ArticleAEM education and training2021
Utilization of heat-mapping tools to match a resident staffing template to emergency department arrival patterns.
Article in AEM education and training, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- The risk of heat stress to South African emergency medicine registrars rotating through hospitals in warmer climate zones during summer months.International journal of biometeorology · 2025Article
- Utilization of heat-mapping tools to match a resident staffing template to emergency department arrival patterns.AEM education and training · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesAcademic emergency departments (ED) rely on a steady flow of patients to provide residents with good clinical training. Understanding institutional volume patterns allows training directors to create a schedule that maximizes learning opportunities while also adequately staffing the ED. Our primary objective of this study was to utilize heat-mapping software to optimize resident staffing in an academic ED.
methodsHeat-mapping tools within Microsoft Excel were utilized to overlay ED patient arrival patterns on top of the potential patients per hour based on published productivity data for trainees and historical averages for advanced practice providers at our institution. Time frames for under- and overstaffing were identified and color-coded. This analysis informed a revised schedule template and the same heat-mapping process was used to determine the appropriateness of the revised staffing template.
resultsThe heat map for the original schedule template revealed understaffing in the morning and overstaffing the rest of the day. Informed by these findings, schedule adjustments were made. There was no net increase in the number of resident or advanced practice provider coverage hours. Prior to implementation, the ED was understaffed by 5% or more during 18.4% of operating hours. Following changes to the staffing template, only 5.9% of operating hours were understaffed (p < 0.001). Furthermore, significant understaffing (20% or more) decreased from 16.6% to 3.1% (p < 0.001).
conclusionsNovel use of heat-mapping software has the potential to successfully match ED patient arrival patterns to an optimal resident staffing template. Future directions include incorporation of variable resident productivity to account for fatigue as the shift progresses.
Identifiers
What OpenQuestion holds
Registered trials
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.