EMS runs for suspected opioid overdose: implications for surveillance and prevention - PubMed (original) (raw)

EMS runs for suspected opioid overdose: implications for surveillance and prevention

Amy Knowlton et al. Prehosp Emerg Care. 2013 Jul-Sep.

Abstract

Background: Opioid (including prescription opiate) abuse and overdose rates in the United States have surged in the past decade. The dearth and limitations of opioid abuse and overdose surveillance systems impede the development of interventions to address this epidemic. Objective. We explored evidence to support the validity of emergency medical services (EMS) data on naloxone administration as a possible proxy for estimating incidence of opioid overdose.

Methods: We reviewed data from Baltimore City Fire Department EMS patient records matched with dispatch records over a 13-month time period (2008-2009) based on 2008 Census data. We calculated incidence rates and patient demographic and temporal patterns of naloxone administration, and examined patient evaluation data associated with naloxone administration. Results were compared with the demographic distributions of the EMS patient and city populations and with prior study findings.

Results: Of 116,910 EMS incidents during the study period for patients aged 15 years and older, EMS providers administered naloxone 1,297 times (1.1% of incidents), an average of 100 administrations per month. The overall incidence was 1.87 administrations per 1,000 residents per year. Findings indicated that naloxone administration peaked in the summer months (31% of administrations), on weekends (32%), and in the late afternoon (4:00-5:00 pm [8%]); and there was a trend toward peaking in the first week of the month. The incidence of suspected opioid overdose was highest among male patients, white patients, and those in the 45-54-year age group. Findings on temporal patterns were comparable with findings from prior studies. Demographic patterns of suspected opioid overdose were similar to medical examiner reports of demographic patterns of fatal drug- or alcohol-related overdoses in Baltimore in 2008-2009 (88% of which involved opioids). The findings on patient evaluation data suggest some inconsistencies with previously recommended clinical indications of opioid overdose.

Conclusions: While our findings suggest limitations of EMS naloxone administration data as a proxy indicator of opioid overdose, the results provide partial support for using these data for estimating opioid overdose incidence and suggest ways to improve such data. The study findings have implications for an EMS role in conducting real-time surveillance and treatment and prevention of opioid abuse and overdose.

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Conflict of interest statement

Conflicts of interest: None.

Figures

Figure 1

Figure 1

Baltimore City Emergency Medical Services (EMS) naloxone administration incidents and all other EMS incidents by month and year (observed frequency and 95% confidence intervals) (October 2008-09).

Figure 2

Figure 2

Baltimore City Emergency Medical Services (EMS) incidents of naloxone administration and all other EMS incidents by day of the week (observed frequency and 95% confidence intervals) (October 2008-09).

Figure 3

Figure 3

Distribution of Baltimore City Emergency Medical Services (EMS) incidents and 95% confidence intervals of naloxone administration and all other EMS incidents by hour of the day (October 2008-09).

Figure 4

Figure 4

Distribution of naloxone administration by Baltimore City Emergency Medical Services by hour of the day (Walter & Elwood [1975] test of seasonality) (October 2008-09).

Figure 5

Figure 5

Distribution of naloxone administration by Baltimore City Emergency Medical Services by day of week (Walter & Elwood [1975] test of seasonality) (October 2008-09).

Figure 6

Figure 6

Distribution of naloxone administration by Baltimore City Emergency Medical Services by day of the month (Walter & Elwood [1975] test of seasonality) (October 2008-09). Note: The predicted number of incidents decreases at the end of the month due to fewer of these days in the data.

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