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

Acad Emerg Med. 2007 Sep;14(9):799-809. doi: 10.1197/j.aem.2007.05.011.


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.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Censuses*
  • Crowding
  • Efficiency, Organizational*
  • Emergency Service, Hospital / organization & administration*
  • Humans
  • Models, Statistical*
  • Patient Transfer / organization & administration
  • Time Factors
  • Trauma Centers
  • Urban Population