EMS naloxone administration as non-fatal opioid overdose surveillance: 6-year outcomes in Marion County, Indiana

Antecedents of fatal overdose in an adult cohort identified through administrative record linkage in Indiana, 2015-2022

BACKGROUND

The United States continues to experience unprecedented rates of overdose mortality and need to identify effective policies or practices that can be implemented. This study aims to measure the prevalence, frequency, timing, and rate of touchpoints that occurred prior to a fatal overdose where communities might intervene.

METHODS

In collaboration with Indiana state government, we conducted record-linkage of statewide administrative datasets to vital records (January 1, 2015, through August 26, 2022) to identify touchpoints (jail booking, prison release, prescription medication dispensation, emergency department visits, and emergency medical services). We examined touchpoints within 12-months prior to a fatal overdose among an adult cohort and explored variation over time and by demographic characteristics.

RESULTS

Over the 92-month study period there were 13,882 overdose deaths (89.3% accidental poisonings, X40-X44) in our adult cohort that were record-linked to multiple administrative datasets and revealed nearly two-thirds (64.7%; n=8980) experienced an emergency department visit, the most prevalent touchpoint followed by prescription medication dispensation, emergency medical services responses, jail booking, and prison release. However, with approximately 1 out of every 100 returning citizens dying from drug overdose within 12-months of release, prison release had the highest touchpoint rate followed by emergency medical services responses, jail booking, emergency department visits, and prescription medication dispensation.

CONCLUSION

Record-linking administrative data from routine practice to vital records from overdose mortality is a viable means of identifying where resources should be situated to reduce fatal overdose, with potential to evaluate the effectiveness of overdose prevention efforts.

Deep Neural Networks for Fine-Grained Surveillance of Overdose Mortality

Surveillance of drug overdose deaths relies on death certificates for identification of the substances that caused death. Drugs and drug classes can be identified through the International Classification of Diseases, Tenth Revision (ICD-10), codes present on death certificates. However, ICD-10 codes do not always provide high levels of specificity in drug identification. To achieve more fine-grained identification of substances on death certificate, the free-text cause-of-death section, completed by the medical certifier, must be analyzed. Current methods for analyzing free-text death certificates rely solely on lookup tables for identifying specific substances, which must be frequently updated and maintained. To improve identification of drugs on death certificates, a deep-learning named-entity recognition model was developed, utilizing data from the Kentucky Drug Overdose Fatality Surveillance System (2014-2019), which achieved an F1-score of 99.13%. This model can identify new drug misspellings and novel substances that are not present on current surveillance lookup tables, enhancing the surveillance of drug overdose deaths.

Identification of Non-Fatal Opioid Overdose Cases Using 9-1-1 Computer Assisted Dispatch and Prehospital Patient Clinical Record Variables

Background: The current epidemic of opioid overdoses in the United States necessitates a robust public health and clinical response. We described patterns of non-fatal opioid overdoses (NFOODs) in a small western region using data from the 9-1-1 Computer Assisted Dispatch (CAD) record and electronic Patient Clinical Records (ePCR) completed by EMS responders. We determined whether CAD and ePCR variables could identify NFOOD cases in 9-1-1 data for intervention and surveillance efforts. Methods: We conducted a retrospective analysis of 1 year of 9-1-1 emergency medical CAD and ePCR (including naloxone administration) data from the sole EMS provider in the response area. Cases were identified based on clinician review of the ePCR, and categorized as definitive NFOOD, probable NFOOD, or non-OOD. Sensitivity, specificity, positive and negative predictive values (PPV and NPV) of the most prevalent CAD and ePCR variables were calculated. We used a machine learning technique-Random-Forests (RF) modeling-to optimize our ability to accurately predict NFOOD cases within census blocks. Results: Of 37,960 9-1-1 calls, clinical review identified 158 NFOOD cases (0.4%), of which 123 (77.8%) were definitive and 35 (22.2%) were probable cases. Overall, 106 (67.1%) received naloxone from the EMS responder at the scene. As a predictor of NFOOD, naloxone administration by paramedics had 67.1% sensitivity, 99.6% specificity, 44% PPV, and 99.9% NPV. Using CAD variables alone achieved a sensitivity of 36.7% and specificity of 99.7%. Combining ePCR variables with CAD variables increased the diagnostic accuracy with the best RF model yielding 75.9% sensitivity, 99.9% specificity, 71.4% PPV, and 99.9% NPV. Conclusion: CAD problem type variables and naloxone administration, used alone or in combination, had sub-optimal predictive accuracy. However, a Random Forests modeling approach improved accuracy of identification, which could foster improved surveillance and intervention efforts. We identified the set of NFOODs that EMS encountered in a year and may be useful for future surveillance efforts.

