Emergency Medical Services and Syndromic Surveillance: A Comparison With Traditional Surveillance and Effects on Timeliness

Abstract

Objective: Traditional public health surveillance of nonfatal opioid overdose relies on emergency department (ED) billing data, which can be delayed substantially. We compared the timeliness of 2 new data sources for rapid drug overdose surveillance-emergency medical services (EMS) and syndromic surveillance-with ED billing data.

Methods: We used data on nonfatal opioid overdoses in Kentucky captured in EMS, syndromic surveillance, and ED billing systems during 2018-2019. We evaluated the time-series relationships between EMS and ED billing data and syndromic surveillance and ED billing data by calculating cross-correlation functions, controlling for influences of autocorrelations. A case example demonstrates the usefulness of EMS and syndromic surveillance data to monitor rapid changes in opioid overdose encounters in Kentucky during the COVID-19 epidemic.

Results: EMS and syndromic surveillance data showed moderate-to-strong correlation with ED billing data on a lag of 0 (r = 0.694; 95% CI, 0.579-0.782; t = 9.73; df = 101; P < .001; and r = 0.656; 95% CI, 0.530-0.754; t = 8.73; df = 101; P < .001; respectively) at the week-aggregated level. After the COVID-19 emergency declaration, EMS and syndromic surveillance time series had steep increases in April and May 2020, followed by declines from June through September 2020. The ED billing data were available for analysis 3 months after the end of a calendar quarter but closely followed the trends identified by the EMS and syndromic surveillance data.

Conclusion: Data from EMS and syndromic surveillance systems can be reliably used to monitor nonfatal opioid overdose trends in Kentucky in near-real time to inform timely public health response.

Keywords: COVID-19; EMS; opioid overdose; syndromic surveillance; time-series analysis.

Figure 1

Suspected opioid overdose encounters, by week and surveillance data source (emergency department billing, emergency medical services, and syndromic surveillance), with 4-week rolling average, Kentucky, 2018-2019. The 4-week rolling average provides a general smoothing of each surveillance system for the purpose of visual comparison. Data sources: claims files, Cabinet for Health and Family Services, Office of Health Data and Analytics; Kentucky Board of Emergency Medical Services: Kentucky State Ambulance Reporting System; and Kentucky Syndromic Surveillance Data Cabinet for Health and Family Services, Department for Public Health.

Figure 2

Cross-correlation function between rapid surveillance systems (emergency medical services and syndromic surveillance) and a traditional surveillance system (emergency department billing) in detecting suspected opioid overdose cases, by various positive and negative lags, Kentucky, 2018-2019. The graphs visually indicate a moderately strong correlation at lag of 0 (simultaneity). The correlations at lag different from 0 are relatively weak. If there were no real relationship between the systems, much lower correlation would be expected (similar to white noise). Data sources: claims files, Cabinet for Health and Family Services, Office of Health Data and Analytics; Kentucky Board of Emergency Medical Services: Kentucky State Ambulance Reporting System; and Kentucky Syndromic Surveillance Data Cabinet for Health and Family Services, Department for Public Health.

Figure 3

Suspected opioid overdose encounters, by week and surveillance data source (emergency department billing, emergency medical services, and syndromic surveillance), with 4-week rolling average, Kentucky, January 1, 2019, through September 30, 2020. The solid vertical line indicates when a national emergency was declared for COVID-19, on March 13, 2020. At the time of analysis, emergency department billing data were available only through quarter 2 of 2020, confirming the large increase in opioid overdoses several months after initial indications in emergency medical services and syndromic surveillance data. Data sources: claims files, Cabinet for Health and Family Services, Office of Health Data and Analytics; Kentucky Board of Emergency Medical Services: Kentucky State Ambulance Reporting System; and Kentucky Syndromic Surveillance Data Cabinet for Health and Family Services, Department for Public Health.