Emergency department crowding: consensus development of potential measures

Ann Emerg Med. 2003 Dec;42(6):824-34. doi: 10.1016/S0196064403008163.


Study objective: We identify measures of emergency department (ED) and hospital workflow that would be of value in understanding, monitoring, and managing crowding.

Methods: A national group of 74 experts developed 113 potential measures using a conceptual model of ED crowding that segmented the measures into input, throughput, and output categories. Ten investigators then used group consensus methods to revise and consolidate them into a refined set of 30 measures that were rated by all 74 experts, who used a magnitude estimation technique on a Web site. Each measure was compared with a standard to obtain numeric ratings for feasibility, affordability, early warning potential, long-term planning potential, a summary rating of operational usefulness, and research potential. After review of the comprehensiveness of the resulting measures, 8 additional measures were developed and also rated by all reviewers.

Results: The original set of 113 measures (46 input, 35 throughput, and 32 output) was reduced to 38 through the iterative revision and rating process (15 input, 9 throughput, and 14 output). Summary scores in each rating category showed significant variation in ratings among the various potential measures. For measures that address similar concepts, the priority ranking depended on the rating category chosen.

Conclusion: The final 38 measures of ED and hospital workflow provide a useful pool from which EDs and policymakers can draw to improve their ability to understand and address the issue of ED crowding. These measures require rigorous testing for feasibility, reliability, and value.

Publication types

  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Consensus*
  • Emergency Service, Hospital / organization & administration*
  • Health Facility Planning / methods*
  • Health Services Needs and Demand / organization & administration*
  • Hospital Bed Capacity
  • Humans
  • Models, Organizational
  • United States