Performance Measures of Diagnostic Codes for Detecting Opioid Overdose in the Emergency Department

Cannabis Legalization and Resource Use for Ingestions by Young Children

OBJECTIVE

In conjunction with widening legalization, there has been a rapid rise in unintentional cannabis ingestions in young children. We sought to determine if the legal status of recreational cannabis was associated with resource use in young children with cannabis poisoning.

METHODS

This retrospective cross-sectional study of the Pediatric Health Information System included emergency department encounters between January 2016 and April 2023 for children <6 years of age with a diagnosis indicating cannabis ingestion. The primary exposure was recreational cannabis legalization status in the state in which the encounter occurred. We used logistic regression models to determine the association of recreational cannabis legality with resource utilization outcomes, adjusting for demographic covariates.

RESULTS

We included 3649 children from 47 hospitals; 29% of encounters occurred in places in which recreational cannabis was legal. Compared with environments in which recreational cannabis was illegal, cannabis-legal locations had lower uses of advanced neuroimaging (24% vs 35%; adjusted odds ratio [aOR], 0.65; 95% confidence interval [CI]: 0.55-0.77), lumbar puncture (1.6% vs 3.8%; aOR, 0.42; 95% CI: 0.24-0.70), ICU admission (7.9% vs 11%; aOR, 0.71; 95% CI: 0.54-0.93), and mechanical ventilation (0.8% vs 2.9%; aOR, 0.30; 95% CI: 0.14-0.58). Urine testing was more common in places in which recreational cannabis was legal (71% vs 58%; aOR, 1.87; 95% CI: 1.59-2.20).

CONCLUSIONS

State-level legalization of recreational cannabis was associated with a significant decrease in the utilization of advanced medical resources in cases of cannabis intoxication in children. These findings suggest the need for a focus on policies and procedures to minimize invasive testing in cases of cannabis intoxication in children.

Performance of International Classification of Disease-10 codes in detecting emergency department patients with opioid misuse

BACKGROUND AND AIMS

Accurate case discovery is critical for disease surveillance, resource allocation and research. International Classification of Disease (ICD) diagnosis codes are commonly used for this purpose. We aimed to determine the sensitivity, specificity and positive predictive value (PPV) of ICD-10 codes for opioid misuse case discovery in the emergency department (ED) setting.

DESIGN AND SETTING

Retrospective cohort study of ED encounters from January 2018 to December 2020 at an urban academic hospital in the United States. A sample of ED encounters enriched for opioid misuse was developed by oversampling ED encounters with positive urine opiate screens or pre-existing opioid-related diagnosis codes in addition to other opioid misuse risk factors.

CASES

A total of 1200 randomly selected encounters were annotated by research staff for the presence of opioid misuse within health record documentation using a 5-point scale for likelihood of opioid misuse and dichotomized into cohorts of opioid misuse and no opioid misuse.

MEASUREMENTS

Using manual annotation as ground truth, the sensitivity and specificity of ICD-10 codes entered during the encounter were determined with PPV adjusted for oversampled data. Metrics were also determined by disposition subgroup: discharged home or admitted.

FINDINGS

There were 541 encounters annotated as opioid misuse and 617 with no opioid misuse. The majority were males (54.4%), average age was 47 years and 68.5% were discharged directly from the ED. The sensitivity of ICD-10 codes was 0.56 (95% confidence interval [CI], 0.51-0.60), specificity 0.99 (95% CI, 0.97-0.99) and adjusted PPV 0.78 (95% CI, 0.65-0.92). The sensitivity was higher for patients discharged from the ED (0.65; 95% CI, 0.60-0.69) than those admitted (0.31; 95% CI, 0.24-0.39).

CONCLUSIONS

International Classification of Disease-10 codes appear to have low sensitivity but high specificity and positive predictive value in detecting opioid misuse among emergency department patients in the United States.

Resource utilization among children presenting with cannabis poisonings in the emergency department

BACKGROUND

Exploratory pediatric cannabis poisonings are increasing. The aim of this study is to provide a national assessment of the frequency and trends of diagnostic testing and procedures in the evaluation of pediatric exploratory cannabis poisonings.

METHODS

This is a retrospective cross-sectional study of the Pediatric Health Information Systems database involving all cases of cannabis poisoning for children age 0-10 years between 1/2016 and 12/2021. Cannabis poisoning trends were assessed using a negative binomial regression model. A new variable named "ancillary testing" was created to isolate testing that would not confirm the diagnosis of cannabis poisoning or be used to exclude co-ingestion of acetaminophen or aspirin. Ancillary testing was assessed with regression analyses, with ancillary testing as the outcomes and year as the predictor, to assess trends over time.

RESULTS

A total of 2001 cannabis exposures among 1999 children were included. Cannabis exposures per 100,000 ED visits increased 68.7% (95% CI, 50.3, 89.3) annually. There was a median of 4 (IQR 2.0, 6.0) diagnostic tests performed per encounter. 64.5% of encounters received blood tests, 28.8% received a CT scan, and 2.4% received a lumbar puncture. Compared to White individuals, Black individuals were more likely to receive ancillary testing (OR 1.52 [95% CI, 1.23, 1.89]). Compared to those 2-6 years, those <2 years were more likely to receive ancillary testing (OR 1.55 [95% CI, 1.19, 2.02). We found no significant annual change in the odds of receiving ancillary testing (OR 1.04 [95% CI, 0.97, 1.12]).

