated in all follow-up visits, age- and sex-adjusted incidence before (0.80 [95% CI, 0.55-1.15] falls per year) and after first eye surgery (0.81 [95% CI, 0.57-1.15] falls per year) was similar, but was lower after second eye surgery (0.32 [95% CI 0.21-0.50] falls per year). Mean habitual binocular visual acuity (logMAR) was 0.32 (SD, 0.21) before surgery, 0.15 (SD, 0.17) after first eye surgery, and 0.07 (SD, 0.15) after second eye surgery. CONCLUSIONS First eye surgery substantially improves vision in older people with cataract, but second eye surgery is required to minimise fall incidence. Timely cataract surgery for both eyes not only optimises vision in older people with cataract, but also reduces their risk of injury from falls.
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Affiliation(s)
- Lisa Keay
- The University of New South WalesSydneyNSW
- The George Institute for Global HealthSydneyNSW
| | - Kam Chun Ho
- The University of New South WalesSydneyNSW
- The University of CanberraCanberraACT
| | - Kris Rogers
- The George Institute for Global HealthSydneyNSW
| | | | - Andrew JR White
- Save Sight InstituteThe University of SydneySydneyNSW
- Westmead Institute for Medical ResearchSydneyNSW
| | | | | | | | | | | | - Soufiane Boufous
- Transport and Road Safety (TARS) Research CentreUniversity of New South WalesSydneyNSW
| | - Jessie Huang‐Lung
- The University of New South WalesSydneyNSW
- The George Institute for Global HealthSydneyNSW
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Considerations for Training and Workforce Development to Enhance Rural and Remote Ophthalmology Practise in Australia: A Scoping Review. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19148593. [PMID: 35886446 PMCID: PMC9315488 DOI: 10.3390/ijerph19148593] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Revised: 07/05/2022] [Accepted: 07/07/2022] [Indexed: 11/11/2022]
Abstract
Australia has one of the lowest per capita numbers of ophthalmologists among OECD countries, and they predominantly practise in metropolitan centres of the country. Increasing the size and distribution of the ophthalmology workforce is of critical importance. The objective of this review was to investigate the context of rural ophthalmology training and practise in Australia and how they relate to future ophthalmology workforce development. This scoping review was informed by Arksey and O’Malley’s framework and the methodology described by Coloqhuon et al. The search yielded 428 articles, of which 261 were screened for eligibility. Following the screening, a total of 75 articles were included in the study. Themes identified relating to rural ophthalmology training and practise included: Indigenous eye health; access and utilisation of ophthalmology-related services; service delivery models for ophthalmic care; ophthalmology workforce demographics; and ophthalmology workforce education and training for rural and remote practise. With an anticipated undersupply and maldistribution of ophthalmologists in the coming decade, efforts to improve training must focus on how to build a sizeable, fit-for-purpose workforce to address eye health needs across Australia. More research focusing on ophthalmology workforce distribution is needed to help identify evidence-based solutions for workforce maldistribution. Several strategies to better prepare the future ophthalmology workforce for rural practise were identified, including incorporating telehealth into ophthalmology training settings; collaborating with other health workers, especially optometrists and specialist nurses in eyecare delivery; and exposing trainees to more patients of Indigenous background.
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Tegegn MT, Assaye AK, Belete GT, Munaw MB. Visually significant cataract and associated factors among older people attending a community ophthalmic service in central Gondar Zone, Northwest Ethiopia: a cross-sectional study. J Int Med Res 2022; 50:3000605221104761. [PMID: 35698450 PMCID: PMC9201317 DOI: 10.1177/03000605221104761] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/03/2022] Open
Abstract
Objective In this study, we aimed to determine the prevalence of visually significant
cataract and associated factors among older people attending community
ophthalmic services in the central Gondar Zone, Northwest Ethiopia. Methods We conducted a community outreach-based cross-sectional study among adults
aged ≥40 years in the central Gondar Zone from 30 May to 15 June 2021. We
used systematic random sampling to select study participants.
Interviewer-administered questionnaires and ocular examinations were
performed and the data recorded. We applied binary logistic regression to
identify factors associated with visually significant cataract. Results A total of 821 participants were included, with median age 57 years. The
prevalence of visually significant cataract was 29.1% (95% CI: 26.1–32.0).
Age ≥80 years (adjusted odds ratio [AOR] = 16.9; 95% CI: 7.5–38.4), rural
residence (AOR = 1.7; 95% CI: 1.02–2.7), unmarried status (AOR = 1.9; 95%
CI: 1.2–3.2), illiteracy (AOR = 2.9; 95% CI: 1.4–6.1), unemployed status
(AOR = 1.7; 95% CI: 1.1–2.7), and sunlight exposure ≥5 hours per day
(AOR = 1.6; 95% CI: 1.04–2.4) were significantly associated with visually
significant cataract. Conclusion In this study, visually significant cataract was found to be high, which
requires immediate public health intervention.
