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Introduction Linking emergency medical services (EMS) data to emergency department (ED) data enables assessing the continuum of care and evaluating patient outcomes. We developed novel methods to enhance linkage performance and analysis of EMS and ED data for opioid overdose surveillance in North Carolina.Methods We identified data on all EMS encounters in North Carolina during January 1–November 30, 2017, with documented naloxone administration and transportation to the ED. We linked these data with ED visit data in the North Carolina Disease Event Tracking and Epidemiologic Collection Tool. We manually reviewed a subset of data from 12 counties to create a gold standard that informed developing iterative linkage methods using demographic, time, and destination variables. We calculated the proportion of suspected opioid overdose EMS cases that received International Classification of Diseases, Tenth Revision, Clinical Modificationdiagnosis codes for opioid overdose in the ED.Results We identified 12 088 EMS encounters of patients treated with naloxone and transported to the ED. The 12-county subset included 1781 linkage-eligible EMS encounters, with historical linkage of 65.4% (1165 of 1781) and 1.6% false linkages. Through iterative linkage methods, performance improved to 91.0% (1620 of 1781) with 0.1% false linkages. Among statewide EMS encounters with naloxone administration, the linkage improved from 47.1% to 91.1%. We found diagnosis codes for opioid overdose in the ED among 27.2% of statewide linked records.Practice Implications Through an iterative linkage approach, EMS–ED data linkage performance improved greatly while reducing the number of false linkages. Improved EMS–ED data linkage quality can enhance surveillance activities, inform emergency response practices, and improve quality of care through evaluating initial patient presentations, field interventions, and ultimate diagnoses.

Objectives Studies describing linkage of ambulance trips and emergency department (ED) visits of patients with opioid-related overdose (ORO) are limited. We linked records of patients experiencing ORO from ambulance trip and ED visit records in Massachusetts during April 1–June 30, 2017.Methods We estimated the positive predictive value of ORO-capturing definitions by examining the narratives and triage notes of a sample of OROs from each data source. Because of a lack of common unique identifiers, we deterministically linked OROs to records in the counter data set on date of birth, incident date, facility, and sex. To validate the linkage strategy, we compared ambulance trip narratives with ED triage notes and chief complaints for a sample of pairs.Results Of 3203 ambulance trips for ORO and 3046 ED visits for ORO, 82% and 63%, respectively, matched a record in the counter data set on date of birth, incident date, facility, and sex. In 200 randomly selected linked pairs from a final linked data set of 3006 paired records, only 5 (3%) appeared to be false matches.Practice Implications This exercise demonstrated the feasibility of linking ORO records between 2 data sets without a unique identifier. Future analyses of the linked data could produce insights not available from analyzing either data set alone. Linkage using 2 rapidly available data sets can actively inform the state’s public health opioid overdose response and allow for de-duplicating counts of OROs treated by ambulance, in an ED, or both.

Federal and state enforcement authorities have increasingly intervened on the criminal overprescribing of opioids. However, little is known about the health effects these enforcement actions have on patients experiencing disrupted access to prescription opioids or medication-assisted treatment/medication for opioid use disorder. Simultaneously, opioid death rates have increased. In response, the Maryland Department of Health (MDH) has worked to coordinate mitigation strategies with enforcement partners (defined as any federal, state, or local enforcement authority or other governmental investigative authority). One strategy is a standardized protocol to implement emergency response functions, including rapidly identifying health hazards with real-time data access, deploying resources locally, and providing credible messages to partners and the public. From January 2018 through October 2019, MDH used the protocol in response to 12 enforcement actions targeting 34 medical professionals. A total of 9624 patients received Schedule II-V controlled substance prescriptions from affected prescribers under investigation in the 6 months before the respective enforcement action; 9270 (96%) patients were residents of Maryland. Preliminary data indicate fatal overdose events and potential loss of follow-up care among the patient population experiencing disrupted health care as a result of an enforcement action. The success of the strategy hinged on endorsement by leadership; the establishment of federal, state, and local roles and responsibilities; and data sharing. MDH’s approach, data sources, and lessons learned may support health departments across the country that are interested in conducting similar activities on the front lines of the opioid crisis.

