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The diagnostic and triage accuracy of digital and online symptom checker tools: a systematic review

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Title: The diagnostic and triage accuracy of digital and online symptom checker tools: a systematic review
Authors: Wallace, W
Chan, C
Chidambaram, S
Hanna, L
Iqbal, FM
Acharya, A
Normahani, P
Ashrafian, H
Markar, SR
Sounderajah, V
Darzi, A
Item Type: Journal Article
Abstract: Digital and online symptom checkers are an increasingly adopted class of health technologies that enable patients to input their symptoms and biodata to produce a set of likely diagnoses and associated triage advice. However, concerns regarding the accuracy and safety of these symptom checkers have been raised. This systematic review evaluates the accuracy of symptom checkers in providing diagnoses and appropriate triage advice. MEDLINE and Web of Science were searched for studies that used either real or simulated patients to evaluate online or digital symptom checkers. The primary outcomes were the diagnostic and triage accuracy of the symptom checkers. The QUADAS-2 tool was used to assess study quality. Of the 177 studies retrieved, 10 studies met the inclusion criteria. Researchers evaluated the accuracy of symptom checkers using a variety of medical conditions, including ophthalmological conditions, inflammatory arthritides and HIV. 50% of the studies recruited real patients, while the remainder used simulated cases. The diagnostic accuracy of the primary diagnosis was low across included studies (range: 19% to 37.9%) and varied between individual symptom checkers, despite consistent symptom data input. Triage accuracy (range: 48.8% to 90.1%) was typically higher than diagnostic accuracy. Overall, the diagnostic and triage accuracy of symptom checkers are variable and of low accuracy. Given the increasing push towards adopting this class of technologies across numerous health systems, this study demonstrates that reliance upon symptom checkers could pose significant patient safety hazards. Large scale primary studies, based upon real world data, are warranted to demonstrate adequate performance of these technologies in a manner that is and non-inferior to current best practice. Moreover, an urgent assessment of how these systems are regulated and implemented is required.
Issue Date: 17-Aug-2022
Date of Acceptance: 25-Jul-2022
URI: http://hdl.handle.net/10044/1/98530
DOI: 10.1038/s41746-022-00667-w
ISSN: 2398-6352
Publisher: Nature Research
Journal / Book Title: npj Digital Medicine
Volume: 5
Copyright Statement: © The Author(s) 2022. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
Sponsor/Funder: National Institute of Health Research
Keywords: Science & Technology
Life Sciences & Biomedicine
Health Care Sciences & Services
Medical Informatics
Publication Status: Published
Article Number: ARTN 118
Appears in Collections:Department of Surgery and Cancer
Faculty of Medicine
Institute of Global Health Innovation

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