ESSENCE

The Louisiana Office of Public Health (OPH) Infectious Disease Epidemiology Section (IDEpi) conducts syndromic surveillance of Emergency Department (ED) visits through the Louisiana Early Event Detection System (LEEDS) and submits the collected data to ESSENCE. There are currently 86 syndromes defined in LEEDS including infectious disease, injury and environmental exposure syndromes, among others. LEEDS uses chief complaint, admit reason, and/or diagnosis fields to tag visits to relevant syndromes. Visits that do not have information in any of these fields, or do not fit any syndrome definition are tagged to Null syndrome. ESSENCE uses a different algorithm from LEEDS and only looks in chief complaint for symptom information to bin visits to syndromes defined in ESSENCE. Visits that do not fit the defined syndromes or do not contain any symptom information are tagged to Other syndrome. Since the transition from BioSense to ESSENCE, IDEpi has identified various data quality issues and has been working to address them. The NSSP team recently notified IDEpi that a large number of records are binning to Other syndrome, which led to the investigation of the possible underlying data quality issues captured in Other syndrome.

Objective:

This investigation takes a closer look at Other syndrome in ESSENCE and Null syndrome in LEEDS to understand what types of records are not tagged to a syndrome to elucidate data quality issues.

Oregon Public Health Division (OPHD), in collaboration with The Johns Hopkins University Applied Physics Laboratory, implemented Oregon ESSENCE in 2011. ESSENCE is an automated, electronic syndromic surveillance system that captures emergency department data from hospitals across Oregon. While each hospital system sends HL7 2.5.1-formatted messages, each uses a uniquely configured interface to capture, extract, and send data. Consequently, ESSENCE receives messages that vary greatly in content and structure. Emergency department data are ingested using the Rhapsody Integration Engine 6.2.1 (Orion Health, Auckland, NZ), which standardizes messages before entering ESSENCE. Mechanisms in the ingestion route (error-handling filters) identify messages that do not completely match accepted standards for submission. A sub-set of these previously-identified messages with errors are corrected within the route as they emerge. Existence of errors does not preclude a message’s insertion into ESSENCE. However, the quality and quantity of errors determine the quality of the data that ESSENCE uses. Unchecked, error accumulation also can cause strain to the integration engine. Despite ad-hoc processes to address errors, backlogs accrue. With no meta-data to assess the importance and source of backlogged errors, the ESSENCE team had no guide with which to mitigate errors. The ESSENCE team needed a way to determine which errors could be fixed by updating the Rhapsody Integration Engine and which required consultation with partner health systems and their data vendors. To formally address these issues, the ESSENCE team developed an error-capture module within Rhapsody to identify and quantify all errors identified in syndromic messages and to use as a guide to prioritize fixing new errors.

Objective:

To streamline emergency department data processing in Oregon ESSENCE (Oregon’s statewide syndromic surveillance) by systematically and efficiently addressing data quality issues among submitting hospital systems.

Overdose deaths involving opioids (i.e., opioid pain relievers and illicit opioids such as heroin) accounted for at least 63% (N = 33,091) of overdose deaths in 2015. Overdose deaths related to illicit opioids, heroin and illicitly-manufactured fentanyl, have rapidly increased since 2010. For instance, heroin overdose deaths quadrupled from 3,036 in 2010 to 12,989 in 2015. Unfortunately, timely response to emerging trends is inhibited by time lags for national data on both overdose mortality via vital statistics (8-12 months) and morbidity via hospital discharge data (over 2 years). Emergency department (ED) syndromic data can be leveraged to respond more quickly to emerging drug overdose trends as well as identify drug overdose outbreaks. CDC’s NSSP BioSense Platform collects near real-time ED data on approximately two-thirds of ED visits in the US. NSSP’s data analysis and visualization tool, Electronic Surveillance System for the Notification of Community-based Epidemics (ESSENCE), allows for tailored syndrome queries and can monitor ED visits related to heroin overdose at the local, state, regional, and national levels quicker than hospital discharge data.

Objective:

This paper analyzes emergency department syndromic data in the Centers for Disease Control and Prevention's (CDC) National Syndromic Surveillance Program’s (NSSP) BioSense Platform to understand trends in suspected heroin overdose.

In January 2017, the NSSP transitioned their BioSense analytical tools to Electronic Surveillance System for Early Notification of Community-Based Epidemics (ESSENCE). The chief complaint field in BioSense 2.0 was a concatenation of the record's chief complaint, admission reason, triage notes, and diagnostic impression. Following the transition to ESSENCE, the chief complaint field was comprised of the first chief complaint entered or the first admission reason, if the chief complaint was blank. Furthermore, the ESSENCE chief complaint field was electronically parsed (i.e., the original chief complaint text was altered to translate abbreviations and remove punctuation). This abstract highlights key findings from Maricopa County Department of Public Health's evaluation of the new chief complaint field, its impact on heat-related illness syndromic surveillance, and implications for ongoing surveillance efforts.

Objective:

To evaluate the effect and implications of changing the chief complaint field during the National Syndromic Surveillance Program (NSSP) transition from BioSense 2.0 analytical tools to BioSense Platform ESSENCE.