Examining the Utility of the Essence Syndromic Surveillance System in the Early Detection of Hospital Emergency Department Crowding
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Date
2019-03-30
Type of Work
Department
Public Health and Policy
Program
Doctor of Public Health
Citation of Original Publication
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Abstract
The pertinent information synthesized by well-designed surveillance operations are essential to the planning, implementation, and evaluation of both public health and healthcare services. Divergent applications within existing surveillance initiatives have subsequently led to novel uses of health-related data becoming increasingly valuable. Heightened surveillance techniques, such as syndromic surveillance, have revealed pragmatic capabilities that adequately complement the dynamic nature of public health programming. As syndromic surveillance is still an emerging science, scholarly activities probing the utility of emergency department (ED)-based syndromic surveillance systems have remained noticeably narrow in scope. However, it is commonly speculated that the inherent multifaceted functionalities of ED-based syndromic surveillance systems equip them with the potential to meaningfully enhance surveillance capacities, across a broader assortment of public health and healthcare settings.
The purpose of this dissertation study was to explore the utility of ED-based syndromic surveillance data for resolutions beyond infectious disease control and prevention. More specifically, this study examined ED utilization data, captured and forecasted by the Electronic Surveillance System for the Early Detection of Community-based Epidemics (ESSENCE), and its aptness for the early detection of ED crowding.
Pre-existing data extracted from the ESSENCE syndromic surveillance system and the County Hospital Alert Tracking System (CHATS), were cross-classified to test the principal hypotheses of this study. A multiple logistic regression model was employed to assess whether the odds of reported ED crowding increased on days when actual ED utilization counts surpassed the expected utilization counts forecasted by ESSENCE.
Findings from this investigative inquiry proved that ED-based syndromic surveillance data, may be able to serve as an early indicator of emergency department crowding. The increased odds observed in the multiple logistic regression supports our primary research hypothesis and warrants further exploration into the matter.
This dissertation was tailored for use as a foundational piece, to drive a series of studies to follow. Future research should seek to improve upon the examination methods modeled in this study, for the creation of a gauge for heightened awareness or increased risk of ED crowding. Ultimately, this study contributes to an increased understanding and acknowledgment of the adroit capabilities that ED-based syndromic surveillance systems possess. Many of which could contribute to the development of innovative solutions to a great number of public health challenges, through both individual and larger organizational efforts.