Accepted for/Published in: Journal of Medical Internet Research
Date Submitted: Oct 22, 2020
Date Accepted: Jun 14, 2021
Mobile Applications in Clinical and Perioperative Care for Anesthesia: A Narrative Review
ABSTRACT
Background:
With increasing use of smartphones by providers and patients alike, digital health specifically with the use of mobile applications, has the potential to transform perioperative care and education in anesthesia.
Objective:
This review describes the current scope of use of mobile applications in anesthesiology, their feasibility, as well as limitations.
Methods:
Literature was searched using PubMed, Scopus, and ClinicalTrials.gov for articles published from January 1, 2010 through April 1, 2020. Only English language studies were included. Articles were included if they examined the use of a mobile health application in the setting of anesthesia or in perioperative (immediate pre-, intra-, and post-operative) period. Studies were excluded if they explored video interventions or did not specifically examine the feasibility or efficacy of the mobile app.
Results:
Twenty-nine articles were included and identified three areas of clinical functionality: patient-centered care (pre-operative, intra-operative, post-operative), systems-based improvement, and medical education. Studies demonstrate feasibility and reliability of mobile apps for these functions, but many are only tested for efficacy in simulated environments or with small samples.
Conclusions:
Smartphone apps show promising evidence to improve communication between anesthesiologists, improve workflow efficiency, enhance medical education, and reduce hospital costs. However, there is need for validation and improvement before full implementation for the provider, patient and hospital systems. Future studies are needed to demonstrate meaningful clinical outcomes using high quality research guidelines specific to mobile technology.
Citation
Request queued. Please wait while the file is being generated. It may take some time.
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.