Impact of the COVID-19 pandemic on opioid overdose and other adverse events in the USA and Canada: a systematic review.

IMPORTANCE: The COVID-19 pandemic impacted healthcare beyond COVID-19 infections. A better understanding of how COVID-19 worsened the opioid crisis has potential to inform future response efforts. OBJECTIVE: To summarize changes from the COVID-19 pandemic on outcomes regarding opioid use and misuse in the USA and Canada. EVIDENCE REVIEW: We searched MEDLINE via PubMed, EMBASE, and CENTRAL for peer-reviewed articles published between March 2020 and December 2021 that examined outcomes relevant to patients with opioid use, misuse, and opioid use disorder by comparing the period before vs after COVID-19 onset in the USA and Canada. Two reviewers independently screened studies, extracted data, assessed methodological quality and bias via Newcastle-Ottawa Scale, and synthesized results. FINDINGS: Among 20 included studies, 13 (65%) analyzed service utilization, 6 (30%) analyzed urine drug testing results, and 2 (10%) analyzed naloxone dispensation. Opioid-related emergency medicine utilization increased in most studies (85%, 11/13) for both service calls (17% to 61%) and emergency department visits (42% to 122%). Urine drug testing positivity results increased in all studies (100%, 6/6) for fentanyl (34% to 138%), most (80%, 4/5) studies for heroin (-12% to 62%), and most (75%, 3/4) studies for oxycodone (0% to 44%). Naloxone dispensation was unchanged and decreased in one study each. INTERPRETATION: Significant increases in surrogate measures of the opioid crisis coincided with the onset of COVID-19. These findings serve as a call to action to redouble prevention, treatment, and harm reduction efforts for the opioid crisis as the pandemic evolves. PROSPERO REGISTRATION NUMBER: CRD42021236464.

Linking Emergency Medical Services and Emergency Department Data to Improve Overdose Surveillance in North Carolina.

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 Modification diagnosis 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.

Improvements in Toxicology Testing to Identify Fentanyl Analogs and Other Novel Synthetic Opioids in Fatal Drug Overdoses, Connecticut, January 2016-June 2019.

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.

Using Surveillance With Near-Real-Time Alerts During a Cluster of Overdoses From Fentanyl-Contaminated Crack Cocaine, Connecticut, June 2019.

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.

Linking Ambulance Trip and Emergency Department Surveillance Data on Opioid-Related Overdose, Massachusetts, 2017.

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.

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.

Using Emergency Medical Services Data to Monitor Nonfatal Opioid Overdoses in Real Time : Development, Validation, and Use of a Case Definition, Rhode Island, 2018.

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.

A Mixed-Methods Comparison of a National and State Opioid Overdose Surveillance Definition.

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.

Willingness to use a wearable device capable of detecting and reversing overdose among people who use opioids in Philadelphia.

BACKGROUND: The incidence of opioid-related overdose deaths has been rising for 30 years and has been further exacerbated amidst the COVID-19 pandemic. Naloxone can reverse opioid overdose, lower death rates, and enable a transition to medication for opioid use disorder. Though current formulations for community use of naloxone have been shown to be safe and effective public health interventions, they rely on bystander presence. We sought to understand the preferences and minimum necessary conditions for wearing a device capable of sensing and reversing opioid overdose among people who regularly use opioids. METHODS: We conducted a combined cross-sectional survey and semi-structured interview at a respite center, shelter, and syringe exchange drop-in program in Philadelphia, Pennsylvania, USA, during the COVID-19 pandemic in August and September 2020. The primary aim was to explore the proportion of participants who would use a wearable device to detect and reverse overdose. Preferences regarding designs and functionalities were collected via a questionnaire with items having Likert-based response options and a semi-structured interview intended to elicit feedback on prototype designs. Independent variables included demographics, opioid use habits, and previous experience with overdose. RESULTS: A total of 97 adults with an opioid use history of at least 3 months were interviewed. A majority of survey participants (76%) reported a willingness to use a device capable of detecting an overdose and automatically administering a reversal agent upon initial survey. When reflecting on the prototype, most respondents (75.5%) reported that they would wear the device always or most of the time. Respondents indicated discreetness and comfort as important factors that increased their chance of uptake. Respondents suggested that people experiencing homelessness and those with low tolerance for opioids would be in greatest need of the device. CONCLUSIONS: The majority of people sampled with a history of opioid use in an urban setting were interested in having access to a device capable of detecting and reversing an opioid overdose. Participants emphasized privacy and comfort as the most important factors influencing their willingness to use such a device. TRIAL REGISTRATION: NCT04530591.

