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Abstract
Objective
The aim of this project was to assess the face validity of surveillance case
definitions for heroin overdose in emergency medical services (EMS) and emergency
department syndromic surveillance (SyS) data systems by comparing case counts to
those found in a statewide emergency department (ED) hospital administrative billing
data system.
Introduction
In 2016, the Centers for Disease Control and Prevention funded 12 states, under the
Enhanced State Opioid Overdose Surveillance (ESOOS) program, to utilize state
Emergency Medical Services (EMS) and emergency department syndromic surveillance
(SyS) data systems to increase timeliness of state data on drug overdose events. An
important component of the ESOOS program is the development and validation of case
definitions for drug overdoses for EMS and ED SyS data systems with a focus on small
area anomaly detection. In fiscal year one of the grant Kentucky collaborated with
CDC to develop case definitions for heroin and opioid overdoses for both SyS and EMS
data. These drug overdose case definitions are compared between these two rapid
surveillance systems, and further compared to emergency department (ED) hospital
administrative claims billing data, to assess their face validity.
Methods
The most recent available data were pulled from multiple hospitals in a large
healthcare system serving an urban region of Kentucky. Definitions for acute heroin
overdose were applied to all three sources. For SyS and ED data, definitions were
queried against the same hospitals within this geographic region and aggregated to
week-level totals. SyS and ED data are similar with the exception of additional
textual information available in SyS (such as chief complaint). Our EMS definition
of heroin overdose was loosely based on a draft definition that was produced by the
Massachusetts Department of Public Health, and relies more on textual analysis
versus ICD10 codes used in SyS and ED data systems. While SyS and ED used the same
hospitals as the frame of selection, EMS used incidents that occurred in the
approximate catchment area served by those hospitals. Weekly totals from all three
data sources were plotted in R studio with LOESS-smoothed trend lines. Unsmoothed
times series plots also demonstrate highly correlated trends, but the smoothed trend
lines are less cluttered and easier to interpret.
Results
Visual interpretation of the LOESS-smoothed trend lines shows very similar
trajectories among all three sources [Fig 1]. The resultant graph demonstrates that
individually, the time courses described by SyS and EMS data track closely with the
one observed in ED data. The absolute counts between the three sources showed some
differences, as expected. The EMS system captures a slightly different cohort that
may include people that do not go to the ED (observation patients, refused
transport, etc.) and SyS/ED have slightly different definitions (as ED does not
include a free-text chief complaint. These types of limitations are better explored
through data linkage that may or may not include medical record review to establish
ground truth.
Conclusions
Public health surveillance of drug overdoses has traditionally relied on ED billing
data. In most states, however, there is a lag of at least several months before this
data becomes available for analysis. In some jurisdictions the delay may be
considerably longer. Rapid surveillance data sources may allow for more timely
identification of changes in overdose patterns at the local level. In addition,
SyS/EMS can be used together to confirm that a spike seen in one rapid system is
confirmed within the other, with relative ease.
Though the comparison is a rather simple or crude visual analysis of three data
systems at a common geographic level, there is still appears to be a common pattern
among the three systems. While this does not carry the validity of cross-data
matched analysis, it does provide some of the utility of looking at these system
collective without match; and therefore may be of use to surveillance users that may
be limited by de-identified data.
Heroin Overdoses in KY Region, 04/2016-09/2017
ISDS Annual Conference Proceedings 2018. This is an Open Access
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provided the original work is properly cited.