Dual public health crises: the overlap of drug overdose and firearm injury in Indianapolis, Indiana, 2018-2020

Background

Drug overdose and firearm injury are two of the United States (US) most unrelenting public health crises, both of which have been compounded by the COVID-19 pandemic. Programs and policies typically focus on each epidemic, alone, which may produce less efficient interventions if overlap does exist. The objective is to examine whether drug overdose correlates with and is associated with firearm injury at the census tract level while controlling for neighborhood characteristics.

Methods

An ecological study of census tracts in Indianapolis, Indiana from 2018 to 2020. Population rates per 100,000 and census tracts with the highest overlap of overdose and firearm injury were identified based on spatial clusters. Bivariate association between census tract characteristic and drug overdose and firearm violence rate within spatial clusters. Zero-inflated negative binominal regression was used to estimate if the drug overdose activity is associated with higher future firearm injury.

Results

In high overdose—high firearm injury census tracts, rates of firearm injury and drug overdose are two times higher compared to city wide rates. Indicators of structural disadvantage and structural racism are higher in high overdose—high firearm injury census tracts compared to city-wide averages. Drug overdoses are associated with higher rates of firearm injury in the following year (IRR: 1.004, 95% CI 1.001, 1.007, p < 0.05), adjusting for census tract characteristics and spatial dependence.

Conclusions

Drug overdose and firearm injury co-spatially concentrate within census tracts. Moreover, drug overdoses are associated with future firearm injury. Interventions to reduce firearm injuries and drug overdoses should be a co-response in high drug overdose—high firearm injury communities.

Ineffectiveness of paramedic naloxone administration as a standalone metric for community opioid overdoses and the increasing use of naloxone by community members

Introduction:With Canada's growing opioid crisis, many communities are attempting to monitor cases in real-time. Paramedic Naloxone Administration (PNA) has become a common metric for monitoring overdoses. We evaluate whether the use of naloxone administration counts represents an effective monitoring tool for community opioid overdoses.Methods:The electronic ambulance call report database of Peterborough Paramedics (Ontario, Canada) was examined. De-identified records from 2016-2019 with problem codes of "Opioid Overdose", along with all patients documented as receiving naloxone were extracted. Chi-square and Bonferroni-adjusted post hoc proportion tests were used for comparison of counts.Results:558 opioid overdoses were identified, 124 (22%) of which had PNA documented, 181(32%) had naloxone prior to arrival documented and 264 (47%) received no naloxone. Over the three years, the annual number of overdose cases increased, while the proportion of patients receiving PNA decreased significantly each year. PNA was also associated with calls in a residence. Naloxone was administered by a non-paramedic in 262 cases, with 181 of these identified as opioid overdoses and was more common in later years and in cases occurring in public places.Conclusion:PNA calls did not account for a significant percentage of opioid overdoses attended to by paramedics. The strong association between PNA and call location being a residence, along with increasing use of community naloxone kits, may cause certain populations to be under-represent if PNA is used as a standalone metric. The decreasing association with time may also lead to a falsely improving metric further reducing its effectiveness. Thus, PNA when used alone may no longer be a suitable metric for opioid overdose tracking.

Characterizing Opioid Overdoses Using Emergency Medical Services Data : A Case Definition Algorithm Enhanced by Machine Learning

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.

Opioid-related incident severity and emergency medical service naloxone administration by sex in Massachusetts, 2013-2019

BACKGROUND

A Cross-sectional study of all emergency ambulance runs reported by licensed Emergency Medical Services (EMS) providers between 2013 and 2019 was undertaken to determine if the sex of a patient experiencing opioid-related symptoms had an impact on their odds of receiving naloxone from EMS. Methods: All runs within Massachusetts for individuals 11 years and older with a reported sex between 2013 and 2019 (n = 5,533,704 runs) were included. Covariates modeled were patient age, year of the incident, and county of the incident. Runs were separated into those that were opioid-related versus not; opioid-related runs were further subdivided into five severity categories including dead on arrival, acute opioid overdose, opioid intoxicated, opioid withdrawal, and other opioid-related incident. Results: Among opioid-related runs, women had 24% lower odds (95% CI 0.68-0.86) of appearing in the dead on arrival category and 20% lower odds (95% CI 0.78-0.82) of appearing in the acute opioid overdose category than men. Among acute opioid overdoses, runs where patient symptoms met Massachusetts EMS guidelines for naloxone administration, women had 18% lower odds (95% CI 0.76-0.89) of receiving naloxone than men. Conclusions: Sex-related differences persist in the odds of naloxone administration by EMS providers when controlling for symptom presentation.

