Patterns and factors associated with intensive use of ED services: implications for allocating resources

Am J Emerg Med. 2012 Nov;30(9):1884-94. doi: 10.1016/j.ajem.2012.04.001. Epub 2012 Jul 12.

Abstract

Aim: This study aims to better understand the patterns and factors associated with the use of emergency department (ED) services on high-volume and intensive (defined by high volume and high-patient severity) days to improve resource allocation and reduce ED overcrowding.

Methods: This study created a new index of "intensive use" based on the volume and severity of illness and a 3-part categorization (normal volume, high volume, intensive use) to measure stress in the ED environment. This retrospective, cross-sectional study collected data from hospital clinical and financial records of all patients seen in 2001 at an urban academic hospital ED.

Results: Multiple logistic regression models identified factors associated with high volume and intensive use. Factors associated with intensive days included being in a motor vehicle crash; having a gun or stab wound; arriving during the months of January, April, May, or August; and arriving during the days of Monday, Tuesday, or Wednesday. Factors associated with high-volume days included falling from 0 to 10 ft; being in a motor vehicle crash; arriving during the months of January, April, May, or August; and arriving during the days of Monday, Tuesday, or Wednesday.

Conclusion: These findings offer inputs for reallocating resources and altering staffing models to more efficiently provide high-quality ED services and prevent overcrowding.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Academic Medical Centers / statistics & numerical data
  • Adolescent
  • Adult
  • Aged
  • Aged, 80 and over
  • Cross-Sectional Studies
  • Crowding
  • Emergency Service, Hospital / organization & administration
  • Emergency Service, Hospital / statistics & numerical data*
  • Female
  • Hospitals, Urban / statistics & numerical data
  • Humans
  • Male
  • Middle Aged
  • Resource Allocation* / statistics & numerical data
  • Retrospective Studies
  • Seasons
  • Severity of Illness Index
  • Time Factors
  • Young Adult