Objectives Increasing knowledge about the toxicology of drug overdose and substance misuse (DOSM) is important in improving our understanding of the epidemic. We describe the Minnesota Drug Overdose and Substance Use Pilot Surveillance Activity, which started collecting data on emergency department (ED) visits attributable to DOSM in 2017, with a focus on the toxicology results of a subset of clinical encounters.Methods From November 1, 2017, through January 30, 2020, we collected near–real-time data on DOSM-related ED encounters. The Minnesota Department of Health Public Health Laboratory tested leftover clinical specimens (blood and/or urine) for the presence of various substances for patients who died, were hospitalized, had an atypical clinical presentation, or were part of a local drug overdose cluster. Testing looked for >250 drugs or their metabolites, including those commonly misused (eg, methamphetamine, cocaine), prescription medications, synthetic cannabinoids and cathinones, and opioids. We describe characteristics of the overall group and a subgroup of clinical encounters with toxicology results.Results Specimens submitted from 6 EDs during the study period represented 239 clinical encounters. Methamphetamine was the most frequently detected substance (67.4%) but was suspected in only 45.6% of encounters. At least 1 opioid was detected in 42.5% of encounters but suspected in only 29.7%. Testing also detected potential adulterants and additives (eg, fentanyl, fentanyl analogues, levamisole) and showed frequent patient exposure to substances not reported by patients or suspected by clinicians. Nearly half (44.4%) of clinical encounters had >1 substance detected.Conclusions ED surveillance for DOSM encounters, enhanced by toxicology testing, can provide local situational awareness on overdoses, prevent potential mischaracterization of the true drug overdose epidemic, and inform harm reduction and drug overdose prevention efforts.

Objectives Drug overdose deaths in Connecticut increasingly involve a growing number of fentanyl analogs and other novel nonfentanyl synthetic opioids (ie, novel synthetics). Current postmortem toxicology testing methods often lack the sophistication needed to detect these compounds. We examined how improved toxicology testing of fatal drug overdoses can determine the prevalence and rapidly evolving trends of novel synthetics.Methods From 2016 to June 2019, the Connecticut Office of the Chief Medical Examiner increased its scope of toxicology testing of suspected drug overdose deaths in Connecticut from basic to enhanced toxicology testing to detect novel synthetics. The toxicology laboratory also expanded its testing panels during this time. We analyzed toxicology results to identify and quantify the involvement of novel synthetics over time.Results From 2016 to June 2019, 3204 drug overdose deaths received enhanced toxicology testing; novel synthetics were detected in 174 (5.4%) instances. Ten different novel synthetics were detected with 205 total occurrences. Of 174 overdose deaths with a novel synthetic detected, most had 1 (n = 146, 83.9%) or 2 (n = 26, 14.9%) novel synthetics detected, with a maximum of 4 novel synthetics detected. Para-fluorobutyrylfentanyl/FIBF, furanylfentanyl, and U-47700 were most identified overall, but specific novel synthetics came in and out of prominence during the study period, and the variety of novel synthetics detected changed from year to year.Conclusions Enhanced toxicology testing for drug overdose deaths is effective in detecting novel synthetics that are not identified through basic toxicology testing. Identifying emerging novel synthetics allows for a timely and focused response to potential drug outbreaks and illustrates the changing drug market.

Objectives Tracking nonfatal overdoses in the escalating opioid overdose epidemic is important but challenging. The objective of this study was to create an innovative case definition of opioid overdose in North Carolina emergency medical services (EMS) data, with flexible methodology for application to other states’ data.Methods This study used de-identified North Carolina EMS encounter data from 2010-2015 for patients aged >12 years to develop a case definition of opioid overdose using an expert knowledge, rule-based algorithm reflecting whether key variables identified drug use/poisoning or overdose or whether the patient received naloxone. We text mined EMS narratives and applied a machine-learning classification tree model to the text to predict cases of opioid overdose. We trained models on the basis of whether the chief concern identified opioid overdose.Results Using a random sample from the data, we found the positive predictive value of this case definition to be 90.0%, as compared with 82.7% using a previously published case definition. Using our case definition, the number of unresponsive opioid overdoses increased from 3412 in 2010 to 7194 in 2015. The corresponding monthly rate increased by a factor of 1.7 from January 2010 (3.0 per 1000 encounters; n = 261 encounters) to December 2015 (5.1 per 1000 encounters; n = 622 encounters). Among EMS responses for unresponsive opioid overdose, the prevalence of naloxone use was 83%.Conclusions This study demonstrates the potential for using machine learning in combination with a more traditional substantive knowledge algorithm-based approach to create a case definition for opioid overdose in EMS data.

Objective No case definition exists that allows public health authorities to accurately identify opioid overdoses using emergency medical services (EMS) data. We developed and evaluated a case definition for suspected nonfatal opioid overdoses in EMS data.Methods To identify suspected opioid overdose–related EMS runs, in 2019 the Rhode Island Department of Health (RIDOH) developed a case definition using the primary impression, secondary impression, selection of naloxone in the dropdown field for medication given, indication of medication response in a dropdown field, and keyword search of the report narrative. We developed the case definition with input from EMS personnel and validated it using an iterative process of random medical record review. We used naloxone administration in consideration with other factors to avoid misclassification of opioid overdoses.Results In 2018, naloxone was administered during 2513 EMS runs in Rhode Island, of which 1501 met our case definition of a nonfatal opioid overdose. Based on a review of 400 randomly selected EMS runs in which naloxone was administered, the RIDOH case definition accurately identified 90.0% of opioid overdoses and accurately excluded 83.3% of non–opioid overdose–related EMS runs. Use of the case definition enabled analyses that identified key patterns in overdose locations, people who experienced repeat overdoses, and the creation of hotspot maps to inform outbreak detection and response.Practice Implications EMS data can be an effective tool for monitoring overdoses in real time and informing public health practice. To accurately identify opioid overdose–related EMS runs, the use of a comprehensive case definition is essential.