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Affiliation(s)
- Melkamu Temeselew Tegegn
- Department of Optometry, School of Medicine, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia
| | - Aragaw Kegne Assaye
- Department of Optometry, School of Medicine, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia
| | - Gizachew Tilahun Belete
- Department of Optometry, School of Medicine, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia
| | - Minychil Bantihun Munaw
- Department of Optometry, School of Medicine, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia
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Tham YC, Goh JHL, Anees A, Lei X, Rim TH, Chee ML, Wang YX, Jonas JB, Thakur S, Teo ZL, Cheung N, Hamzah H, Tan GSW, Husain R, Sabanayagam C, Wang JJ, Chen Q, Lu Z, Keenan TD, Chew EY, Tan AG, Mitchell P, Goh RSM, Xu X, Liu Y, Wong TY, Cheng CY. Detecting visually significant cataract using retinal photograph-based deep learning. NATURE AGING 2022; 2:264-271. [PMID: 37118370 PMCID: PMC10154193 DOI: 10.1038/s43587-022-00171-6] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/12/2021] [Accepted: 01/10/2022] [Indexed: 02/06/2023]
Abstract
Age-related cataracts are the leading cause of visual impairment among older adults. Many significant cases remain undiagnosed or neglected in communities, due to limited availability or accessibility to cataract screening. In the present study, we report the development and validation of a retinal photograph-based, deep-learning algorithm for automated detection of visually significant cataracts, using more than 25,000 images from population-based studies. In the internal test set, the area under the receiver operating characteristic curve (AUROC) was 96.6%. External testing performed across three studies showed AUROCs of 91.6-96.5%. In a separate test set of 186 eyes, we further compared the algorithm's performance with 4 ophthalmologists' evaluations. The algorithm performed comparably, if not being slightly more superior (sensitivity of 93.3% versus 51.7-96.6% by ophthalmologists and specificity of 99.0% versus 90.7-97.9% by ophthalmologists). Our findings show the potential of a retinal photograph-based screening tool for visually significant cataracts among older adults, providing more appropriate referrals to tertiary eye centers.
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Affiliation(s)
- Yih-Chung Tham
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Jocelyn Hui Lin Goh
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
| | - Ayesha Anees
- Institute of High Performance Computing, A*STAR, Singapore, Singapore
| | - Xiaofeng Lei
- Institute of High Performance Computing, A*STAR, Singapore, Singapore
| | - Tyler Hyungtaek Rim
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
| | - Miao-Li Chee
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
| | - Ya Xing Wang
- Beijing Institute of Ophthalmology, Beijing Ophthalmology and Visual Science Key Lab, Beijing, China
| | - Jost B Jonas
- Department of Ophthalmology, Medical Faculty Mannheim of the Ruprecht-Karis-University Heidelberg, Mannheim, Germany
| | - Sahil Thakur
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
| | - Zhen Ling Teo
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
| | - Ning Cheung
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
| | - Haslina Hamzah
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
| | - Gavin S W Tan
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
| | - Rahat Husain
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
| | - Charumathi Sabanayagam
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
| | | | - Qingyu Chen
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA
| | - Zhiyong Lu
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA
| | - Tiarnan D Keenan
- National Eye Institute, National Institutes of Health, Bethesda, MD, USA
| | - Emily Y Chew
- National Eye Institute, National Institutes of Health, Bethesda, MD, USA
| | - Ava Grace Tan
- Centre for Vision Research, Department of Ophthalmology, The Westmead Institute for Medical Research, University of Sydney, Westmead Hospital, Westmead, New South Wales, Australia
- National Health Medical Research Council Clinical Trials Centre, University of Sydney, Sydney, New South Wales, Australia
| | - Paul Mitchell
- Centre for Vision Research, Department of Ophthalmology, The Westmead Institute for Medical Research, University of Sydney, Westmead Hospital, Westmead, New South Wales, Australia
| | - Rick S M Goh
- Institute of High Performance Computing, A*STAR, Singapore, Singapore
| | - Xinxing Xu
- Institute of High Performance Computing, A*STAR, Singapore, Singapore
| | - Yong Liu
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
- Institute of High Performance Computing, A*STAR, Singapore, Singapore
| | - Tien Yin Wong
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Ching-Yu Cheng
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore.
- Duke-NUS Medical School, Singapore, Singapore.
