Opioid

Arguably the two most significant public health issues over the past two years have been the outbreak of ebola in West Africa and the rising epidemic of heroin use and overdoses. In the case of Ebola, the CDC issued guidance for inpatient facilities to screen for potential cases, however, there was little guidance for screening patients that presented to EMS workers. The West African pateint aht presented to the Emergency Department in Dallas was transported, unknowingly, by EMS, potentially exposing them and others to this deadly disease. Likewise, heroin has become an exploding epidemic in the United States with deaths from overdoses skyrocketing across the country. There are few data sources for overdoses that can alert and track real time instances of heroin overdose which are arguably the highest risk patients in the community. This will make it difficult for interventions in the community as expressed recently by the White House.

Objective

The objective of this oral presentation is to describe the use of near real time 911 Emergency Medical Services data in looking for suspected cases of Ebola and heroin cases in the community.

In October 2015, the Centers for Disease Control and Prevention (CDC) released health advisory #384 to inform people about increases in fentanyl fatalities. Florida’s statewide syndromic surveillance system, Electronic Surveillance System for the Early Notification of Community-based Epidemics (ESSENCE-FL), captures electronic death record data in near real time which allows for the monitoring of mortality trends across the state. One limitation of using death record data for fentanyl surveillance is the lack of a fentanyl-specific overdose ICD-10 code; however, the literal cause of death fields (“literals”) provide a level of detail that is rich enough to capture mentions of fentanyl use. The “literals” are a free text field on the death certificate, recorded by a physician at the time of death and detail the factors that led to the death. ESSENCE-FL has the benefit of not only receiving death record data in near real-time, but also receiving the literal cause of death fields. This work analyzes trends in fentanyl-associated mortality in Florida over time by using the literal cause of death fields within death records data obtained from ESSENCE-FL.

Objective

To characterize fentanyl-associated mortality in Florida using free text queries of the literal causes of death listed on death certificates.

Overdoses of heroin and prescription opioids are a growing cause of mortality in the United States. Deaths from opioids have contributed to a rise in the overall mortality rate of middle-aged white males during an era when other demographics are experiencing life expectancy gains. A successful public health intervention to reverse this mortality trend requires a detailed understanding of which populations are most affected and where those populations live. While mortality is the most relevant metric for this emerging challenge, increased burden on laboratory facilities can create significant delays in obtaining confirmation of which patients died from opioid overdoses.

Emergency department visits for opioid overdoses can provide a more timely proxy measure of overall opioid use. Unfortunately, chief complaints do not always contain an indication of opioid involvement. Overdose patients are not always conscious at registration which limits the amount of information they can provide. Menu-driven registration systems can lump all overdoses together regardless of substance. A more complete record of the emergency department interaction, such as that provided by triage notes, could provide the information necessary to differentiate opioid-related visits from other overdoses. 

Objective

To identify heroin- and opioid-related emergency department visits using pre-diagnositc data. To demonstrate the value of clinical notes to public health surveillance and situational awareness. 

Prescription Drug Monitoring Programs (PDMPs) are operating in 49 states and several U.S. territories. Current methods for surveillance of prescription drug related behaviors, include the mean daily dosage of morphine milligram equivalent (MME) per patient, annual percentage of days with overlapping prescriptions per patient, and annual multiple provider episodes for multiple controlled substance prescription drugs per patient that are described elsewhere.1,2 This work builds on these efforts by extending longitudinal methods to prescription drug behavior surveillance in order to predict risks associated with prescription drug use. 

Objective

This study aims to show the application of longitudinal statistical and epidemiological methods for building a proactive prescription drug surveillance system for public health.