Literature DB >> 16797427

A comparison of anesthesiology resident and faculty electronic evaluations before and after implementation of automated electronic reminders.

James M Blum1, Sachin Kheterpal, Kevin K Tremper.   

Abstract

STUDY
OBJECTIVE: To develop an automated e-mail reminder system to contact residents and faculty regarding incomplete evaluations. DESIGN, SETTING, INTERVENTION, AND MEASUREMENTS: In the retrospective study, two 9-month periods were evaluated representing pre- and post-introduction of the automated e-mail reminder system. Data collected contained the number of evaluations completed and the rating of residents and faculty at the University of Michigan Health System in 5 different categories on a 5-point scale. MAIN
RESULTS: The use of electronic reminders resulted in a nearly 4-fold increase in the number of resident evaluations by faculty from 1050 to 3761. Faculty completing evaluations increased from 40 (61%) to 66 (100%). The mean evaluation scores showed statistically significant but clinically negligible change for resident judgement, interpersonal skills, and intraoperative management. Resident preoperative evaluation and knowledge did not show statistically significant changes. Residents completing evaluations of faculty increased from 244 to 1798, and the number of residents completing evaluations rose from 40 (56%) to 87 (100%). There were no statistically significant changes in the evaluation of faculty except in the category of feedback.
CONCLUSION: An automated e-mail reminder system implemented to contact residents and faculty regarding incomplete evaluations for residents and faculty dramatically enhanced participation in the evaluation process.

Mesh:

Year:  2006        PMID: 16797427     DOI: 10.1016/j.jclinane.2005.10.008

Source DB:  PubMed          Journal:  J Clin Anesth        ISSN: 0952-8180            Impact factor:   9.452


  1 in total

1.  RadRemind!-an Automated Paging System for Reminding Radiology Residents of Their Roles and Responsibilities.

Authors:  Shawn Lyo; Arkadij Grigorian; Dan Cohen-Addad; Srinivas Kolla
Journal:  J Digit Imaging       Date:  2021-03-19       Impact factor: 4.056

  1 in total

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