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
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Zhang S, Chen J, Yang F, Xu B, Tang Y, Lu Y. Prevalence rates of cataract and cataract surgery in elderly Chinese people living in suburban Shanghai: the Pujiang Cataract Cohort Study. Br J Ophthalmol 2022; 107:683-689. [PMID: 35086805 DOI: 10.1136/bjophthalmol-2021-319991] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Accepted: 12/02/2021] [Indexed: 11/04/2022]
Abstract
PURPOSE To estimate the prevalence rates of cataract and cataract surgery in suburban Shanghai, China. METHODS This population-based, cross-sectional study was carried out in Pujiang Town, Shanghai, China, using a random cluster sampling strategy. A total of 5846 participants (11,657 eyes) aged ≥65 years were enrolled. Detailed eye examinations included presenting visual acuity (VA), best-corrected VA, non-contact tonometry, measurement of ocular parameters using IOLMaster 700, slit-lamp assessment of lens opacities using the Lens Opacities Classification System III and dilated fundus evaluation. RESULTS Cataract was present in 57.0% of participants (53.8% of eyes). Cortical, nuclear and posterior subcapsular cataract (PSC) were found in 41.3%, 41.0% and 12.6% of participants. Among participants with any cataract, VA was <20/40 in 32.5%. According to Global Burden of Disease Study visual impairment (VI) criteria, 52.5% of participants with PSC had VI, 4.9% were considered blind (VA <20/400) and 31.9% had moderate VI (VA ≥20/400 to <20/63). This rate was significantly greater than that in participants with cortical (32.0%) or nuclear (38.0%) cataract (P<0.05). Cataract surgery was performed in 8.1% of eyes (men, 3.1%; women, 5.0%) or 10.9% of participants (men, 4.2%; women, 6.7%). CONCLUSIONS The Pujiang Cataract Cohort Study has revealed the prevalence rates of cataract and cataract surgery among elderly individuals in suburban Shanghai, China. Although the frequency of cataract surgery has increased in China in recent decades, the high prevalence of cataract-related VI among older people suggests further attention to primary eyecare and medical awareness is necessary.
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Affiliation(s)
- Shaohua Zhang
- Eye Institute and Department of Ophthalmology, Eye & ENT Hospital, Fudan University, Shanghai, 200031, China.,NHC Key Laboratory of Myopia (Fudan University); Key Laboratory of Myopia, Chinese Academy of Medical Sciences, Shanghai, 200031, China.,Shanghai Key Laboratory of Visual Impairment and Restoration, Shanghai, 200031, China
| | - Jiahui Chen
- Eye Institute and Department of Ophthalmology, Eye & ENT Hospital, Fudan University, Shanghai, 200031, China.,NHC Key Laboratory of Myopia (Fudan University); Key Laboratory of Myopia, Chinese Academy of Medical Sciences, Shanghai, 200031, China.,Shanghai Key Laboratory of Visual Impairment and Restoration, Shanghai, 200031, China
| | - Fan Yang
- Eye Institute and Department of Ophthalmology, Eye & ENT Hospital, Fudan University, Shanghai, 200031, China.,NHC Key Laboratory of Myopia (Fudan University); Key Laboratory of Myopia, Chinese Academy of Medical Sciences, Shanghai, 200031, China.,Shanghai Key Laboratory of Visual Impairment and Restoration, Shanghai, 200031, China
| | - Binxin Xu
- Human Phenome Institute, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Institute of Brain Science, School of Life Sciences, Fudan University, Shanghai, 200438, China
| | - Yating Tang
- Eye Institute and Department of Ophthalmology, Eye & ENT Hospital, Fudan University, Shanghai, 200031, China .,NHC Key Laboratory of Myopia (Fudan University); Key Laboratory of Myopia, Chinese Academy of Medical Sciences, Shanghai, 200031, China.,Shanghai Key Laboratory of Visual Impairment and Restoration, Shanghai, 200031, China
| | - Yi Lu
- Eye Institute and Department of Ophthalmology, Eye & ENT Hospital, Fudan University, Shanghai, 200031, China .,NHC Key Laboratory of Myopia (Fudan University); Key Laboratory of Myopia, Chinese Academy of Medical Sciences, Shanghai, 200031, China.,Shanghai Key Laboratory of Visual Impairment and Restoration, Shanghai, 200031, China
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8
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Allen P, Jessup B, Khanal S, Baker-Smith V, Obamiro K, Barnett T. Distribution and Location Stability of the Australian Ophthalmology Workforce: 2014-2019. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:ijerph182312574. [PMID: 34886297 PMCID: PMC8656490 DOI: 10.3390/ijerph182312574] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/29/2021] [Revised: 11/23/2021] [Accepted: 11/25/2021] [Indexed: 11/16/2022]
Abstract
OBJECTIVE To investigate the ophthalmology workforce distribution and location stability using Modified Monash Model category of remoteness. METHODS Whole of ophthalmologist workforce analysis using Australian Health Practitioner Registration Agency (AHPRA) data. Modified Monash Model (MMM) category was mapped to postcode of primary work location over a six-year period (2014 to 2019). MMM stability was investigated using survival analysis and competing risks regression. DESIGN Retrospective cohort study. SETTING Australia. PARTICIPANTS Ophthalmologists registered with AHPRA. MAIN OUTCOME MEASURES Retention within MMM category of primary work location. RESULTS A total of 948 ophthalmologists were identified (767 males, 181 females). Survival estimates indicate 84% of ophthalmologists remained working in MMM1, while 79% of ophthalmologists working in MMM2-MMM7remained in these regions during the six-year period. CONCLUSION The Australian ophthalmology workforce shows a high level of location stability and is concentrated in metropolitan areas of Australia. Investment in policy initiatives designed to train, recruit and retain ophthalmologists in regional, rural and remote areas is needed to improve workforce distribution outside of metropolitan areas.
