Evidence map›Paper›PMID 39803611›Full record

ArticleAEM education and training2025

Prevalence and characteristics of group standardized letters of evaluation in emergency medicine: A cross-sectional observational study.

Morgan Sehdev, Daniel J Egan, Sharon Bord, Cullen Hegarty, Eric Shappell

Abstract read
In one paragraph

Article in AEM education and training, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Morgan SehdevHarvard-Affiliated Emergency Medicine Residency Brigham and Women's Hospital/Massachusetts General Hospital/Harvard Medical School Boston Massachusetts USA.ORCID https://orcid.org/0000-0002-2981-0512
Daniel J EganDepartment of Emergency Medicine Massachusetts General Hospital/Harvard Medical School Boston Massachusetts USA.
Sharon BordDepartment of Emergency Medicine The Johns Hopkins University School of Medicine Baltimore Maryland USA.ORCID https://orcid.org/0009-0008-5987-4139
Cullen HegartyDepartment of Emergency Medicine University of Minnesota Medical School St. Paul Minnesota USA.ORCID https://orcid.org/0000-0002-7249-8675
Eric ShappellDepartment of Emergency Medicine Massachusetts General Hospital/Harvard Medical School Boston Massachusetts USA.ORCID https://orcid.org/0000-0003-0281-3219

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The standardized letter of evaluation (SLOE) for emergency medicine (EM) is a well-established tool for residency selection. While previous work characterizes the utility and outcomes related to SLOE use, less is known about SLOE authorship patterns and trends. Objective: The objective was to measure the prevalence of group SLOEs in EM over time, characterize the role groups represented in group SLOEs, and compare the rating practices of groups of authors versus single authors. Methods: SLOE data from 2016 through 2021 were obtained from the CORD database. An algorithm was developed to process SLOE author fields to accomplish three tasks: (1) determine whether the SLOE was written by an individual or a group, (2) determine the number of named letter writers on group SLOEs, and (3) identify roles of individuals listed on group SLOEs. A total of 150 SLOEs were randomly selected for review by the study team to use as a standard to which algorithm performance was compared. Mean ratings were compared for (1) individual versus group SLOEs and (2) individual SLOEs from clerkship directors (CDs) versus others. Results: A total of 40,218 SLOEs met inclusion criteria. The algorithm performed well in detecting group SLOEs, authors, and titles. Institutions submitting only SLOEs written by a group of authors increased from 31.4% to 54.5%. Authors per group SLOE increased from 3.4 in 2016 to 4.0 in 2021. Mean ratings were slightly higher in individual SLOEs compared to group SLOEs. Individual SLOEs from non-CDs had higher ratings compared to those from CDs. Conclusions: The proportion of SLOEs authored by groups increased over the study interval. Grading practices are similar between group SLOEs and individual SLOEs authored by CDs. Individual SLOEs from non-CDs had slightly higher ratings compared to the other groups.

Identifiers

PMID39803611
PMCPMC11724697

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.