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Nagino K, Sung J, Midorikawa-Inomata A, Eguchi A, Fujimoto K, Okumura Y, Miura M, Yee A, Hurramhon S, Fujio K, Akasaki Y, Hirosawa K, Huang T, Ohno M, Morooka Y, Zou X, Kobayashi H, Inomata T. Clinical Utility of Smartphone Applications in Ophthalmology: A Systematic Review. OPHTHALMOLOGY SCIENCE 2024; 4:100342. [PMID: 37869018 PMCID: PMC10587618 DOI: 10.1016/j.xops.2023.100342] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Revised: 05/17/2023] [Accepted: 05/23/2023] [Indexed: 10/24/2023]
Abstract
Topic Numerous smartphone applications have been devised for diagnosis, treatment, and symptom management in ophthalmology. Despite the importance of systematic evaluation of the purpose, target disease, effectiveness, and utility of smartphone applications to their effective utilization, few studies have formally evaluated their validity, reliability, and clinical utility. Clinical Relevance This report identifies smartphone applications with potential for clinical implementation in ophthalmology and summarizes the evidence on their practical utility. Methods We searched PubMed and EMBASE on July 28, 2022, for articles reporting original data on the effectiveness of treatment, disease detection, diagnostic accuracy, disease monitoring, and usability of smartphone applications in ophthalmology published between January 1, 1987, and July 25, 2022. Their quality was assessed using the Joanna Briggs Institute Critical Appraisal Checklist. Results The initial search yielded 510 articles. After removing 115 duplicates and 285 articles based on inclusion and exclusion criteria, the full texts of the remaining 110 articles were reviewed. Furthermore, 71 articles were included in the final qualitative synthesis. All studies were determined to be of high (87.3%) or moderate (12.7%) quality. In terms of respective application of interest, 24 (33.8%) studies assessed diagnostic accuracy, 17 (23.9%) assessed disease detection, and 3 (4.2%) assessed intervention efficacy. A total of 48 smartphone applications were identified, of which 27 (56.3%) were publicly available. Seventeen (35.4%) applications included functions for ophthalmic examinations, 13 (27.1%) included functions aimed at disease detection, 10 (20.8%) included functions to support medical personnel, five (10.4%) included functions related to disease education, and three (6.3%) included functions to promote treatment adherence for patients. The largest number of applications targeted amblyopia (18.8%), followed by retinal disease (10.4%). Two (4.2%) smartphone applications reported significant efficacy in treating diseases. Conclusion In this systematic review, a comprehensive appraisal is presented on studies related to diagnostic accuracy, disease detectability, and efficacy of smartphone applications in ophthalmology. Forty-eight applications with potential clinical utility are identified. Appropriate smartphone applications are expected to enable early detection of undiagnosed diseases via telemedicine and prevent visual dysfunction via remote monitoring of chronic diseases. Financial Disclosures Proprietary or commercial disclosure may be found after the references.
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Affiliation(s)
- Ken Nagino
- Department of Hospital Administration, Juntendo University Graduate School of Medicine, Tokyo, Japan
- Department of Ophthalmology, Juntendo University Graduate School of Medicine, Tokyo, Japan
- Department of Digital Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Jaemyoung Sung
- Department of Ophthalmology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Akie Midorikawa-Inomata
- Department of Hospital Administration, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Atsuko Eguchi
- Department of Hospital Administration, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Keiichi Fujimoto
- Department of Ophthalmology, Juntendo University Graduate School of Medicine, Tokyo, Japan
- Department of Digital Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Yuichi Okumura
- Department of Ophthalmology, Juntendo University Graduate School of Medicine, Tokyo, Japan
- Department of Digital Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Maria Miura
- Department of Ophthalmology, Juntendo University Graduate School of Medicine, Tokyo, Japan
- Department of Digital Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Alan Yee
- Department of Ophthalmology, Juntendo University Graduate School of Medicine, Tokyo, Japan
- Department of Digital Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Shokirova Hurramhon
- Department of Ophthalmology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Kenta Fujio
- Department of Ophthalmology, Juntendo University Graduate School of Medicine, Tokyo, Japan
- Department of Digital Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Yasutsugu Akasaki
- Department of Ophthalmology, Juntendo University Graduate School of Medicine, Tokyo, Japan
- Department of Digital Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Kunihiko Hirosawa
- Department of Ophthalmology, Juntendo University Graduate School of Medicine, Tokyo, Japan
- Department of Digital Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Tianxiang Huang
- Department of Ophthalmology, Juntendo University Graduate School of Medicine, Tokyo, Japan
- Department of Digital Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Mizu Ohno
- Department of Ophthalmology, Juntendo University Graduate School of Medicine, Tokyo, Japan
- Department of Digital Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Yuki Morooka
- Department of Ophthalmology, Juntendo University Graduate School of Medicine, Tokyo, Japan
- Department of Digital Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Xinrong Zou
- Department of Ophthalmology, Juntendo University Graduate School of Medicine, Tokyo, Japan
- Department of Ophthalmology, Fengcheng Hospital, Shanghai, China
| | - Hiroyuki Kobayashi
- Department of Hospital Administration, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Takenori Inomata
- Department of Hospital Administration, Juntendo University Graduate School of Medicine, Tokyo, Japan
- Department of Ophthalmology, Juntendo University Graduate School of Medicine, Tokyo, Japan
- Department of Digital Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan
- AI Incubation Farm, Juntendo University Graduate School of Medicine, Tokyo, Japan
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Claessens D, Krüger RV, Grötzinger L. Change in Sub-aspects of Vision-Related Quality of Life after Three Months of Using an App to Categorize Metamorphopsia. Klin Monbl Augenheilkd 2023; 240:1091-1097. [PMID: 35426105 DOI: 10.1055/a-1809-5125] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
AIM Distorted vision (metamorphopsia) is a leading symptom in retinal disease and can be categorized with the app MacuFix. This prospective controlled pilot study examined the influence of the app MacuFix as a method to assess metamorphopsia on vision-related quality of life. METHODS Forty-five patients suffering from metamorphopsia in at least one eye were recruited for the study. Vision-related quality of life before and after 3 months of optional home monitoring using the app MacuFix were compared with the questionnaire National Eye Institute Visual Function Questionnaire-25. RESULTS The 45 participants (18 women, 27 men) were, on average, 68 years old (SD ± 9.7) and had a mean best-corrected visual acuity of 0.6 (SD ± 0.25). Of 90 eyes, 18 revealed no maculopathy. Age-related macular degeneration existed in 52 eyes, epiretinal gliosis in 6, and macular hole in 1 eye. Macular edema was present in two eyes due to diabetes, four eyes due to uveitis, one eye after retinal venous thrombosis, four eyes because of an Irvine Gass syndrome, and two eyes caused by central serous thrombosis. After 3 months, 35 persons used the app for home monitoring, 8 persons applied the Amsler Grid, and 2 did not use any test. App users showed a highly significant improvement in vision-related quality of life in questions on mental health and concern about vision, and a significant improvement in performance, dejection, control, and embarrassing situations. CONCLUSION The results suggest that MacuFix can possibly ameliorate partial aspects of vision-related quality of life.
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Affiliation(s)
- Daniela Claessens
- Augenheilkunde, Gemeinschaftspraxis Augenheilkunde Lindenthal, Köln, Deutschland
| | | | - Lilly Grötzinger
- Gesundheitsökonomie, Hochschule Ravensburg-Weingarten, Deutschland
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