CONCLUSIONS

We found no change in the proportion of encounters associated with ancillary testing, despite increases in exploratory cannabis poisonings over the study period. Given the increasing rate of pediatric cannabis poisonings, emergency providers should consider this diagnosis early in the evaluation of a pediatric patient with acute change in mental status. While earlier use of urine drug screening may reduce ancillary testing and invasive procedures, even a positive urine drug screen does not rule out alternative pathologies and should not replace a thoughtful evaluation.

Association of Prescription Drug Monitoring Programs With Opioid Prescribing and Overdose in Adolescents and Young Adults

STUDY OBJECTIVE

Prescription opioid use is associated with substance-related adverse outcomes among adolescents and young adults through a pathway of prescribing, diversion and misuse, and addiction and overdose. Assessing the effect of current prescription drug monitoring programs (PDMPs) on opioid prescribing and overdoses will further inform strategies to reduce opioid-related harms.

METHODS

We performed interrupted time series analyses to measure the association between state-level implementation of PDMPs with annual opioid prescribing and opioid-related overdoses in adolescents (13 to 18 years) and young adults (19 to 25 years) between 2008 and 2019. We focused on PDMPs that included mandatory reviews by providers. Data were obtained from a commercial insurance company.

RESULTS

Among 9,344,504 adolescents and young adults, 1,405,382 (15.0%) had a dispensed opioid prescription, and 6,262 (0.1%) received treatment for an opioid-related overdose. Mandated PDMP review was associated with a 4.2% (95% CI, 1.9% to 6.4%) reduction in annual opioid dispensations among adolescents and a 7.8% (95% CI, 4.7% to 10.9%) annual reduction among young adults. For opioid-related overdoses, mandated PDMP review was associated with a 16.1% (95% CI, 3.8 to 26.7) and 15.9% (95% CI, 7.6 to 23.4) reduction in annual opioid overdoses for adolescents and young adults, respectively.

CONCLUSION

PDMPs were associated with sustained reductions in opioid prescribing and overdoses in adolescents and young adults. Although these findings support the value of mandated PDMPs as part of ongoing strategies to reduce opioid overdoses, further studies with prospective study designs are needed to characterize the effect of these programs fully.

Trends and correlated outcomes in population-level prescription opioid and transdermal fentanyl use in Israel

BACKGROUND

In the last twenty years, there was a documented increase in prescription opioid procurement in Israel. However, there is still little evidence of the association between opioid procurement rates, health service utilisation in secondary care, and enrollment rates to substance use disorder treatment programmes. In this study, we show trends in the reports of opioid-related hospitalisations, emergency department visits, enrollment to community-based outpatient treatment for Prescription Opioid Use Disorder and opioid-related mortality rates. Additionally, we examine potential correlations between these health service utilisation rates and prescription opioid procurement rates at the population level, with a focus on transdermal fentanyl.

METHODS

A longitudinal study at the population level. We used seven-year data on indicators of opioid-related morbidity, prescription opioid procurement data for 2015-2021, and six-year opioid-related mortality data for 2015-2020. We measure the correlation between procurement rates of prescription opioids in Oral Morphine Equivalent per capita, and aggregated rates obtained from hospital administrative data for hospitalisations, emergency department visits, and patient enrolment in specialised prescription opioid use disorder outpatient treatment in the community setting.

RESULTS

Between 2015 and 2021, procurement rates in primary care per capita for all prescription opioids increased by 85%, while rates of transdermal fentanyl procurement increased by 162%. We found a significant positive correlation at the population level, between annual opioid procurement rates, and rates per population of opioid-related visits to emergency departments (r = 0.96, p value < 0.01, [CI 0.74-0.99]), as well as a positive correlation with the rates per population of patient enrolment in specialised prescription opioid use disorder outpatient treatment (r = 0.93, p value = 0.02, [CI 0.58-0.99]). Opioid-related mortality peaked in 2019 at 0.31 deaths per 100,000 but decreased to 0.20 deaths per 100,000 in 2020.

CONCLUSION

Data shows that all-opioid and transdermal fentanyl procurement has increased yearly between 2015 and 2021. This increase is positively correlated with a growing demand for community-based Prescription Opioid Use Disorder outpatient treatment. Efforts to reduce opioid-related morbidity may require effective approaches toward appropriate prescribing, monitoring, and further increasing access to prescription opioid outpatient treatment.

Study protocol for a multisite randomized controlled trial of a peer navigator intervention for emergency department patients with nonfatal opioid overdose

BACKGROUND

Patients presenting to emergency departments (EDs) after a nonfatal opioid-involved overdose are at high risk for future overdose and death. Responding to this risk, the New York City (NYC) Department of Health and Mental Hygiene operates the Relay initiative, which dispatches trained peer "Wellness Advocates" to meet patients in the ED after a suspected opioid-involved overdose and follow them for up to 90 days to provide support, education, referrals to treatment, and other resources using a harm reduction framework.

METHODS

In this article, we describe the protocol for a multisite randomized controlled trial of Relay. Study participants are recruited from four NYC EDs and are randomized to receive the Relay intervention or site-directed care (the control arm). Outcomes are assessed through survey questionnaires conducted at 1-, 3-, and 6-months after the baseline visit, as well as through administrative health data. The primary outcome is the number of opioid-related adverse events, including any opioid-involved overdose or any other substance use-related ED visit, in the 12 months post-baseline. Secondary and exploratory outcomes will also be analyzed, as well as hypothesized mediators and moderators of Relay program effectiveness.

CONCLUSION

We present the protocol for a multisite randomized controlled trial of a peer-delivered OD prevention intervention in EDs. We describe how the study was designed to minimize disruption to routine ED operations, and how the study was implemented and adapted during the COVID-19 pandemic. This trial is registered with ClinicalTrials.gov [NCT04317053].