Retention in Treatment after Emergency Department-Initiated Buprenorphine

BACKGROUND

Emergency department-initiated buprenorphine (EDIB) has been shown to be effective in connecting patients with opioid use disorder (OUD) to outpatient treatment. Five diverse emergency departments (EDs) have successfully implemented EDIB programs.

OBJECTIVES

1) To measure attendance at the first referral appointment and 30-day retention in treatment rates for patients receiving EDIB; 2) To describe demographic and opioid use characteristics of patients receiving EDIB; and 3) To determine average length of time in treatment after EDIB at the five participating EDs.

METHODS

All patients receiving EDIB at the participating EDs (n = 522) were seen by a peer recovery specialist in the ED and demographic and opioid use characteristics were recorded. Patients were followed prospectively. The referral site was contacted and information regarding attendance at the first referral appointment and 30-day retention in treatment was obtained. All patients still in treatment at 30 days were continually followed at subsequent 30-day intervals until the referral site indicated the patient had ended treatment at their facility.

RESULTS

The rate of attendance at the first referral appointment was 77.0% for patients receiving EDIB. At 30-day follow-up, 43.1% of patients were retained in treatment. The mean age of patient enrollment was 36.7 years, 58% of enrollees were male, 90.5% were white, and 73.4% had no medical insurance. Seventy-seven percent reported no substance use other than opioids. The mean time in treatment was 158 days.

CONCLUSIONS

EDIB programs across diverse ED settings are effective at promoting attendance at the first referral appointment for OUD treatment; however, additional work is warranted to increase 30-day treatment retention rates, particularly among patients with nonprescription-only use profiles.

Rural Emergency Medical Service Providers Perceptions on the Causes of and Solutions to the Opioid Crisis: A Qualitative Assessment

Introduction:

The continuing opioid crisis poses unique challenges to remote and often under-resourced rural communities. Emergency medical service (EMS) providers serve a critical role in responding to opioid overdose for individuals living in rural or remote areas who experience opioid overdoses. They are often first at the scene of an overdose and are sometimes the only health care provider in contact with an overdose patient who either did not survive or refused additional care. As such, EMS providers have valuable perspectives to share on the causes and consequences of the opioid crisis in rural communities.

Methods:

EMS providers attending a statewide EMS conference serving those from greater Minnesota and surrounding states were invited to take a 2-question survey asking them to reflect upon what they believed to be the causes of the opioid crisis and what they saw as the solutions to the opioid crisis. Results were coded and categorized using a Consensual Qualitative Research approach.

Results:

EMS providers’ perceptions on causes of the opioid crisis were categorized into 5 main domains: overprescribing, ease of access, socioeconomic vulnerability, mental health concerns, and lack of resources and education. Responses focused on solutions to address the opioid crisis were categorized into 5 main domains: need for increased education, enhanced opioid oversight, increased access to treatment programs, alternative therapies for pain management, and addressing socioeconomic vulnerabilities.

Conclusion:

Along with the recognition that the opioid crisis was at least partially caused by overprescribing, rural EMS providers who participated in this study recognized the critical role of social determinants of health in perpetuating opioid-related harm. Participants in this study reported that education and increased access to treatment facilities and appropriate pain management, along with recognition of the role of social determinants of health in opioid dependency, were necessary steps to address the opioid crisis.

A modified two-process Knox test for investigating the relationship between law enforcement opioid seizures and overdoses

Recent research has shown an association between monthly law enforcement drug seizure events and accidental drug overdose deaths using cross-sectional data in a single state, whereby increased seizures correlated with more deaths. In this study, we conduct statistical analysis of street-level data on law enforcement drug seizures, along with street-level data on fatal and non-fatal overdose events, to determine possible micro-level causal associations between opioid-related drug seizures and overdoses. For this purpose, we introduce a novel, modified two-process Knox test that controls for self-excitation to measure clustering of overdoses nearby in space and time following law enforcement seizures. We observe a small, but statistically significant ( p  < 0.001), effect of 17.7 excess non-fatal overdoses per 1000 law enforcement seizures within three weeks and 250 m of a seizure. We discuss the potential causal mechanism for this association along with policy implications.

