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Measuring Emergency Department Workload Perception Using Electronic Medical Record Measures of Patient Volume and Acuity.
Baymon, DaMarcus E; Shappell, Eric; Park, Yoon Soo; Aaronson, Emily; Egan, Daniel J; Raja, Ali S; Yun, Brian J.
Afiliação
  • Baymon DE; Department of Emergency Medicine, Brigham and Women's Hospital, Boston, Massachusetts; Harvard Medical School, Boston, Massachusetts. Electronic address: dbaymon@bwh.harvard.edu.
  • Shappell E; Harvard Medical School, Boston, Massachusetts; Department of Emergency Medicine, Massachusetts General Hospital, Boston, Massachusetts.
  • Park YS; Department of Emergency Medicine, Massachusetts General Hospital, Boston, Massachusetts.
  • Aaronson E; Harvard Medical School, Boston, Massachusetts; Department of Emergency Medicine, Massachusetts General Hospital, Boston, Massachusetts.
  • Egan DJ; Harvard Medical School, Boston, Massachusetts; Department of Emergency Medicine, Massachusetts General Hospital, Boston, Massachusetts.
  • Raja AS; Harvard Medical School, Boston, Massachusetts; Department of Emergency Medicine, Massachusetts General Hospital, Boston, Massachusetts.
  • Yun BJ; Department of Emergency Medicine, Boston Medical Center, Boston, Massachusetts.
J Emerg Med ; 66(3): e374-e380, 2024 Mar.
Article em En | MEDLINE | ID: mdl-38423864
ABSTRACT

BACKGROUND:

Workload in the emergency department (ED) fluctuates and there is no established model for measurement of clinician-level ED workload.

OBJECTIVE:

The aim of this study was to measure perceived ED workload and assess the relationship between perceived workload and objective measures of workload from the electronic medical record (EMR).

METHODS:

This study was conducted at a tertiary care, academic ED from July 1, 2020 through April 13, 2021. Attending workload perceptions were collected using a 5-point scale in three care areas with variable acuity. We collected eight EMR measures thought to correlate with perceived workload. EMR values were compared across areas of the department using ANOVA and correlated with attending workload ratings using linear regression.

RESULTS:

We collected 315 unique workload ratings, which were normally distributed. For the entire department, there was a weak positive correlation between reported workload perception and mean percentage of inpatient admissions (r = 0.23; p < 0.001), intensive care unit admissions (r = 0.2; p < 0.001), patient arrivals per shift (r = 0.14; p = 0.017), critical care billed visits (r = 0.22; p < 0.001), cardiopulmonary resuscitation code activations (r = 0.2; p < 0.001), and level 5 visits (r = 0.13; p = 0.02). There was weak negative correlation for ED discharges (r = -0.23; p < 0.001). Several correlations were stronger in individual care areas, including percent admissions in the lowest-acuity area (r = 0.43; p = 0.033) and patient arrivals in the highest-acuity area (r = 0.44; p < .01). No significant correlation was found in any area for observation admissions or trauma activations.

CONCLUSIONS:

In this study, EMR measures of workload were not closely correlated with ED attending physician workload perception. Future study should examine additional factors contributing to physician workload outside of the EMR.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Carga de Trabalho / Registros Eletrônicos de Saúde Limite: Humans Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Carga de Trabalho / Registros Eletrônicos de Saúde Limite: Humans Idioma: En Ano de publicação: 2024 Tipo de documento: Article