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The Bone & Joint Journal
Vol. 105-B, Issue 8 | Pages 843 - 849
1 Aug 2023
Grandhi TSP Fontalis A Raj RD Kim WJ Giebaly DE Haddad FS

Telehealth has the potential to change the way we approach patient care. From virtual consenting to reducing carbon emissions, costs, and waiting times, it is a powerful tool in our clinical armamentarium. There is mounting evidence that remote diagnostic evaluation and decision-making have reached an acceptable level of accuracy and can safely be adopted in orthopaedic surgery. Furthermore, patients’ and surgeons’ satisfaction with virtual appointments are comparable to in-person consultations. Challenges to the widespread use of telehealth should, however, be acknowledged and include the cost of installation, training, maintenance, and accessibility. It is also vital that clinicians are conscious of the medicolegal and ethical considerations surrounding the medium and adhere strictly to the relevant data protection legislation and storage framework. It remains to be seen how organizations harness the full spectrum of the technology to facilitate effective patient care.

Cite this article: Bone Joint J 2023;105-B(8):843–849.


The Bone & Joint Journal
Vol. 103-B, Issue 6 Supple A | Pages 196 - 204
1 Jun 2021
Chen JS Buchalter DB Sicat CS Aggarwal VK Hepinstall MS Lajam CM Schwarzkopf RS Slover JD

Aims

The COVID-19 pandemic led to a swift adoption of telehealth in orthopaedic surgery. This study aimed to analyze the satisfaction of patients and surgeons with the rapid expansion of telehealth at this time within the division of adult reconstructive surgery at a major urban academic tertiary hospital.

Methods

A total of 334 patients underging arthroplasty of the hip or knee who completed a telemedicine visit between 30 March and 30 April 2020 were sent a 14-question survey, scored on a five-point Likert scale. Eight adult reconstructive surgeons who used telemedicine during this time were sent a separate 14-question survey at the end of the study period. Factors influencing patient satisfaction were determined using univariate and multivariate ordinal logistic regression modelling.