Comparative Study of Opioid Initiation With Tramadol, Short-acting Hydrocodone, or Short-acting Oxycodone on Opioid-related Adverse Outcomes Among Chronic Noncancer Pain Patients

OBJECTIVE

To compare the safety profiles of low and high-dose tramadol, short-acting hydrocodone, and short-acting oxycodone therapies among chronic noncancer pain individuals.

MATERIALS AND METHODS

A retrospective cohort study of individuals with back/neck pain/osteoarthritis with an initial opioid prescription for tramadol, hydrocodone, or oxycodone was conducted using IQVIA PharMetrics Plus claims for Academics database (2006 to 2020). Two cohorts were created for separately studying opioid-related adverse events (overdoses, accidents, self-inflicted injuries, and violence-related injuries) and substance use disorders (opioid and nonopioid). Patients were followed from the index date until an outcome event, end of enrollment, or data end. Time-varying exposure groups were constructed and Cox regression models were estimated.

RESULTS

A total of 1,062,167 (tramadol [16.5%], hydrocodone [61.1%], and oxycodone [22.4%]) and 986,809 (tramadol [16.5%], hydrocodone [61.3%], and oxycodone [22.2%]) individuals were in the adverse event and substance use disorder cohorts. All high-dose groups had elevated risk of nearly all outcomes, compared with low-dose hydrocodone. Compared with low-dose hydrocodone, low-dose oxycodone was associated with a higher risk of opioid overdose (hazard ratio: 1.79 [1.37 to 2.33]). No difference in risk was observed between low-dose tramadol and low-dose hydrocodone (hazard ratio: 0.85 [0.64 to 1.13]). Low-dose oxycodone had higher risks of an opioid use disorder, and low-dose tramadol had a lower risk of accidents, self-inflicted injuries, and opioid use disorder compared with low-dose hydrocodone.

DISCUSSION

Low-dose oxycodone had a higher risk of opioid-related adverse outcomes compared with low-dose tramadol and hydrocodone. This should be interpreted in conjunction with the benefits of pain control and functioning associated with oxycodone use in future research.

Medical Marijuana Legalization and Opioid- and Pain-Related Outcomes Among Patients Newly Diagnosed With Cancer Receiving Anticancer Treatment

Importance

The past decade saw rapid declines in opioids dispensed to patients with active cancer, with a concurrent increase in marijuana use among cancer survivors possibly associated with state medical marijuana legalization.

Objective

To assess the associations between medical marijuana legalization and opioid-related and pain-related outcomes for adult patients receiving cancer treatment.

Design, Setting, and Participants

This cross-sectional study used 2012 to 2017 national commercial claims data and a difference-in-differences design to estimate the associations of interest for patients residing in 34 states without medical marijuana legalization by January 1, 2012. Secondary analysis differentiated between medical marijuana legalization with and without legal allowances for retail dispensaries. Data analysis was conducted between December 2021 and August 2022. Study samples included privately insured patients aged 18 to 64 years who received anticancer treatment during the 6 months after a new breast (in women), colorectal, or lung cancer diagnosis.

Exposures

State medical marijuana legalization that took effect between 2012 and 2017.

Main Outcomes and Measures

Having 1 or more days of opioids, 1 or more days of long-acting opioids, total morphine milligram equivalents of any opioid dispensed to patients with 1 or more opioid days, and 1 or more pain-related emergency department visits or hospitalizations (hereafter, hospital events) during the 6 months after a new cancer diagnosis. Interaction terms were included between each policy indicator and an indicator of recent opioids, defined as having 1 or more opioid prescriptions during the 12 months before the new cancer diagnosis. Logistic models were estimated for dichotomous outcomes, and generalized linear models were estimated for morphine milligram equivalents.

Results

The analysis included 38 189 patients newly diagnosed with breast cancer (38 189 women [100%]), 12 816 with colorectal cancer (7100 men [55.4%]), and 7190 with lung cancer (3674 women [51.1%]). Medical marijuana legalization was associated with a reduction in the rate of 1 or more opioid days from 90.1% to 84.4% (difference, 5.6 [95% CI, 2.2-9.0] percentage points; P = .001) among patients with breast cancer with recent opioids, from 89.4% to 84.4% (difference, 4.9 [95% CI, 0.5-9.4] percentage points; P = .03) among patients with colorectal cancer with recent opioids, and from 33.8% to 27.2% (difference, 6.5 [95% CI, 1.2-11.9] percentage points; P = .02) among patients with lung cancer without recent opioids. Medical marijuana legalization was associated with a reduction in the rate of 1 or more pain-related hospital events from 19.3% to 13.0% (difference, 6.3 [95% CI, 0.7-12.0] percentage points; P = .03) among patients with lung cancer with recent opioids.

Conclusions and Relevance

Findings of this cross-sectional study suggest that medical marijuana legalization implemented from 2012 to 2017 was associated with a lower rate of opioid dispensing and pain-related hospital events among some adults receiving treatment for newly diagnosed cancer. The nature of these associations and their implications for patient safety and quality of life need to be further investigated.

Sensitivity of health records for self-reported nonfatal drug and alcohol overdose

BACKGROUND AND OBJECTIVES

Public health surveillance for overdose sometimes depends on nonfatal drug overdoses recorded in health records. However, the proportion of total overdoses identified through health record systems is unclear. Comparison of overdoses from health records to those that are self-reported may provide insight on the proportion of nonfatal overdoses that are not identified.

METHODS

We conducted a cohort study linking survey data on overdose from a national survey of Veterans to United States Department of Veterans Affairs (VA) health records, including community care paid for by VA. Self-reported overdose in the prior 3 years was compared to diagnostic codes for overdoses and substance use disorders in the same time period.