Conceptualizing overdose trauma: The relationships between experiencing and witnessing overdoses with PTSD symptoms among street-recruited female sex workers in Baltimore, Maryland

BACKGROUND

The opioid crisis has rendered witnessing and experiencing overdoses a common occurrence, especially among marginalized and drug using populations, including female sex workers (FSW). Such exposures may confer psychological trauma that has gone unrecognized. We explored relationships between experiencing and witnessing overdoses and PTSD symptomology to understand the traumatic nature of these experiences.

METHODS

Data were from FSW (N = 380) in Baltimore City, Maryland, who reported whether they had witnessed/experienced any overdoses in the past 6 months ("overdose traumas") and PTSD symptoms (PCL-5). We tested for associations between overdose traumas and PTSD diagnoses/symptomology in bivariate logistic regression models and multivariate models, adjusting for sociodemographic, experiences of violence, and drug use characteristics.

RESULTS

In our sample, 35.3% witnessed a fatal overdose, 51.9% witnessed a non-fatal overdose, and 28.3% experienced an overdose in the past 6 months. More than half (52.4%) met criteria for PTSD. Most endorsed symptoms within each PTSD domain: 63.2% for intrusive, 58.4% for avoidance, 66.1% for cognition/mood, and 64.7% for arousal/reactivity symptoms. Experiencing an overdose was associated with meeting PTSD criteria and symptoms in all domains in bivariate models. Witnessing an overdose was associated with PTSD diagnoses and intrusive and arousal/reactivity symptoms in bivariate models. Adjusting for sociodemographic characteristics and drug use, experiencing an overdose was associated with intrusive and cognition/mood symptoms, while neither trauma remained associated with PTSD diagnoses.

CONCLUSIONS

Traumas related to overdose, coined "overdose traumas" appear to be extremely psychologically traumatic, though the relationships vary by type and symptom. Programs should be cognizant of psychological trauma to address the full spectrum of overdose harms. Existing measures of PTSD do not accurately represent the effects of overdose traumas in populations like FSW due to the structural barriers to avoiding locations/situations where overdoses may occur and the overlap between symptoms, drug effects, and adaptive responses to homelessness.

Increases in Naloxone Administrations by Emergency Medical Services Providers During the COVID-19 Pandemic: Retrospective Time Series Study

BACKGROUND

The opioid crisis in the United States may be exacerbated by the COVID-19 pandemic. Increases in opioid use, emergency medical services (EMS) runs for opioid-related overdoses, and opioid overdose deaths have been reported. No study has examined changes in multiple naloxone administrations, an indicator of overdose severity, during the COVID-19 pandemic.

OBJECTIVE

This study examines changes in the occurrence of naloxone administrations and multiple naloxone administrations during EMS runs for opioid-related overdoses during the COVID-19 pandemic in Guilford County, North Carolina (NC).

METHODS

Using a period-over-period approach, we compared the occurrence of opioid-related EMS runs, naloxone administrations, and multiple naloxone administrations during the 29-week period before (September 1, 2019, to March 9, 2020) and after NC's COVID-19 state of emergency declaration (ie, the COVID-19 period of March 10 to September 30, 2020). Furthermore, historical data were used to generate a quasi-control distribution of period-over-period changes to compare the occurrence of each outcome during the COVID-19 period to each 29-week period back to January 1, 2014.

RESULTS

All outcomes increased during the COVID-19 period. Compared to the previous 29 weeks, the COVID-19 period experienced increases in the weekly mean number of opioid-related EMS runs (25.6, SD 5.6 vs 18.6, SD 6.6; P<.001), naloxone administrations (22.3, SD 6.2 vs 14.1, SD 6.0; P<.001), and multiple naloxone administrations (5.0, SD 1.9 vs 2.7, SD 1.9; P<.001), corresponding to proportional increases of 37.4%, 57.8%, and 84.8%, respectively. Additionally, the increases during the COVID-19 period were greater than 91% of all historical 29-week periods analyzed.

CONCLUSIONS

The occurrence of EMS runs for opioid-related overdoses, naloxone administrations, and multiple naloxone administrations during EMS runs increased during the COVID-19 pandemic in Guilford County, NC. For a host of reasons that need to be explored, the COVID-19 pandemic appears to have exacerbated the opioid crisis.

Buprenorphine Treatment Intake and Critical Encounters following a Nonfatal Opioid Overdose

BACKGROUND

Individuals with prior opioid-related overdose events have an increased risk for opioid-related mortality. Buprenorphine is a partial agonist that has shown to be an effective medication for opioid use disorder (MOUD). Yet, few studies have investigated whether buprenorphine reduces the risk of opioid-related mortality following a nonfatal opioid-related overdose.

