Digital Health Applications to Establish a Remote Diagnosis of Orthopedic Knee Disorders: Scoping Review

Abstract

Background: Knee pain is highly prevalent worldwide, and this number is expected to rise in the future. The COVID-19 outbreak, in combination with the aging population, rising health care costs, and the need to make health care more accessible worldwide, has led to an increasing demand for digital health care applications to deliver care for patients with musculoskeletal conditions. Digital health and other forms of telemedicine can add value in optimizing health care for patients and health care providers. This might reduce health care costs and make health care more accessible while maintaining a high level of quality. Although expectations are high, there is currently no overview comparing digital health applications with face-to-face contact in clinical trials to establish a primary knee diagnosis in orthopedic surgery.

Objective: This study aimed to investigate the currently available digital health and telemedicine applications to establish a primary knee diagnosis in orthopedic surgery in the general population in comparison with imaging or face-to-face contact between patients and physicians.

Methods: A scoping review was conducted using the PubMed and Embase databases according to the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) statement. The inclusion criteria were studies reporting methods to determine a primary knee diagnosis in orthopedic surgery using digital health or telemedicine. On April 28 and 29, 2021, searches were conducted in PubMed (MEDLINE) and Embase. Data charting was conducted using a predefined form and included details on general study information, study population, type of application, comparator, analyses, and key findings. A risk-of-bias analysis was not deemed relevant considering the scoping review design of the study.

Results: After screening 5639 articles, 7 (0.12%) were included. In total, 2 categories to determine a primary diagnosis were identified: screening studies (4/7, 57%) and decision support studies (3/7, 43%). There was great heterogeneity in the included studies in algorithms used, disorders, input parameters, and outcome measurements. No more than 25 knee disorders were included in the studies. The included studies showed a relatively high sensitivity (67%-91%). The accuracy of the different studies was generally lower, with a specificity of 27% to 48% for decision support studies and 73% to 96% for screening studies.

Conclusions: This scoping review shows that there are a limited number of available applications to establish a remote diagnosis of knee disorders in orthopedic surgery. To date, there is limited evidence that digital health applications can assist patients or orthopedic surgeons in establishing the primary diagnosis of knee disorders. Future research should aim to integrate multiple sources of information and a standardized study design with close collaboration among clinicians, data scientists, data managers, lawyers, and service users to create reliable and secure databases.

Keywords: artificial intelligence; diagnosis; digital health; eHealth; knee; mHealth; mobile health; mobile phone; musculoskeletal system; orthopedic surgery; remote patient management; telemedicine.