Accepted for/Published in: Journal of Medical Internet Research
Date Submitted: Jun 23, 2022
Open Peer Review Period: Jun 23, 2022 - Aug 18, 2022
Date Accepted: Dec 23, 2022
Date Submitted to PubMed: Dec 25, 2022
(closed for review but you can still tweet)
Digital health applications to establish a remote diagnosis for orthopedic knee disorders: a scoping review.
ABSTRACT
Background:
Digital health and other forms of telemedicine can add value in optimizing healthcare for patients and healthcare providers. Aim of this study was to investigate the currently available digital health and telemedicine applications to establish a primary knee diagnosis in orthopedic surgery without face-to-face contact between patient and physician.
Objective:
Provide an overview of the available applications to establish a primary diagnosis for knee disorders.
Methods:
A systematic scoping review was conducted in the PUBMED and EMBASE database according to the PRISMA Extension for Scoping Reviews (PRISMA-ScR) statement. The inclusion criteria were studies reporting methods to establish a primary knee diagnosis using digital health or telemedicine.
Results:
A total of 7 articles was included after full text screening. Two categories to determine a primary diagnosis were identified: screening studies (n=4) and decision support studies (n=3). There was a large heterogeneity in the included studies in used algorithms, disorders, input parameters and outcome measurements. The included studies show a relatively high sensitivity in diagnosing a limited set of 25 knee disorders. However, the included applications were in general not accurate enough to make a specific diagnosis.
Conclusions:
This scoping review shows that it is currently not possible to establish a reliable remote diagnosis for knee disorders in orthopedic practice. To date there is limited evidence that digital health applications can actually assist a patient or orthopedic surgeon in establishing the primary diagnosis for knee disorders. Future research should aim at integrating multiple sources of information, standardizing study designs with close collaboration between clinicians, data scientists, data managers, lawyers and service users in order to create reliable and secure databases.
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Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.