METHODS

A retrospective study was conducted on all overdose cases in Indiana between January 1, 2017 and December 31, 2017. Data were linked from multiple administrative sources. Cases were linked to vital records to assess mortality. Bivariate analyses were conducted to assess group differences between survivors and decedents. A series of multiple logistic regression models were used to determine main and interaction effects of opioid-related mortality.

RESULTS

Among the 10,195 nonfatal overdoses, 2.4% (247) resulted in a subsequent fatal overdose. Overdose decedents were on average 36.4 years-old, 66.8% male, 91.1% White, and 83.8% did not receive a buprenorphine dispensation. Incremental increases in the number of buprenorphine dispensations decreased the likelihood of fatal overdose by 94% (95% CI = 0.88-0.98, p = .001). Incremental increases in arrest encounters were found to significantly increase the likelihood of a fatal overdose (AOR = 2.16; 95% CI = 1.13-3.55). Arrest encounters were a significant moderator of the relationship between buprenorphine uptake effectiveness and drug-related mortality.

CONCLUSIONS

Analysis of linked data provided details of risk and protective factors of fatal overdose. Buprenorphine reduced the risk of death; however, criminal justice involvement remains an area of attention for diversion and overdose death prevention interventions.

Comparing mortality and healthcare utilization in the year following a paramedic-attended non-fatal overdose among people who were and were not transported to hospital: A prospective cohort study using linked administrative health data

BACKGROUND

As the overdose emergency continues in British Columbia (BC), paramedic-attended overdoses are increasing, as is the proportion of people not transported to hospital following an overdose. This study investigated risk of death and subsequent healthcare utilization for people who were and were not transported to hospital after a paramedic-attended non-fatal overdose.

METHODS

Using a linked administrative health data set which includes all overdoses that come into contact with health services in BC, we conducted a prospective cohort study of people who experienced a paramedic-attended non-fatal overdose between 2015 and 2016. People were followed for 365 days after the index event. The primary outcomes assessed were all-cause mortality and overdose-related death. Additionally, we examined healthcare utilization after the index event.

RESULTS

In this study, 8659 (84%) people were transported and 1644 (16%) were not transported to hospital at the index overdose event. There were 279 overdose deaths (2.7% of people, 59.4% of deaths) during follow-up. There was no significant difference in risk of overdose-related death, though people not transported had higher odds of a subsequent non-fatal overdose event captured in emergency department and outpatient records within 90 days. People transported to hospital had higher odds of using hospital and outpatient services for any reason within 365 days.

CONCLUSIONS

Transport to hospital after a non-fatal overdose is an opportunity to provide care for underlying and chronic conditions. There is a need to better understand factors that contribute to non-transport, particularly among people aged 20-59 and people without chronic conditions.

Literature review: Substance use screening and co-morbidity in medically hospitalized youth

OBJECTIVES

Pediatric and young adult patients frequently present to medical inpatient (MIP) units for treatment of substance use disorder (SUD). Given the risk of lifelong dependence and related complications in early life substance use (SU), a review of the literature is warranted.

METHODS

We conducted a Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) systematic review of literature published through April, 62,020, which examined incidence, screening, and complications of pediatric and young adult SU in the MIP setting.

RESULTS

8843 articles were screened, and 28 articles were included for final qualitative synthesis. The overall prevalence of SU-related discharge diagnoses ranged from 1.3% to 5% for patients aged 0 to 26 years. When compared to adult patients, nearly double the rate of co-morbid psychopathology was observed. Three studies utilized systematic screening tools, with the remainder relying on biologic screens and admission or discharge diagnoses.

CONCLUSIONS

The results of our review indicate that current screening practices for SU in the MIP clinical setting are subpar and likely result in an underestimation of incidence and morbidity due to limited use of systematic screening tools. Despite this, incidence of SU hospitalizations and related medical and psychiatric complications continue to rise.

Endogenous Opiates and Behavior: 2018

This paper is the forty-first consecutive installment of the annual anthological review of research concerning the endogenous opioid system, summarizing articles published during 2018 that studied the behavioral effects of molecular, pharmacological and genetic manipulation of opioid peptides and receptors as well as effects of opioid/opiate agonists and antagonists. The review is subdivided into the following specific topics: molecular-biochemical effects and neurochemical localization studies of endogenous opioids and their receptors (2), the roles of these opioid peptides and receptors in pain and analgesia in animals (3) and humans (4), opioid-sensitive and opioid-insensitive effects of nonopioid analgesics (5), opioid peptide and receptor involvement in tolerance and dependence (6), stress and social status (7), learning and memory (8), eating and drinking (9), drug abuse and alcohol (10), sexual activity and hormones, pregnancy, development and endocrinology (11), mental illness and mood (12), seizures and neurologic disorders (13), electrical-related activity and neurophysiology (14), general activity and locomotion (15), gastrointestinal, renal and hepatic functions (16), cardiovascular responses (17), respiration and thermoregulation (18), and immunological responses (19).