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Affiliation(s)
- Penny Allen
- Rural Clinical School, Hospitals’ Campus, University of Tasmania, Brickport Road, Burnie, TAS 7320, Australia
- Correspondence:
| | - Belinda Jessup
- Centre for Rural Health, Newnham Campus, University of Tasmania, Launceston, TAS 7250, Australia; (B.J.); (K.O.); (T.B.)
| | - Santosh Khanal
- The Royal Australian and New Zealand College of Ophthalmology, 94-98 Chalmers Street, Surry Hills, NSW 2010, Australia; (S.K.); (V.B.-S.)
| | - Victoria Baker-Smith
- The Royal Australian and New Zealand College of Ophthalmology, 94-98 Chalmers Street, Surry Hills, NSW 2010, Australia; (S.K.); (V.B.-S.)
| | - Kehinde Obamiro
- Centre for Rural Health, Newnham Campus, University of Tasmania, Launceston, TAS 7250, Australia; (B.J.); (K.O.); (T.B.)
| | - Tony Barnett
- Centre for Rural Health, Newnham Campus, University of Tasmania, Launceston, TAS 7250, Australia; (B.J.); (K.O.); (T.B.)
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Goh JHL, Lim ZW, Fang X, Anees A, Nusinovici S, Rim TH, Cheng CY, Tham YC. Artificial Intelligence for Cataract Detection and Management. Asia Pac J Ophthalmol (Phila) 2020; 9:88-95. [PMID: 32349116 DOI: 10.1097/01.apo.0000656988.16221.04] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
The rising popularity of artificial intelligence (AI) in ophthalmology is fuelled by the ever-increasing clinical "big data" that can be used for algorithm development. Cataract is one of the leading causes of visual impairment worldwide. However, compared with other major age-related eye diseases, such as diabetic retinopathy, age-related macular degeneration, and glaucoma, AI development in the domain of cataract is still relatively underexplored. In this regard, several previous studies explored algorithms for automated cataract assessment using either slit lamp of color fundus photographs. However, several other study groups proposed or derived new AI-based calculation for pre-cataract surgery intraocular lens power. Along with advancements in digitization of clinical data, data curation for future cataract-related AI developmental work is bound to undergo significant improvements in the foreseeable future. Even though most of these previous studies reported early promising performances, limitations such as lack of robust, high-quality training data, and lack of external validations remain. In the next phase of work, apart from algorithm's performance, it will also be pertinent to evaluate deployment angles, feasibility, efficiency, and cost-effectiveness of these new cataract-related AI systems.
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Affiliation(s)
- Jocelyn Hui Lin Goh
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore
- School of Chemical and Biomedical Engineering, Division of Bioengineering, Nanyang Technological University, Singapore
| | - Zhi Wei Lim
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore
- Faculty of Medicine, University of New South Wales, Sydney, Australia
| | - Xiaoling Fang
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore
- Department of Ophthalmology, Shanghai Eye Disease Prevention & Treatment Center, Shanghai Eye Hospital, Shanghai, China
| | - Ayesha Anees
- Institute of High Performance Computing, A∗STAR, Singapore
| | - Simon Nusinovici
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore
| | - Tyler Hyungtaek Rim
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore
- Duke-NUS Medical School, Singapore
| | - Ching-Yu Cheng
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore
- Duke-NUS Medical School, Singapore
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore
| | - Yih-Chung Tham
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore
- Duke-NUS Medical School, Singapore
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