Predictors of enrollment in opioid agonist therapy after opioid overdose or diagnosis with opioid use disorder: A cohort study.

BACKGROUND: Medicaid recipients have a high burden of opioid overdose and opioid use disorder (OUD). Opioid agonist therapies are an effective treatment for OUD, but there is a wide and persisting gap between those who are indicated and those who receive treatment. The objective of this study was to identify the predictors of enrollment in opioid agonist therapy within 6 months of an opioid overdose or OUD diagnosis in a cohort of Medicaid recipients. METHODS: Using multiple linked, state-level databases, we conducted a retrospective cohort study of 17,449 Medicaid recipients in Rhode Island who had an opioid overdose or an OUD diagnosis between July 2013 and June 2018. RESULTS: The majority (58 %) of Medicaid recipients did not enroll in opioid agonist therapy within 6 months. In adjusted models, having one or more prior overdose (adjusted risk ratio [ARR] = 0.33, 95 % CI: 0.28, 0.38), alcohol use disorder (ARR = 0.56, 95 % CI: 0.52, 0.60), or back problems (ARR = 0.58, 95 % CI: 0.55, 0.61) were strong predictors of non-enrollment. Conversely, emergency department (ARR = 1.31, 95 % CI: 1.28-1.34) and primary care provider (ARR = 1.03, 95 % CI: 1.01-1.34) visit frequency above the 75th percentile were associated with timely enrollment in opioid agonist therapy. CONCLUSIONS: Our findings underscore the need to enhance pathways to treatment for OUD through varied nodes of engagement with healthcare systems. Interventions to improve screening for OUD and referrals to opioid agonist therapies should include high-impact settings, such as treatment programs for alcohol and substance use disorders, pain clinics, and outpatient behavioral care settings.

Incidence and Characteristics of Nonfatal Opioid Overdose Among Youths Aged 11 to 24 Years by Sex.

Importance: Opioid-related overdose has substantially increased among adolescents and young adults in recent years. How overdose differs by age and sex among youths and the factors associated with overdose by sex remain poorly described. Objective: To compare the sociodemographic and clinical characteristics of female and male youths who have experienced a nonfatal opioid overdose (NFOD) and compare the incidence of NFOD by sex. Design, Setting, and Participants: This retrospective cohort study used data on US individuals aged 11 to 24 years with a diagnosis of NFOD from the IBM MarketScan Commercial Database from January 1, 2006, through December 31, 2017. Exposure: Sex. Main Outcomes and Measures: The primary outcome was NFOD stratified by sex; covariates included sociodemographic and clinical characteristics. Results: Among 20 312 youths aged 11 to 24 years who had a history of NFOD and met study eligibility criteria, the median age was 20 years (interquartile range, 18-22 years; mean [SD] age, 20.0 [2.9] years) and 56.7% were male. Compared with male youths, female youths had a higher baseline prevalence of mood or anxiety disorder (65.5% vs 51.9%, P < .001), trauma and stress-related disorders (16.4% vs 10.1%, P < .001), and history of suicide attempt or self-harm (14.6% vs 9.9%, P < .001). Male youths had a higher prevalence of opioid use disorder (44.7% vs 29.2%, P < .001), cannabis use disorder (18.3% vs 11.3%, P < .001), and alcohol use disorder (20.3% vs 14.4%, P < .001). The incidence rate ratio of NFODs in females vs males was greater than 1 for ages 11 to 16 years and was less than or equal to 1 after age 17 years. Conclusions and Relevance: This cohort study found differences between female and male youths in sociodemographic and clinical characteristics and incidence of NFOD. Although female and male youths who experience overdose appear to have different risk factors, many of these risk factors may be amenable to early detection through screening and intervention.

Addressing opioid overdose deaths: The vision for the HEALing communities study.

The United States is facing two devastating public health crises- the opioid epidemic and the COVID-19 pandemic. Within this context, one of the most ambitious implementation studies in addiction research is moving forward. Launched in May 2019, the HEALing Communities Study (HCS) was developed by the National Institutes of Health (NIH) and the Substance Abuse and Mental Health Services Administration (SAMHSA) as part of the Helping to End Addiction Long-termSM Initiative (National Institutes of Health, 2020). The goal for this research was to reduce opioid overdose deaths by 40 % in three years by enhancing and integrating the delivery of multiple evidence-based practices (EBPs) with proven effectiveness in reducing opioid overdose deaths across health care, justice, and community settings. This paper describes the initial vision, goals, and objectives of this initiative; the impact of COVID-19; and the potential for knowledge to be generated from HCS at the intersection of an unrelenting epidemic of opioid misuse and overdoses and the ravishing COVID-19 pandemic.