Individual and county-level variation in outcomes following non-fatal opioid-involved overdose

BACKGROUND

A lack of large-scale, individually linked data often has impeded efforts to disentangle individual-level variability in outcomes from area-level variability in studies of many diseases and conditions. This study investigated individual and county-level variability in outcomes following non-fatal overdose in a state-wide cohort of opioid overdose patients.

METHODS

Participants were 24 031 patients treated by emergency medical services or an emergency department for opioid-involved overdose in Indiana between 2014 and 2017. Outcomes included repeat non-fatal overdose, fatal overdose and death. County-level predictors included sociodemographic, socioeconomic and treatment availability indicators. Individual-level predictors included age, race, sex and repeat non-fatal opioid-involved overdose. Multilevel models examined outcomes following non-fatal overdose as a function of patient and county characteristics.

RESULTS

10.9% (n=2612) of patients had a repeat non-fatal overdose, 2.4% (n=580) died of drug overdose and 9.2% (n=2217) died overall. Patients with a repeat overdose were over three times more likely to die of drug-related causes (OR=3.68, 99.9% CI 2.62 to 5.17, p<0.001). County-level effects were limited primarily to treatment availability indicators. Higher rates of buprenorphine treatment providers were associated with lower rates of mortality (OR=0.82, 95% CI 0.68 to 0.97, p=0.024), but the opposite trend was found for naltrexone treatment providers (OR=1.20, 95% CI 1.03 to 1.39, p=0.021). Cross-level interactions showed higher rates of Black deaths relative to White deaths in counties with high rates of naltrexone providers (OR=1.73, 95% CI 1.09 to 2.73, p=0.019).

CONCLUSION

Although patient-level differences account for most variability in opioid-related outcomes, treatment availability may contribute to county-level differences, necessitating multifaceted approaches for the treatment and prevention of opioid abuse.

Receipt of Addiction Treatment After Opioid Overdose Among Medicaid-Enrolled Adolescents and Young Adults

IMPORTANCE

Nonfatal opioid overdose may be a critical touch point when youths who have never received a diagnosis of opioid use disorder can be engaged in treatment. However, the extent to which youths (adolescents and young adults) receive timely evidence-based treatment following opioid overdose is unknown.

OBJECTIVE

To identify characteristics of youths who experience nonfatal overdose with heroin or other opioids and to assess the percentage of youths receiving timely evidence-based treatment.

DESIGN, SETTING, AND PARTICIPANTS

This retrospective cohort study used the 2009-2015 Truven-IBM Watson Health MarketScan Medicaid claims database from 16 deidentified states representing all US census regions. Data from 4 039 216 Medicaid-enrolled youths aged 13 to 22 years were included and were analyzed from April 20, 2018, to March 21, 2019.

EXPOSURES

Nonfatal incident and recurrent opioid overdoses involving heroin or other opioids.

MAIN OUTCOMES AND MEASURES

Receipt of timely addiction treatment (defined as a claim for behavioral health services, for buprenorphine, methadone, or naltrexone prescription or administration, or for both behavioral health services and pharmacotherapy within 30 days of incident overdose). Sociodemographic and clinical characteristics associated with receipt of timely treatment as well as with incident and recurrent overdoses were also identified.

RESULTS

Among 3791 youths with nonfatal opioid overdose, 2234 (58.9%) were female, and 2491 (65.7%) were non-Hispanic white. The median age was 18 years (interquartile range, 16-20 years). The crude incident opioid overdose rate was 44.1 per 100 000 person-years. Of these 3791 youths, 1001 (26.4%) experienced a heroin overdose; the 2790 (73.6%) remaining youths experienced an overdose involving other opioids. The risk of recurrent overdose among youths with incident heroin involvement was significantly higher than that among youths with other opioid overdose (adjusted hazard ratio, 2.62; 95% CI, 2.14-3.22), and youths with incident heroin overdose experienced recurrent overdose at a crude rate of 20 700 per 100 000 person-years. Of 3606 youths with opioid-related overdose and continuous enrollment for at least 30 days after overdose, 2483 (68.9%) received no addiction treatment within 30 days after incident opioid overdose, whereas only 1056 youths (29.3%) received behavioral health services alone, and 67 youths (1.9%) received pharmacotherapy. Youths with heroin overdose were significantly less likely than youths with other opioid overdose to receive any treatment after their overdose (adjusted odds ratio, 0.64; 95% CI, 0.49-0.83).