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.

Objectives We assessed the differences between the first version of the Centers for Disease Control and Prevention (CDC) opioid surveillance definition for suspected nonfatal opioid overdoses (hereinafter, CDC definition) and the North Carolina Disease Event Tracking and Epidemiologic Collection Tool (NC DETECT) surveillance definition to determine whether the North Carolina definition should include additional International Classification of Diseases, Tenth Revision, Clinical Modification(ICD-10-CM) codes and/or chief complaint keywords.Methods Two independent reviewers retrospectively reviewed data on North Carolina emergency department (ED) visits generated by components of the CDC definition not included in the NC DETECT definition from January 1 through July 31, 2018. Clinical reviewers identified false positives as any ED visit in which available evidence supported an alternative explanation for patient presentation deemed more likely than an opioid overdose. After individual assessment, reviewers reconciled disagreements.Results We identified 2296 ED visits under the CDC definition that were not identified under the NC DETECT definition during the study period. False-positive rates ranged from 2.6% to 41.4% for codes and keywords uniquely identifying ≥10 ED visits. Based on uniquely identifying ≥10 ED visits and a false-positive rate ≤10.0%, 4 of 16 ICD-10-CM codes evaluated were identified for NC DETECT definition inclusion. Only 2 of 25 keywords evaluated, “OD” and “overdose,” met inclusion criteria to be considered a meaningful addition to the NC DETECT definition.Practice Implications Quantitative and qualitative trends in coding and keyword use identified in this analysis may prove helpful for future evaluations of surveillance definitions.

In 2019, Connecticut launched an opioid overdose–monitoring program to provide rapid intervention and limit opioid overdose–related harms. The Connecticut Statewide Opioid Response Directive (SWORD)—a collaboration among the Connecticut State Department of Public Health, Connecticut Poison Control Center (CPCC), emergency medical services (EMS), New England High Intensity Drug Trafficking Area (HIDTA), and local harm reduction groups—required EMS providers to call in all suspected opioid overdoses to the CPCC. A centralized data collection system and the HIDTA overdose mapping tool were used to identify outbreaks and direct interventions. We describe the successful identification of a cluster of fentanyl-contaminated crack cocaine overdoses leading to a rapid public health response. On June 1, 2019, paramedics called in to the CPCC 2 people with suspected opioid overdose who reported exclusive use of crack cocaine after being resuscitated with naloxone. When CPCC specialists in poison information followed up on the patients’ status with the emergency department, they learned of 2 similar cases, raising suspicion that a batch of crack cocaine was mixed with an opioid, possibly fentanyl. The overdose mapping tool pinpointed the overdose nexus to a neighborhood in Hartford, Connecticut; the CPCC supervisor alerted the Connecticut State Department of Public Health, which in turn notified local health departments, public safety officials, and harm reduction groups. Harm reduction groups distributed fentanyl test strips and naloxone to crack cocaine users and warned them of the dangers of using alone. The outbreak lasted 5 days and tallied at least 22 overdoses, including 6 deaths. SWORD’s near–real-time EMS reporting combined with the overdose mapping tool enabled rapid recognition of this overdose cluster, and the public health response likely prevented additional overdoses and loss of life.

The Rhode Island Department of Health (RIDOH) uses emergency department data to monitor nonfatal opioid overdoses in Rhode Island. In April 2019, RIDOH detected an increase in nonfatal opioid overdoses in Woonsocket, Rhode Island, and sent an alert to state and local partners (eg, fire departments, emergency departments, faith leaders) with guidance on how to respond. To guide community-level, strategic response efforts, RIDOH analyzed surveillance data to identify overdose patterns, populations, and geographic areas most affected. During April–June 2019, nonfatal opioid overdoses in Woonsocket increased 463% (from 13 to 73) when compared with the previous 3 months. Because of the sustained increase in nonfatal opioid overdoses, RIDOH brought together community partners at a meeting in June 2019 to discuss RIDOH opioid overdose data and coordinate next steps. Data analyses were essential to framing the discussion and allowed community partners at the event to identify an unexpected increase in cocaine-involved nonfatal opioid overdoses in Woonsocket. Many patients with cocaine-involved nonfatal overdoses also had fentanyl in their system, and input from community partners suggested that many patients were unaware of using fentanyl. Community response actions included targeting harm reduction services (eg, distribution of naloxone, mobile needle exchange); deploying peer recovery support specialists to overdose hotspots to connect people to treatment and recovery resources; placing harm reduction messaging in high-traffic areas; and targeted social media messaging. After the meeting, nonfatal opioid overdoses returned to pre-outbreak levels. This case study provides an example of how timely opioid overdose data can be effectively used to detect a spike in nonfatal opioid overdoses and inform a strategic, community-level response.