RESULTS

The sensitivity of diagnostic codes for overdose, compared to self-report as a reference standard for this analysis, varied by substance: 28.1% for alcohol, 23.1% for sedatives, 12.0% for opioids, and 5.5% for cocaine. There was a notable concordance between substance use disorder diagnoses and self-reported overdose (sensitivity range 17.9%-90.6%).

DISCUSSION AND CONCLUSIONS

Diagnostic codes in health records may not identify a substantial proportion of drug overdoses. A health record diagnosis of substance use disorder may offer a stronger inference regarding the size of the population at risk. Alternatively, screening for self-reported overdose in routine clinical care could enhance overdose surveillance and targeted intervention.

SCIENTIFIC SIGNIFICANCE

This study suggests that diagnostic codes for overdose are insensitive. These findings support consideration of alternative approaches to overdose surveillance in public health.

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.

Characterising methamphetamine use to inform health and social policies in Manitoba, Canada: a protocol for a retrospective cohort study using linked administrative data

INTRODUCTION

Rising use of methamphetamine is causing significant public health concern in Canada. The biological and behavioural effects of methamphetamine range from wakefulness, vigour and euphoria to adverse physical health outcomes like myocardial infarction, haemorrhagic stroke, arrhythmia and seizure. It can also cause severe psychological complications such as psychosis. National survey data point to increasing rates of methamphetamine use, as well as increasing ease of access and serious methamphetamine-related harms. There is an urgent need for evidence to address knowledge gaps, provide direction to harm reduction and treatment efforts and inform health and social policies for people using methamphetamine. This protocol describes a study that aims to address this need for evidence.

METHODS

The study will use linked, whole population, de-identified administrative data from the Manitoba Population Research Data Repository. The cohort will include individuals in the city of Winnipeg, Manitoba, who came into contact with the health system for reasons related to methamphetamine use from 2013 to 2021 and a comparison group matched on age, sex and geography. We will describe the cohort's sociodemographic characteristics, calculate incidence and prevalence of mental disorders associated with methamphetamine use and examine rates of health and social service use. We will evaluate the use of olanzapine pharmacotherapy in reducing adverse emergency department outcomes. In partnership with Indigenous co-investigators, outcomes will be stratified by First Nations and Métis identity.

ETHICS AND DISSEMINATION

The study was approved by the University of Manitoba Health Research Ethics Board, and access datasets have been granted by all data providers. We also received approval from the First Nations Health and Social Secretariat of Manitoba's Health Information Research Governance Committee and the Manitoba Métis Federation. Dissemination will be guided by an 'Evidence 2 Action' group of public rightsholders, service providers and knowledge users who will ensure that the analyses address the critical issues.

When Effects Cannot be Estimated: Redefining Estimands to Understand the Effects of Naloxone Access Laws

Violations of the positivity assumption (also called the common support condition) challenge health policy research and can result in significant bias, large variance, and invalid inference. We define positivity in the single- and multiple-timepoint (i.e., longitudinal) health policy evaluation setting, and discuss real-world threats to positivity. We show empirical evidence of the practical positivity violations that can result when attempting to estimate the effects of health policies (in this case, Naloxone Access Laws). In such scenarios, an alternative is to estimate the effect of a shift in law enactment (e.g., the effect if enactment had been delayed by some number of years). Such an effect corresponds to what is called a modified treatment policy, and dramatically weakens the required positivity assumption, thereby offering a means to estimate policy effects even in scenarios with serious positivity problems. We apply the approach to define and estimate the longitudinal effects of Naloxone Access Laws on opioid overdose rates.

Comparative Risk of Opioid Overdose With Concomitant use of Prescription Opioids and Skeletal Muscle Relaxants

BACKGROUND AND OBJECTIVES

The concomitant use of prescription opioids and skeletal muscle relaxants has been associated with opioid overdose, but little data exist on the head-to-head safety of these drug combinations. The objective of this study was to compare the risk of opioid overdose among patients on long-term opioid therapy who concurrently initiate skeletal muscle relaxants.

METHODS

We conducted an active comparator cohort study spanning 2000 to 2019 using healthcare utilization data from four US commercial and public insurance databases. Individuals were required to have at least 180 days of continuous enrollment and at least 90 days of continuous prescription opioid use immediately before and on the date of skeletal muscle relaxant initiation. Exposures were the concomitant use of prescription opioids and skeletal muscle relaxants, and the main outcome was the hazard ratio (HR) and bootstrapped 95% confidence interval (CI) of opioid overdose resulting in an emergency visit or hospitalization. The primary analysis quantified opioid overdose risk across seven prescription opioid-skeletal muscle relaxant therapies and a negative control outcome (sepsis) to assess potential confounding by unmeasured illicit opioid use. Secondary analyses evaluated two- and five-group comparisons in patients with similar baseline characteristics; individuals without prior recorded substance abuse; and subgroups stratified by baseline opioid dosage, benzodiazepine co-dispensing, and oxycodone or hydrocodone use.

RESULTS

Weighted HR of opioid overdose relative to cyclobenzaprine was 2.52 (95% CI 1.29-4.90) for baclofen; 1.64 (95% CI 0.81-3.34) for carisoprodol; 1.14 (95% CI 0.53-2.46) for chlorzoxazone/orphenadrine; 0.46 (95% CI 0.17-1.24) for metaxalone; 1.00 (95% CI 0.45-2.20) for methocarbamol; and 1.07 (95% CI 0.49-2.33) for tizanidine in the 30-day intention-to-treat analysis. Findings were similar in the as-treated analysis, two- and five-group comparisons, and in patients without prior recorded substance abuse. None of the therapies relative to cyclobenzaprine were associated with sepsis, and no subgroups indicated increased risk of opioid overdose.