CONCLUSIONS AND RELEVANCE

After opioid overdose, less than one-third of youths received timely addiction treatment, and only 1 in 54 youths received recommended evidence-based pharmacotherapy. Interventions are urgently needed to link youths to treatment after overdose, with priority placed on improving access to pharmacotherapy.

Strengths and weaknesses of existing data sources to support research to address the opioids crisis

Better opioid prescribing practices, promoting effective opioid use disorder treatment, improving naloxone access, and enhancing public health surveillance are strategies central to reducing opioid-related morbidity and mortality. Successfully advancing and evaluating these strategies requires leveraging and linking existing secondary data sources. We conducted a scoping study in Fall 2017 at RAND, including a literature search (updated in December 2018) complemented by semi-structured interviews with policymakers and researchers, to identify data sources and linking strategies commonly used in opioid studies, describe data source strengths and limitations, and highlight opportunities to use data to address high-priority public health research questions. We identified 306 articles, published between 2005 and 2018, that conducted secondary analyses of existing data to examine one or more public health strategies. Multiple secondary data sources, available at national, state, and local levels, support such research, with substantial breadth in data availability, data contents, and the data's ability to support multi-level analyses over time. Interviewees identified opportunities to expand existing capabilities through systematic enhancements, including greater support to states for creating and facilitating data use, as well as key data challenges, such as data availability lags and difficulties matching individual-level data over time or across datasets. Multiple secondary data sources exist that can be used to examine the impact of public health approaches to addressing the opioid crisis. Greater data access, improved usability for research purposes, and data element standardization can enhance their value, as can improved data availability timeliness and better data comparability across jurisdictions.

The Detection of Opioid Misuse and Heroin Use From Paramedic Response Documentation: Machine Learning for Improved Surveillance

Background

Timely, precise, and localized surveillance of nonfatal events is needed to improve response and prevention of opioid-related problems in an evolving opioid crisis in the United States. Records of naloxone administration found in prehospital emergency medical services (EMS) data have helped estimate opioid overdose incidence, including nonhospital, field-treated cases. However, as naloxone is often used by EMS personnel in unconsciousness of unknown cause, attributing naloxone administration to opioid misuse and heroin use (OM) may misclassify events. Better methods are needed to identify OM.

Objective

This study aimed to develop and test a natural language processing method that would improve identification of potential OM from paramedic documentation.

Methods

First, we searched Denver Health paramedic trip reports from August 2017 to April 2018 for keywords naloxone, heroin, and both combined, and we reviewed narratives of identified reports to determine whether they constituted true cases of OM. Then, we used this human classification as reference standard and trained 4 machine learning models (random forest, k-nearest neighbors, support vector machines, and L1-regularized logistic regression). We selected the algorithm that produced the highest area under the receiver operating curve (AUC) for model assessment. Finally, we compared positive predictive value (PPV) of the highest performing machine learning algorithm with PPV of searches of keywords naloxone, heroin, and combination of both in the binary classification of OM in unseen September 2018 data.

Results

In total, 54,359 trip reports were filed from August 2017 to April 2018. Approximately 1.09% (594/54,359) indicated naloxone administration. Among trip reports with reviewer agreement regarding OM in the narrative, 57.6% (292/516) were considered to include information revealing OM. Approximately 1.63% (884/54,359) of all trip reports mentioned heroin in the narrative. Among trip reports with reviewer agreement, 95.5% (784/821) were considered to include information revealing OM. Combined results accounted for 2.39% (1298/54,359) of trip reports. Among trip reports with reviewer agreement, 77.79% (907/1166) were considered to include information consistent with OM. The reference standard used to train and test machine learning models included details of 1166 trip reports. L1-regularized logistic regression was the highest performing algorithm (AUC=0.94; 95% CI 0.91-0.97) in identifying OM. Tested on 5983 unseen reports from September 2018, the keyword naloxone inaccurately identified and underestimated probable OM trip report cases (63 cases; PPV=0.68). The keyword heroin yielded more cases with improved performance (129 cases; PPV=0.99). Combined keyword and L1-regularized logistic regression classifier further improved performance (146 cases; PPV=0.99).

Conclusions

A machine learning application enhanced the effectiveness of finding OM among documented paramedic field responses. This approach to refining OM surveillance may lead to improved first-responder and public health responses toward prevention of overdoses and other opioid-related problems in US communities.