Opioid-related overdose mortality in the era of fentanyl: Monitoring a shifting epidemic by person, place, and time.

BACKGROUND: With the emergence of illicit fentanyl, fentanyl-involved overdose rates increased from 2013 to 2017 in the United States (US). We describe US trends in opioid-related overdose mortality rates by race, age, urbanicity, and opioid type before and after the emergence of fentanyl. METHODS: Using the Centers for Disease Control and Prevention's WONDER database, we estimated crude and age-standardized opioid-related overdose mortality rates at the intersections of race (non-Hispanic [NH] Black and white), age (<55 and ≥55 years), sex (male and female) and urbanicity (urban and rural residence) from 2005 to 2017. We compare relative changes in mortality from 2013 to 17, and describe changes in the contributions of fentanyl, heroin, and other opioids to opioid-related overdose mortality. RESULTS: From 2013 to 2017, the overall opioid overdose mortality rate was consistently higher in NH white Americans, however, the rate increase was greater among NH Black (174 %) compared to NH white (85 %) Americans. The steepest increases occurred in the overdose rates between 2013 and 2017 among younger (aged <55 years) urban NH Black Americans (178 % increase). Among older (≥55 years) adults, only urban NH Black Americans had an increase in overdose-related mortality rate (87 % increase). Urban NH Black Americans also experienced the greatest increase in the percent of fentanyl-involved deaths (65 % in younger, 61 % in older). CONCLUSIONS: In the era of increased availability of illicitly manufactured fentanyl (2013-2017), there has been a disproportionate increase in opioid-related overdose deaths among urban NH Black Americans. Interventions for urban NH Black Americans are urgently needed to halt the increase in overdose deaths.

Fentanyl analog positivity among near-real-time urine drug test results in patients seeking health care.

Overdose deaths involving synthetic opioids continue to climb. Fentanyl analogs have been identified as important contributors to these overdoses, but little is known about their prevalence in patients seeking health care. This cross-sectional study of urine drug test (UDT) results from July 15, 2019, through March 12, 2020, included patient specimens analyzed using liquid chromatography-tandem mass spectrometry (LC-MS/MS), submitted by health care professionals as part of routine care to detect fentanyl and fentanyl analogs. A convenience sample approach was used to select patient specimens from diverse health care practices across all 50 states, then stratified by fentanyl prescription status. Positivity rates, geographic distribution, and co-occurrence were quantified. The total positivity rate for ten fentanyl analogs was 40.55% in the non-prescribed fentanyl-positive population. The most common fentanyl analogs in this population were 4-ANPP (4-anilino-N-phenethylpiperidine), 30.74%; acetyl fentanyl, 19.40%; and carfentanil, 3.13%. The total positivity rate for four fentanyl analogs was 8.93% in the prescribed fentanyl-positive population, including 4-ANPP, 8.85%; acetyl fentanyl, 0.19%; acryl fentanyl, 0.05%; and 4-FiBF, 0.03%. Counties in Ohio and Kentucky had the highest positivity rates. Acetyl fentanyl and 4-ANPP copositivity occurred in 11.36% of non-prescribed patient specimens. However, acetyl fentanyl and 4-ANPP positivity may not be consistent with fentanyl analog use since both are process impurities, and 4-ANPP is a metabolite of fentanyl. Near-real-time, definitive UDT results reveal fentanyl analogs in patients seeking health care, helping clinicians and public health officials better understand their contribution to overdoses and help mitigate the risks they pose.

Predictive Modeling of Opioid Overdose Using Linked Statewide Medical and Criminal Justice Data.