DISCUSSION

Concomitant use of prescription opioids and baclofen relative to cyclobenzaprine is associated with opioid overdose. Clinical interventions may focus on prescribing alternatives in the same drug class or providing access to opioid antagonists if treatment with both medications is necessary for pain management.

Association of Postsurgical Opioid Refills for Patients With Risk of Opioid Misuse and Chronic Opioid Use Among Family Members

IMPORTANCE

The US health care system is experiencing a sharp increase in opioid-related adverse events and spending, and opioid overprescription may be a key factor in this crisis. Ambient opioid exposure within households is one of the known major dangers of overprescription.

OBJECTIVE

To quantify the association between the postsurgical initiation of prescription opioid use in opioid-naive patients and the subsequent prescription opioid misuse and chronic opioid use among opioid-naive family members.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study was conducted using administrative data from the database of a US commercial insurance provider with more than 35 million covered individuals. Participants included pairs of patients who underwent surgery from January 1, 2008, to December 31, 2016, and their family members within the same household. Data were analyzed from January 1 to November 30, 2018.

EXPOSURES

Duration of opioid exposure and refills of opioid prescriptions received by patients after surgery.

MAIN OUTCOMES AND MEASURES

Risk of opioid misuse and chronic opioid use in family members were calculated using inverse probability weighted Cox proportional hazards regression models.

RESULTS

The final cohort included 843 531 pairs of patients and family members. Most pairs included female patients (445 456 [52.8%]) and male family members (442 992 [52.5%]), and a plurality of pairs included patients in the 45 to 54 years age group (249 369 [29.6%]) and family members in the 15 to 24 years age group (313 707 [37.2%]). A total of 3894 opioid misuse events (0.5%) and 7485 chronic opioid use events (0.9%) occurred in family members. In adjusted models, each additional opioid prescription refill for the patient was associated with a 19.2% (95% CI, 14.5%-24.0%) increase in hazard of opioid misuse in family members. The risk of opioid misuse appeared to increase only in households in which the patient obtained refills. Family members in households with any refill had a 32.9% (95% CI, 22.7%-43.8%) increased adjusted hazard of opioid misuse. When patients became chronic opioid users, the hazard ratio for opioid misuse among family members was 2.52 (95% CI, 1.68-3.80), and similar patterns were found for chronic opioid use.

CONCLUSIONS AND RELEVANCE

This cohort study found that opioid exposure was a household risk. Family members of a patient who received opioid prescription refills after surgery had an increased risk of opioid misuse and chronic opioid use.

Pharmaceutical opioid poisonings in Victoria, Australia: Rates and characteristics of a decade of emergency department presentations among nine pharmaceutical opioids

BACKGROUND AND AIMS

Pharmaceutical opioids are a significant contributor to the global 'opioid crisis', yet few studies have comprehensively distinguished between opioid types. We measured whether a range of common pharmaceutical opioids varied in their contribution to the rates and characteristics of harm in a population-wide indicator of non-fatal overdose.

DESIGN

Retrospective observational study of emergency department (ED) patient care records in the Victorian Emergency Minimum Data set (VEMD), July 2009 to June 2019.

SETTING

Victoria, Australia.

CASES

ED presentations for non-fatal overdose related to pharmaceutical opioid use (n = 5403), where the specific pharmaceutical opioid was documented.

MEASUREMENTS

We compared harms across the nine individual pharmaceutical opioids most commonly sold, and considered where multiple opioids contributed to the overdose. We calculated supply-adjusted rates of ED presentations using Poisson regression and used multinomial logistic regression to compare demographic and clinical characteristics of presentations among nine distinct pharmaceutical opioids and a 10th category where multiple opioids were documented for the presentation.

FINDINGS

There were wide differences, up to 27-fold, between supply-adjusted rates of overdose. When considering presentations with sole opioids, the highest supply-adjusted overdose rates [per 100 000 oral morphine equivalents (OME); 95% confidence interval (CI)] were for codeine (OME = 0.078, 95% CI = 0.073-0.08) and oxycodone (OME =0.029, 95% CI = 0.027-0.030) and the lowest were for tapentadol (OME = 0.004, 95% CI = 0.003-0.006) and fentanyl (OME = 0.003, 95% CI = 0.002-0.004). These rates appeared related to availability rather than opioid potency. Most (62%) poisonings involved females. Codeine, oxycodone and tramadol were associated with younger presentations (respectively, 59.5%, 41.7% and 49.8% of presentations were 12-34 years old), and intentional self-harm (respectively 65.2%, 50.6%, and 52.8% of presentations). Relative to morphine, fentanyl [ 0.32 relative risk ratio (RRR)] and methadone ( 0.58 RRR) presentations were less likely to be coded as self-harm. Relative to morphine-buprenorphine, codeine, oxycodone and tramadol presentations were significantly more likely to be associated with the less urgent triage categories (respectively 2.18, 1.80, 1.52, 1.65 RRR).

CONCLUSIONS

In Victoria, Australia, rates and characteristics of emergency department presentations for pharmaceutical opioids show distinct variations by opioid type.

Naloxone and Buprenorphine Prescribing Following US Emergency Department Visits for Suspected Opioid Overdose: August 2019 to April 2021

STUDY OBJECTIVE

Nonfatal emergency department (ED) visits for opioid overdose are important opportunities to prescribe naloxone and buprenorphine, both of which can prevent future overdose-related mortality. We assessed the rate of this prescribing using national data from August 2019 to April 2021, a period during which US opioid overdose deaths reached record levels.