Comparing the predictive capability of self-report and medically-verified non-fatal overdose in adults released from prison: A prospective data linkage study

BACKGROUND

Self-reported non-fatal overdose (NFOD) is a predictor of future overdose and is often used to target overdose prevention for people released from prison. However, the level of agreement between self-reported and medically-verified NFOD history remains unknown. This study aimed to determine the agreement between, and predictive value of, self-reported and medically-verified history of NFOD in people recently released from prison.

METHODS

Pre-release baseline survey data from 1307 adults in prison surveyed from 2008 to 2010 in Queensland, Australia were linked to ambulance, emergency department, and hospital records. We compared the agreement of self-reported NFOD history in the baseline survey and medically-verified NFOD ascertained through linked medical data. Unadjusted and adjusted regression models were used to determine the association between self-reported and medically verified NFOD history and medically-verified NFOD after release from prison.

RESULTS

224 (19 %) participants self-reported NFOD history only, 75 (5 %) had medically-verified NFOD history only, and 56 (4 %) both self-reported and had medically-verified NFOD history. Compared to those with no NFOD history, those who self-reported and had a medical history of NFOD (adjusted hazard ratio (AHR) 6.1, 95 %CI 3.1-11.9), those with a medical history only (AHR 3.4, 95 %CI 1.7-7.0), and those who self-reported only (AHR 1.8, 95 %CI 1.0-3.5) were at increased risk of medically-verified NFOD after release from prison.

CONCLUSIONS

Relying on self-report of NFOD is likely to miss people at increased risk of future NFOD, many of whom could be identified through medical records. Wherever possible, data related to NFOD should be triangulated from multiple sources.

Who receives naloxone from emergency medical services? Characteristics of calls and recent trends

Background: With the rapid rise in opioid overdose-related deaths, state policy makers have expanded policies to increase the use of naloxone by emergency medical services (EMS). However, little is known about changes in EMS naloxone administration in the context of continued worsening of the opioid crisis and efforts to increase use of naloxone. This study examines trends in patient demographics and EMS response characteristics over time and by county urbanicity. Methods: We used data from the 2013-2016 National EMS Information System to examine trends in patient demographics and EMS response characteristics for 911-initiated incidents that resulted in EMS naloxone administration. We also assessed temporal, regional, and urban-rural variation in per capita rates of EMS naloxone administrations compared with per capita rates of opioid-related overdose deaths. Results: From 2013 to 2016, naloxone administrations increasingly involved young adults and occurred in public settings. Particularly in urban counties, there were modest but significant increases in the percentage of individuals who refused subsequent treatment, were treated and released, and received multiple administrations of naloxone before and after arrival of EMS personnel. Over the 4-year period, EMS naloxone administrations per capita increased at a faster rate than opioid-related overdose deaths across urban, suburban, and rural counties. Although national rates of naloxone administration were consistently higher in suburban counties, these trends varied across U.S. Census Regions, with the highest rates of suburban administration occurring in the South. Conclusions: Naloxone administration rates increased more quickly than opioid deaths across all levels of county urbanicity, but increases in the percentage of individuals requiring multiple doses and refusing subsequent care require further attention.

Identifying high-risk areas for nonfatal opioid overdose: a spatial case-control study using EMS run data

PURPOSE

The objective of our study was to incorporate stricter probable nonfatal opioid overdose case criteria, and advanced epidemiologic approaches to more reliably detect local clustering in nonfatal opioid overdose activity in EMS runs data.

METHODS

Data were obtained using emsCharts for our study area in southwestern Pennsylvania from 2007 to 2018. Cases were identified as emergency medical service (EMS) responses where naloxone was administered, and improvement was noted in patient records between initial and final Glasgow Coma Score. A subsample of all-cause EMS responses sites were used as controls and exact matched to cases on sex and 10-year-age category. Clustering was assessed using difference in Ripley's K function for cases and controls and Kulldorff scan statistics.

RESULTS

Difference in K functions indicated no significant difference in probable nonfatal overdose EMS runs across the study area compared to all-cause EMS runs. However, scan statistics did identify significant local clustering of probable nonfatal overdose EMS runs (maximum likelihood = 16.40, P = 0.0003).

CONCLUSIONS

Results highlight relevance of EMS data to detect community-level overdose activity and promote reliable use through stricter case definition criteria and advanced methodological approaches. Techniques examined have the potential to improve targeted delivery of neighborhood-level public health response activities using a near real-time data source.