Document Type
Article
Publication Date
1-4-2021
Abstract
Mobile phone applications (apps) have been used for patient follow-up in the postoperative period, specifically to assess for complications and patient satisfaction. Few studies have evaluated their use in regional anesthesia. The objective of this study was to compare follow-up response rates using manual phone calls versus an automated patient outreach (APO) app for peripheral nerve block patients. We hypothesized that the response rate would be higher in the APO group. A mobile app, "JeffAnesthesia," was developed, which sends notifications to patients to answer survey questions in the app. We randomly assigned patients who received peripheral nerve blocks for postoperative pain to either a manual phone call or an APO app group, with follow-up in each category occurring between postoperative days (POD) 14-21 and 90-100. In total, 60 patients were assigned to the phone call group and 60 patients to the APO app group. Between POD 14-21, 9 (15%) patients were reached in the manual phone call arm, and 16 (26.7%) patients were reached in the APO arm (p = 0.117). At POD 90-100, follow-up was successful with 5 (8.2%) in the manual phone call group vs. 3 (5.0%) patients in the APO app group (p = 0.300). Overall response rate was poor, with comparable response rates between groups. The APO method may reduce time spent by anesthesia staff on follow-up calls, but our data do not suggest this method improves response rates significantly. Further studies are needed to better understand the reasons for the poor response rate and strategies for improvement.
Recommended Citation
Ooi, Gavyn; Schwenk, Eric S.; Torjman, Marc C.; and Berg, Kent, "A Randomized Trial of Manual Phone Calls Versus Automated Text Messages for Peripheral Nerve Block Follow-Ups." (2021). Department of Anesthesiology Faculty Papers. Paper 67.
https://jdc.jefferson.edu/anfp/67
PubMed ID
33404791
Language
English
Comments
This article is the authors' final version prior to publication in Journal of Medical Systems, Volume 45, Issue 1, January 2021, Article number 7.
The published version is available at https://doi.org/10.1007/s10916-020-01699-z. Copyright © Ooi et al.