Importance: Responding to the opioid crisis requires tools to identify individuals at risk of overdose. Given the expansion of illicit opioid deaths, it is essential to consider risk factors across multiple service systems. Objective: To develop a predictive risk model to identify opioid overdose using linked clinical and criminal justice data. Design, Setting, and Participants: A cross-sectional sample was created using 2015 data from 4 Maryland databases: all-payer hospital discharges, the prescription drug monitoring program (PDMP), public-sector specialty behavioral treatment, and criminal justice records for property or drug-associated offenses. Maryland adults aged 18 to 80 years with records in any of 4 databases were included, excluding individuals who died in 2015 or had a non-Maryland zip code. Logistic regression models were estimated separately for risk of fatal and nonfatal opioid overdose in 2016. Model performance was assessed using bootstrapping. Data analysis took place from February 2018 to November 2019. Exposures: Controlled substance prescription fills and hospital, specialty behavioral health, or criminal justice encounters. Main Outcomes and Measures: Fatal opioid overdose defined by the state medical examiner and 1 or more nonfatal overdoses treated in Maryland hospitals during 2016. Results: There were 2 294 707 total individuals in the sample, of whom 42.3% were male (n = 970 019) and 53.0% were younger than 50 years (647 083 [28.2%] aged 18-34 years and 568 160 [24.8%] aged 35-49 years). In 2016, 1204 individuals (0.05%) in the sample experienced fatal opioid overdose and 8430 (0.37%) experienced nonfatal opioid overdose. In adjusted analysis, the factors mostly strongly associated with fatal overdose were male sex (odds ratio [OR], 2.40 [95% CI, 2.08-2.76]), diagnosis of opioid use disorder in a hospital (OR, 2.93 [95% CI, 2.17-3.80]), release from prison in 2015 (OR, 4.23 [95% CI, 2.10-7.11]), and receiving opioid addiction treatment with medication (OR, 2.81 [95% CI, 2.20-3.86]). Similar associations were found for nonfatal overdose. The area under the curve for fatal overdose was 0.82 for a model with hospital variables, 0.86 for a model with both PDMP and hospital variables, and 0.89 for a model that further added behavioral health and criminal justice variables. For nonfatal overdose, the area under the curve using all variables was 0.85. Conclusions and Relevance: In this analysis, fatal and nonfatal opioid overdose could be accurately predicted with linked administrative databases. Hospital encounter data had higher predictive utility than PDMP data. Model performance was meaningfully improved by adding PDMP records. Predictive models using linked databases can be used to target large-scale public health programs.

Development of a Training Program for Law Enforcement K9 Handlers to Administer Naloxone.

As the opioid epidemic continues across the United States, law enforcement K9s (LEK9s) are at increased risk of accidental exposure and overdose. This study evaluated a novel training program teaching handlers to administer naloxone to their LEK9 in the event of an overdose. Seventy-five LEK9 handlers from a governmental agency attended a naloxone training session. A presurvey given to the handlers evaluated their knowledge of opioid overdose in LEK9s and their confidence administering naloxone. Officers were educated via a PowerPoint presentation about naloxone and how to administer it to their LEK9. A postsurvey evaluated changes in their knowledge and confidence as a result of the presentation. Sixty-two presurveys and 47 postsurveys were completed. Nearly all handlers had never given their LEK9 an intramuscular or intranasal injection. Most handlers were not comfortable monitoring their LEK9's vital signs for an opioid overdose. After the training, handlers demonstrated a mild increase in comfort level administering intramuscular and intranasal naloxone (15 and 14% increase, respectively). Comfort level monitoring vital signs and symptoms of an opioid overdose increased 38 and 32%, respectively. Handlers may not be fully prepared to assess and treat their LEK9 and may benefit from a targeted training program teaching them to administer naloxone.

Incidence of Postoperative Opioid Overdose and New Diagnosis of Opioid Use Disorder Among US Veterans.

BACKGROUND AND OBJECTIVES: Perioperative exposure to opioids is associated with adverse outcomes. We aim to determine the associations between surgery and subsequent opioid overdose, an acute event, and a new diagnosis of opioid use disorder (OUD), a chronic relapsing disease, in parallel. METHODS: This retrospective cohort study of US veterans used surgery as exposure and the two outcomes were (1) occurrence of overdose and (2) new diagnosis of OUD in the first postoperative year. Surgical group was matched to the reference controls based on the propensity score of having surgery, and matched logistic regression was used to calculate the odds ratio (OR). RESULTS: A total of 261 208 surgical patients were matched to 479 531 controls. Overdose occurred in 1893 (0.7%) of the surgical patients and in 518 (0.1%) of the matched controls in the first postoperative year (OR, 6.71; 95% confidence interval [CI], 5.80-7.75; P < .001). Among patients with no history of OUD, surgery was also associated with a new diagnosis of OUD in the first postoperative year (OR, 1.13; 95% CI, 1.02-1.24; P = .015). DISCUSSION AND CONCLUSIONS: The postoperative period is strongly associated with opioid overdose, but only weakly associated with new diagnosis of OUD. This is likely due to the difficulty of diagnosing OUD in the postoperative period. SCIENTIFIC SIGNIFICANCE: This is the first study that has examined opioid overdose and new-onset OUD in the postoperative period in parallel. Our analysis suggests different risk factors for each, as well as different strengths of association with surgery. More sensitive diagnostic criteria for postoperative OUD are needed to promptly diagnose and treat this condition. (Am J Addict 2020;00:00-00).