METHODS

We conducted a retrospective cohort analysis using Symphony Health's Integrated Dataverse, which includes data from 5,800 hospitals and 70,000 pharmacies. Of ED visits for opioid overdose between August 4, 2019, and April 3, 2021, we calculated the proportion with at least 1 naloxone prescription within 30 days and repeated this analysis for buprenorphine. To contextualize the naloxone prescribing rate, we calculated the proportion of ED visits for anaphylaxis with at least 1 prescription for epinephrine-another life-saving rescue medication-within 30 days.

RESULTS

Analyses included 148,966 ED visits for opioid overdose. Mean weekly visits increased 23.6% during the period between April 26, 2020 and October 3, 2020 compared with the period between August 4, 2019 to April 25, 2020. Visits declined to prepandemic levels between October 4, 2020 and March 13, 2021, after which visits began to rise. Naloxone and buprenorphine were prescribed within 30 days at 7.4% and 8.5% of the 148,966 visits, respectively. The naloxone prescribing rate (7.4%) was substantially lower than the epinephrine prescribing rate (48.9%) after ED visits for anaphylaxis.

CONCLUSION

Between August 4, 2019, and April 3, 2021, naloxone and buprenorphine were only prescribed after 1 in 13 and 1 in 12 ED visits for opioid overdose, respectively. Findings suggest that clinicians are missing critical opportunities to prevent opioid overdose-related mortality.

Trends and characteristics of hospitalisations from the harmful use of opioids in England between 2008 and 2018: Population-based retrospective cohort study

Objective

To examine the trends and characteristics of opioid-related hospital admissions in England over 10 years, and its burden for the National Health Service and public finances.

Design

Patient-level data from the Hospital Episode Statistics database to examine all opioid-related hospitalisations from 2008 to 2018, stratified by type of opioid admission and patient demographics.

Setting

All National Health Service hospitals in England.

Participants

Patients hospitalised from the harmful use of opioids.

Main outcome measures

The number of opioid-related hospitalisations, length of stay, in-hospital mortality, 30-day readmission rate and treatment costs.

Results

Opioid-related hospitalisations increased by 48.9%, from 10,805 admissions in 2008 to 16,091 admissions in 2018, with total treatment costs of £137 million. The growth in opioid-related hospitalisations was 21% above the corresponding rate for all other emergency admissions in England. Relative changes showed that hospitalisations increased most for individuals older than 55 years (160%), those living in the most affluent areas of England (93.8%), and suffering from four co-morbidities (627.6%) or more. Hospitals reduced mean patient length of stay from 2.8 days to 1.1 days over 10 years. Mean in-hospital mortality was 0.4% and mean 30-day readmission risk was 16.6%.

Conclusion

Opioid use is an increasing public health concern in England, though hospitalisation and mortality rates are less pronounced than in other countries. There are concerns about significant rises in hospitalisations from older, less deprived and sicker population groups. Our findings should prompt policymakers to go beyond monitoring mortality statistics when assessing the impacts of harmful use of opioids.

Risk of Opioid Overdose Associated With Concomitant Use of Oxycodone and Selective Serotonin Reuptake Inhibitors

IMPORTANCE

Some selective serotonin reuptake inhibitors (SSRIs) inhibit the enzymes responsible for the metabolism of oxycodone, a potent prescription opioid. The clinical consequences of this interaction on the risk of opioid overdose have not been elucidated.

OBJECTIVE

To compare opioid overdose rates in patients initiating oxycodone while taking SSRIs that are potent inhibitors of the cytochrome-P450 2D6 enzyme (CYP2D6) vs SSRIs that are not.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study included adults who initiated oxycodone while receiving SSRI therapy between 2000 and 2020 whose data were included in 3 US health insurance databases.

EXPOSURES

Use of SSRIs that strongly inhibit CYP2D6 enzyme (fluoxetine or paroxetine) vs use of other SSRIs at the time of oxycodone initiation.

MAIN OUTCOMES AND MEASURES

Opioid overdose hospitalization or emergency department visit. Outcomes were assessed within 365 days of oxycodone initiation; in primary analyses, patients were followed up until the discontinuation of either oxycodone or their index SSRI group. Propensity score matching weights were used to adjust for confounding. Crude and weighted (adjusted) incidence rates and hazard ratios were estimated using Cox regression models, separately within each database and overall, stratifying on database.

RESULTS

A total of 2 037 490 initiated oxycodone while taking SSRIs (1 475 114 [72.4%] women; mean [SD] age, 50.1 [15.3] years). Most (1 418 712 [69.6%]) were receiving other SSRIs at the time of oxycodone initiation. In the primary analysis, we observed 1035 overdose events (0.05% of the study cohort). The adjusted incidence rate of opioid overdose in those using inhibiting SSRIs at the time of oxycodone initiation (9.47 per 1000 person-years) was higher than in those using other SSRIs (7.66 per 1000 person-years), indicating a greater risk of overdose among patients using CYP2D6-inhibiting SSRIs (adjusted hazard ratio, 1.23; 95% CI, 1.06-1.31). Results were consistent across multiple subgroup and sensitivity analyses.

CONCLUSIONS AND RELEVANCE

In this cohort study of US adults, initiating oxycodone in patients treated with paroxetine or fluoxetine was associated with a small increased risk of opioid overdose.

