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使用自动化电子邮件通知系统提高妇产科麻醉学研究员的 ACGME 合规性。

Improving ACGME Compliance for Obstetric Anesthesiology Fellows Using an Automated Email Notification System.

机构信息

Department of Anesthesiology, Vanderbilt University Medical Center, Nashville, Tennessee, United States.

Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, United States.

出版信息

Appl Clin Inform. 2021 May;12(3):479-483. doi: 10.1055/s-0041-1730323. Epub 2021 May 26.

Abstract

BACKGROUND

The Accreditation Council for Graduate Medical Education establishes minimum case requirements for trainees. In the subspecialty of obstetric anesthesiology, requirements for fellow participation in nonobstetric antenatal procedures pose a particular challenge due to the physical location remote from labor and delivery and frequent last-minute scheduling.

OBJECTIVES

In response to this challenge, we implemented an informatics-based notification system, with the aim of increasing fellow participation in nonobstetric antenatal surgeries.

METHODS

In December 2014 an automated email notification system to inform obstetric anesthesiology fellows of scheduled nonobstetric surgeries in pregnant patients was initiated. Cases were identified via daily automated query of the preoperative evaluation database looking for structured documentation of current pregnancy. Information on flagged cases including patient medical record number, operating room location, and date and time of procedure were communicated to fellows via automated email daily. Median fellow participation in nonobstetric antenatal procedures per quarter before and after implementation were compared using an exact Wilcoxon-Mann-Whitney test due to low baseline absolute counts. The fraction of antenatal cases representing nonobstetric procedures completed by fellows before and after implementation was compared using a Fisher's exact test.

RESULTS

The number of nonobstetric antenatal cases logged by fellows per quarter increased significantly following implementation, from median 0[0,1] to 3[1,6] cases/quarter ( = 0.007). Additionally, nonobstetric antenatal cases completed by fellows as a percentage of total antenatal cases completed increased from 14% in preimplementation years to 52% in postimplementation years ( < 0.001).

CONCLUSION

Through an automated email system to identify nonobstetric antenatal procedures in pregnant patients, we were able to increase the number of these cases completed by fellows during 3 years following implementation.

摘要

背景

研究生医学教育认证委员会为住院医师设定了最低病例要求。在产科麻醉学亚专业中,由于非产科产前程序的物理位置远离分娩和产房,并且经常是最后一刻安排,因此要求研究员参与其中是一个特殊的挑战。

目的

为了应对这一挑战,我们实施了一个基于信息学的通知系统,旨在增加研究员对非产科产前手术的参与度。

方法

2014 年 12 月,我们启动了一个自动电子邮件通知系统,通知产科麻醉学研究员有关孕妇计划中的非产科手术。通过每天自动查询术前评估数据库来识别病例,以查找当前妊娠的结构化文档。通过自动电子邮件每天向研究员传达标记病例的信息,包括患者病历号、手术室位置以及手术日期和时间。由于基线绝对计数较低,使用精确 Wilcoxon-Mann-Whitney 检验比较实施前后每季度非产科产前手术的研究员参与度中位数。使用 Fisher 确切检验比较实施前后研究员完成的产前病例中非产科手术的比例。

结果

实施后,研究员每季度记录的非产科产前病例数量显著增加,中位数从 0[0,1]增加到 3[1,6]例/季度(=0.007)。此外,研究员完成的非产科产前病例占完成的总产前病例的百分比从实施前的 14%增加到实施后的 52%(<0.001)。

结论

通过自动电子邮件系统识别孕妇的非产科产前程序,我们能够在实施后的 3 年内增加这些病例由研究员完成的数量。

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本文引用的文献

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