Tsai Stella

The opioid drug overdose crisis presents serious challenges to state-based public health surveillance programs, not the least of which is uncertainty in the detection of cases in existing data systems. New Jersey historically had slightly higher unintentional drug overdose death rates than the national average, but by 2001 dramatic increases in drug overdose deaths in states like West Virginia began to drive up the national rate (Figure 1). Although the rise in New Jersey's fatal overdose rates has mirrored the national rate since 1999, the rate has dramatically increased since 2011- from 9.7 per 100,000 (868 deaths) to 21.9 per 100,000 in 2016 (1,931 deaths), an increase of 125% in five years.1 The New Jersey Department of Health has been funded by the Centers for Disease Control and Prevention (CDC) to conduct surveillance of opioid-involved overdoses through the Enhanced Surveillance of Opioid-Involved Overdose in States (ESOOS) program, and to conduct syndromic surveillance through the National Syndromic Surveillance Program (NSSP); this has presented a collaboration opportunity for the Department's surveillance grantee programs to use existing resources to evaluate and refine New Jersey’s drug overdose case definitions and develop new indicators to measure the burden of overdose throughout the state and to facilitate effective responses.

Objective: Link syndromic surveillance data for potential opioid-involved overdoses with hospital discharge data to assess positive predictive value of CDC Opioid Classifiers for conducting surveillance on acute drug overdoses.

When the opioid epidemic began in the early 1990s, pills such as oxycodone were the primary means of abuse. Beginning in 2010, injection use of, first, heroin and then synthetic opioids dramatically increased, which led the number of overdose deaths involving opioids to increase fivefold between 1999 and 2016.1 It would be expected that BBP rates would rise with this increase in injection use, and, nationally, there has been a rise in acute hepatitis C (HCV) rates, although the other two main BBPs, acute hepatitis B (HBV) and acute human immunodeficiency virus (HIV) have been flat and declining, respectively.2,3 In this study, we compared New Jersey's reported incidence of these three BBPs (acute HBV, acute HCV, and HIV) over five years (2013-2017) with syndromic surveillance data for opioid use over the same time period in order to test the hypothesis that emergency department (ED) visits for opioid use could be used as a predictor of BBP infection.

Objective: To utilize New Jersey's syndromic surveillance data in the study and comparison of trends in injection opioid use and infection with selected bloodborne pathogens (BBPs) over the years 2013-2017.

In early May of 2013, two chemical spills occurred within high schools in Atlantic county. These incidents, occurring within a week of each other, highlighted the need to strengthen statewide syndromic surveillance of illnesses caused by such exposures. In response to these spills, a new 'chemical exposure' classifier was created in EpiCenter, New JerseyÕs syndromic surveillance system, to track future events by monitoring registration chief complaint data taken from emergency department visits. The primary objective behind creation of the new classifier is to provide local epidemiologists with prompt notification once EpiCenter detects an abnormal numbers of chemical exposure cases.

Objective

To describe the development of a new chemical exposure classifier in New Jersey's syndromic surveillance system (EpiCenter).

In the summer of 2001, New Jersey (NJ) was in the process of developing surveillance activities for bioterrorism. On September 11, 2001, the U.S. suffered a major terrorist attack. Approximately a month later, Anthrax-laced letters were processed through a New Jersey Postal Distribution Center (PDC). As a result of these events, the state instituted simplistic surveillance activities in emergency departments (ED's). Over time, this initial system has developed into a broader, more streamlined approach to surveillance that now includes syndromic data e.g., Influenza-like illness (ILI) as well as the use of technology (automated surveys, real-time data connections, and alert analysis) to achieve surveillance goals and provide daily information to public health partners in local health departments and DHSS response colleagues.

Objective

To describe the improvements in New Jersey's Emergency Department surveillance system over time.

EpiCenter, NJ’s statewide syndromic surveillance system, collects ED registration data. The system uses chief complaint data to classify ED visits into syndrome categories and provides alerts to state and local health departments for surveillance anomalies. After the 2014 Ebola outbreak in West Africa, the New Jersey Department of Health (NJDOH) started collecting medical notes including triage notes, which contain more specific ED visit information than chief complaint, from 10 EDs to strengthen HAI syndromic surveillance efforts. In 2017, the NJDOH was aware of one NJ resident whose surgical site was infected following a cosmetic procedure outside of the US. This event triggered an intensive data mining using medical notes collected in EpiCenter. The NJDOH staff searched one week of medical notes data in EpiCenter with a specific keyword to identify additional potential cases of surgical-site infections (SSI) that could be associated with medical tourism.

Objective:

Medical notes provide a rich source of information that can be used as additional supporting information for healthcare-associated infection (HAI) investigations. The medical notes from 10 New Jersey (NJ) emergency departments (ED) were searched to identify cases of surgical-site infections (SSI).