Measuring Substance-Related Disorders Using Canadian Administrative Health Databanks: Interprovincial Comparisons of Recorded Diagnostic Rates, Incidence Proportions and Mortality Rate Ratios

CONTEXT

Assessing temporal changes in the recorded diagnostic rates, incidence proportions, and health outcomes of substance-related disorders (SRD) can inform public health policymakers in reducing harms associated with alcohol and other drugs.

OBJECTIVE

To report the annual and cumulative recorded diagnostic rates and incidence proportions of SRD, as well as mortality rate ratios (MRRs) by cause of death among this group in Canada, according to their province of residence.

METHODS

Analyses were performed on linked administrative health databases (AHD; physician claims, hospitalizations, and vital statistics) in five Canadian provinces (Alberta, Manitoba, Ontario, Québec, and Nova Scotia). Canadians 12 years and older and registered for their provincial healthcare coverage were included. The International Classification of Diseases (ICD-9 or ICD-10 codes) was used for case identification of SRD from April 2001 to March 2018.

RESULTS

During the study period, the annual recorded SRD diagnostic rates increased in Alberta (2001-2002: 8.0‰; 2017-2018: 12.8‰), Ontario (2001-2002: 11.5‰; 2017-2018: 14.4‰), and Nova Scotia (2001-2002: 6.4‰; 2017-2018: 12.7‰), but remained stable in Manitoba (2001-2002: 5.5‰; 2017-2018: 5.4‰) and Québec (2001-2002 and 2017-2018: 7.5‰). Cumulative recorded SRD diagnostic rates increased steadily for all provinces. Recorded incidence proportions increased significantly in Alberta (2001-2002: 4.5‰; 2017-2018: 5.0‰) and Nova Scotia (2001-2002: 3.3‰; 2017-2018: 3.8‰), but significantly decreased in Ontario (2001-2002: 6.2‰; 2017-2018: 4.7‰), Québec (2001-2002: 4.1‰; 2017-2018: 3.2‰) and Manitoba (2001-2002: 2.7‰; 2017-2018: 2.0‰). For almost all causes of death, a higher MRR was found among individuals with recorded SRD than in the general population. The causes of death in 2015-2016 with the highest MRR for SRD individuals were SRD, suicide, and non-suicide trauma in Alberta, Ontario, Manitoba, and Québec.

DISCUSSION

Linked AHD covering almost the entire population can be useful to monitor the medical service trends of SRD and, therefore, guide health services planning in Canadian provinces.

Emergency Department Drug Surveillance (EDDS) hospital's urinalysis results compared with expanded re-testing by an independent laboratory, a pilot study

INTRODUCTION

Most hospital urine toxicology screens detect a fixed, limited set of common substances. These tests are fast and accurate but may miss emerging trends in substance use in the community and clinical acumen alone is insufficient for identifying new substances.

METHODS

This prospective cohort study examined de-identified urine specimens obtained from patients visiting the Emergency Department (ED) at Prince George's Hospital Center (PGHC), between October 15, 2019 to November 6, 2019 and tested positive for one or more substances. The Emergency Department Drug Surveillance System (EDDS) collects quarterly exports from de-identified electronic health records (EHRs) containing urinalysis results for drug related ED visits. We performed a feasibility study of a new urine specimen submission by collecting a stratified sample of 151 urine specimens from PGHC ED patients. The specimens were tested for 240 drugs using liquid chromatography-tandem mass spectrometry (LC-MS/MS). This paper presents a comparison between the PGHC and expanded testing results.

RESULTS

The expanded urinalysis panel found more cocaine (37% vs. 20%; p < 0.01) and benzodiazepine positives (21% vs. 11%; p < 0.05) than would have been detected by the hospital screen. Additionally, the expanded toxicology panel identified fentanyl in 4-14% of the samples.

CONCLUSION

The EHR data submitted to EDDS from the hospital urine toxicology screen correctly identified hospital substance use patterns over the approximate 1 month study period. The expanded testing also uncovered drugs that the hospital might consider adding to their routine screen. EDDS is a feasible system for monitoring and confirming recent substance use trends among ED patients.

National trends in population rates of opioid-related mortality, hospitalization and emergency department visits in Canada between 2000 and 2017. A population-based study

BACKGROUND AND AIMS

Existing assessments of the time-trends of opioid-related mortality, hospitalization and emergency department visits in Canada have relied mainly on provincial databases, while national assessments generally do not provide information before 2016. We aimed to estimate Canadian national time trends in opioid-related mortality from 2000 to 2017 and opioid-related hospitalization and emergency department visits between 2000 and 2012.

DESIGN

Retrospective cohort study.

SETTING AND PARTICIPANTS

Residents of all Canadian provinces and territories for which comparable data were available from 2000 to 2017.

MEASUREMENTS

We identified opioid-related mortality, hospitalization and emergency department visits using validated algorithms using ICD codes from administrative databases. We calculated crude rates and sex- and age-adjusted rates per million. For hospitalizations, we calculated case-fatality, 90-day and 365-day all-cause mortality and opioid-related re-hospitalization rates. We used Poisson regression to examine the significance of the time trend.

FINDINGS

From 2000 to 2017, the adjusted opioid mortality rate in Canada (outside Quebec) increased significantly by 592.9% (from 20.0 opioid deaths per million in 2000 to 118.3 in 2017). The highest year-to-year increases were from 2015 to 2016 (31.8%) and from 2016 to 2017 (52.2%). The adjusted hospitalizations doubled significantly during the study period (an increase of 103.7%, from 159.7 opioid hospitalizations per million Canadians in 2000 to 325.3 in 2012). The adjusted rate of emergency department visits increased significantly by 188.7% (from 280.6 per million in 2000 to 810.1 in 2012). Case-fatality was 2.3% overall and was mainly constant during the study period. Both 90- and 365-day all-cause mortality increased significantly between 2000 and 2011 (from 1.7 to 3.1% and 3.9 to 7.4%, respectively), while re-hospitalization for opioid-related diagnoses was reduced (from 7.8 to 6.4% and 14.2 to 12.9%, respectively).

