title: Entropy: a conceptual approach to measuring situation-level workload within emergency care and its relationship to emergency department crowding.
abstract: BACKGROUND
  Emergency department (ED) crowding correlates with patient safety. Difficulties quantifying crowding and providing solutions were highlighted in the recent Institute of Medicine (IOM) report calling for the application of advanced industrial engineering (IE) research techniques to evaluate ED crowding. ED personnel workload is a related concept, with potential reciprocal effects between the two. Collaboration between emergency medicine and IE is needed to address crowding and ED personnel workload.
  
  
  OBJECTIVE
  We review ED crowding and workload literature, relationships between workload and ED crowding, and the potential application of information theory as implemented in IE frameworks entitled "entropy" in evaluating both topics.
  
  
  CONCLUSIONS
  IE techniques have applications for emergency medicine and have been successful in helping improve ED operations. Lean and Six Sigma applications are some of these techniques. Existing ED workload measures don't account for all aspects of work in the ED (acuity, efficiency, tasks, etc.) Crowding scales, such as NEDOCS (National ED Overcrowding Study) and EDWIN (ED Work Index), fail to predict ED crowding. A new measurement "entropy" may provide a more comprehensive evaluation of ED workload and may predict work overload seen with crowding. Entropy measures task-based work and the information flow involved. By assigning an entropy value to patient type-specific tasks, we might predict when the ED is overwhelmed, and crowded.
  
  
  CONCLUSIONS
  IE techniques provide solutions to the ED crowding problem and improve ED workload. We propose a technique novel to medicine: "Entropy," derived from information theory, which may provide insight into ED personnel workload, its potential for measuring ED crowding, and possibly, in predicting an overwhelming situation.
authors.affiliation: Department of Emergency Medicine, University of Rochester Medical Center, Rochester, New York.
authors.forename: Peter W
authors.initials: PW
authors.lastname: Crane
authors.affiliation: Department of Industrial Engineering, University at Buffalo, State University of New York, Buffalo, New York.
authors.forename: Yuan
authors.initials: Y
authors.lastname: Zhou
authors.affiliation: Department of Industrial Engineering, University at Buffalo, State University of New York, Buffalo, New York.
authors.forename: Yifan
authors.initials: Y
authors.lastname: Sun
authors.affiliation: Department of Industrial Engineering, University at Buffalo, State University of New York, Buffalo, New York.
authors.forename: Li
authors.initials: L
authors.lastname: Lin
authors.affiliation: Department of Emergency Medicine, University of Rochester Medical Center, Rochester, New York.
authors.forename: Sandra M
authors.initials: SM
authors.lastname: Schneider
mesh_terms: D003441:Crowding; D004636:Emergency Service, Hospital / Q000458:organization & administration* / Q000706:statistics & numerical data*; D006282:Health Personnel; D006801:Humans; D008962:Models, Theoretical; D062072:Patient Acuity; D057566:Self Report; D013997:Time Factors; D013996:Time and Motion Studies; D016526:Workload
keywords: boarding; crowding; operations; process improvement; workload