Literature DB >> 17726126

Advanced statistics: developing a formal model of emergency department census and defining operational efficiency.

Thomas J Flottemesch1, Bradley D Gordon, Spencer S Jones.   

Abstract

BACKGROUND: Emergency department (ED) crowding has been a frequent topic of investigation, but it is a concept without an objective definition. This has limited the scope of research and progress toward the development of consistent and meaningful operational responses.
OBJECTIVES: To develop a straightforward model of ED census that incorporates concepts of ED crowding, daily patient surge, throughput time, and operational efficiency.
METHODS: Using 2005-2006 patient encounter data at a Level 1 urban trauma center, a set of three stylized facts describing daily patterns of ED census was observed. These facts guided the development of a formal, mathematical model of ED census. Using this model, a metric of ED operational efficiency and a forecast of ED census were developed.
RESULTS: The three stylized facts of daily ED census were 1) ED census is cyclical, 2) ED census exhibits an input-output relationship, and 3) unexpected shocks have long-lasting effects. These were represented by a three-equation system. This system was solved for the following expression, Census(t) = A(.) + B(.) cos(vT + epsilon) + a(e(t)), that captured the time path of ED census. Using nonlinear estimation, the parameters of this expression were estimated and a forecasting tool was developed.
CONCLUSIONS: The basic pattern of ED census can be represented by a straightforward expression. This expression can be quickly adapted to a variety of inquiries regarding ED crowding, daily surge, and operational efficiency.

Entities:  

Mesh:

Year:  2007        PMID: 17726126     DOI: 10.1197/j.aem.2007.05.011

Source DB:  PubMed          Journal:  Acad Emerg Med        ISSN: 1069-6563            Impact factor:   3.451


  4 in total

1.  Forecasting emergency department crowding: a discrete event simulation.

Authors:  Nathan R Hoot; Larry J LeBlanc; Ian Jones; Scott R Levin; Chuan Zhou; Cynthia S Gadd; Dominik Aronsky
Journal:  Ann Emerg Med       Date:  2008-04-03       Impact factor: 5.721

2.  A generic method for evaluating crowding in the emergency department.

Authors:  Andreas Halgreen Eiset; Mogens Erlandsen; Anders Brøns Møllekær; Julie Mackenhauer; Hans Kirkegaard
Journal:  BMC Emerg Med       Date:  2016-06-14

3.  Quantifying Dynamic Flow of Emergency Department (ED) Patient Managements: A Multistate Model Approach.

Authors:  Chung-Hsien Chaou; Te-Fa Chiu; Shin-Liang Pan; Amy Ming-Fang Yen; Shu-Hui Chang; Petrus Tang; Chao-Chih Lai; Ruei-Fang Wang; Hsiu-Hsi Chen
Journal:  Emerg Med Int       Date:  2020-12-03       Impact factor: 1.112

4.  Ensemble-based methods for forecasting census in hospital units.

Authors:  Devin C Koestler; Hernando Ombao; Jesse Bender
Journal:  BMC Med Res Methodol       Date:  2013-05-30       Impact factor: 4.615

  4 in total

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