When the Safety Net Is Unsafe Real‐time Assessment of the Overcrowded Emergency Department

Abstract

Abstract. Although much work has been done evaluating causes for increased demand for emergency department (ED) services, few ways are available to help determine that an individual ED is overcrowded. Four calculations are proposed using real-time data for accurately diagnosing an ED with potential for failing both as a safety net and as a source for quality health care. The bed ratio (BR) accounts for the number of patients in relation to the available treatment spaces. The BR is obtained by adding the current number of ED patients to the predicted arrivals minus the predicted departures and dividing the result by the total number of treatment spaces. The acuity ratio (AR) measures the relative burden of illness in the ED. The AR is the average triage category of all patients in the ED. The provider ratio (PR) determines the volume of patients that can be evaluated and treated by the physician providers. The PR is found by dividing the arrivals per hour by the sum of the average patients per hour usually disposed for each provider on duty. From these ratios, the demand value (DV) is calculated, which gives an overall measure of current demand. The DV is found by taking the sum of the BR and PR and multiplying by the AR. A DV of more than 7 should initiate a specific assessment of the individual ratios in order to accurately diagnose the problem and institute action. Based on the values, predetermined processes can be instituted to help remedy the overcrowded situation. Trended over time, the ratios can provide the data needed for better resource assessment, planning, and allocation.

Centralized vs. Decentralized Ambulance Diversion: A Network Perspective

“…Threshold policies are abstractions from more complex workload measures of ED crowding proposed in the emergency medicine literature, which account for additional factors such as staffing and patient severity [Reeder and Garrison 2001, Bernstein et al 2003, Epstein and Tian 2006. Recent research shows that ED occupancy predicts overcrowding as well as these workload measures [Hoot et al 2007] and correlates well with the staff's perception of overcrowding [McCarthy et al 2008].…”

Emergency Department Overcrowding: Analysis of the Factors of Renege Rate

“…[6][7][8] Conceptual models such as the input-throughputoutput model, 9 the Fields chaos model, 10 and the ED Cardiac Analogy Model 11 have been introduced in an effort to understand the factors of overcrowding and their mechanisms. Even the definition of overcrowding is problematic, 12 giving rise to various proposals for measuring ED crowding [13][14][15] and developing consensus on indices of overcrowding. 16 More recently, the National ED Overcrowding Study has demonstrated a simple measure of ED overcrowding across multiple institutions.…”

From an Overcrowded to a Smoothly Functioning Emergency Department within Two Months

“…Some built mathematical models to define when an ED is crowded [7][8][9]. Yet, in some of them there was a mismatch between the definition of overcrowding according to these calculations, and the perception of overcrowding among the ED medical and nursing staff [7,10]. In others, the Emergency department work index (EDWIN) has been shown to be a strong predictor of ambulance diversion, and also to correlate well with staff perception of crowding [8,11].…”

“…Some built mathematical models to define when an ED is crowded [7][8][9]. Yet, in some of them there was a mismatch between the definition of overcrowding according to these calculations, and the perception of overcrowding among the ED medical and nursing staff [7,10].…”