CONCLUSIONS

Opioid-related mortality, hospitalization and emergency department visits in Canada have been increasing gradually since 2000.

Variation in emergency department visit rates for opioid use disorder: Implications for quality improvement initiatives

STUDY OBJECTIVE

Emergency departments (ED) are critical touchpoints for encounters among patients with opioid use disorder (OUD), but implementation of ED initiated treatment and harm reduction programs has lagged. We describe national patient, visit and hospital-level characteristics of ED OUD visits and characterize EDs with high rates of OUD visits in order to inform policies to optimize ED OUD care.

METHODS

We conducted a descriptive, cross-sectional study with the 2017 Nationwide Emergency Department Sample (NEDS) from the Healthcare Cost and Utilization Project, using diagnostic and mechanism of injury codes from ICD-10 to identify OUD related visits. NEDS weights were applied to generate national estimates. We evaluated ED visit and clinical characteristics of all OUD encounters. We categorized hospitals into quartiles by rate of visits for OUD per 1000 ED visits and described the visit, clinical, and hospital characteristics across the four quartiles.

RESULTS

In 2017, the weighted national estimate for OUD visits was 1,507,550. Overdoses accounted for 295,954. (19.6%) of visits. OUD visit rates were over 8× times higher among EDs in the highest quartile of OUD visit rate (22.9 per 1000 total ED visits) compared with EDs in the lowest quartile of OUD visit rate (2.7 per 1000 ED visits). Over three fifths (64.2%) of all OUD visits nationwide were seen by the hospitals in the highest quartile of OUD visit rate. These hospitals were predominantly in metropolitan areas (86.2%), over half were teaching hospitals (51.7%), and less than a quarter (23.3%) were Level 1 or Level 2 trauma centers.

CONCLUSION

Targeting initial efforts of OUD care programs to high OUD visit rate EDs could improve care for a large portion of OUD patients utilizing emergency care.

Defining indicators for drug overdose emergency department visits and hospitalisations in ICD-10-CM coded discharge data

Introduction

The drug overdose epidemic has worsened over the past decade; however, efforts have been made to better understand and track nonfatal overdoses using various data sources including emergency department and hospital admission data from billing and discharge files.

Methods and findings

The Centers for Disease Control and Prevention (CDC) has developed surveillance case definition guidance using standardised discharge diagnosis codes for public health practitioners and epidemiologists using lessons learnt from CDC’s funded recipients and the Council for State and Territorial Epidemiologists (CSTE) International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) Drug Poisoning Indicators Workgroup and General Injury ICD-10-CM Workgroup. CDC’s guidance was informed by health departments and CSTE’s workgroups and included several key aspects for assessing drug overdose in emergency department and hospitalisation discharge data. These include: (1) searching all diagnosis fields to identify drug overdose cases; (2) estimating drug overdose incidence using visits for initial encounter but excluding subsequent encounters and sequelae; (3) excluding underdosing and adverse effects from drug overdose incidence indicators; and (4) using codes T36–T50 for overdose surveillance. CDC’s guidance also suggests analysing intent separately for ICD-10-CM coding.

Conclusions

CDC’s guidance provides health departments a key tool to better monitor drug overdoses in their community. The implementation and validation of this standardised guidance across all CDC-funded health departments will be key to ensuring consistent and accurate reporting across all entities.

Association Between Receipt of Overlapping Opioid and Benzodiazepine Prescriptions From Multiple Prescribers and Overdose Risk

IMPORTANCE

The receipt of overlapping opioid and benzodiazepine prescriptions is associated with increased overdose risk. It is unknown whether this increase in risk varies when overlapping prescriptions are written by multiple prescribers vs 1 prescriber.

OBJECTIVE

To evaluate the association between receipt of overlapping opioid and benzodiazepine prescriptions from multiple prescribers and overdose risk.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study was conducted using 2017 to 2018 claims from the Optum deidentified Clinformatics Data Mart. Participants were patients with private insurance or Medicare Advantage aged 12 years or older with overlapping opioid and benzodiazepine prescriptions. Data were analyzed from March through November 2020.

EXPOSURES

For each patient, person-days on which opioid and benzodiazepine prescriptions overlapped were identified. The exposure was whether these prescriptions were written by multiple prescribers vs 1 prescriber.

MAIN OUTCOMES AND MEASURES

The outcome was a treated overdose, defined as the occurrence of 1 or more claims containing a diagnosis code for opioid or benzodiazepine poisoning on a person-day of opioid-benzodiazepine overlap. The association between exposure and outcome at the person-day level was estimated using logistic regression, controlling for opioid and benzodiazepine prescribing patterns, demographics, and comorbidities. The average marginal effect (AME) of the exposure, defined as the absolute difference in the probability of a treated overdose if all person-days of overlap involved prescriptions from multiple prescribers vs 1 prescriber, was calculated.

RESULTS

Among 529 053 patients, the mean (SD) age was 61.2 (15.6) years and 350 857 (66.3%) were female patients. Mean (SD) follow-up was 198.7 (249.8) days. During follow-up, overdose occurred on 1 or more person-days of opioid-benzodiazepine overlap for 2288 patients (0.4%, or 1 in 231 patients). There were 52 989 316 person-days of opioid-benzodiazepine overlap. Among 19 895 457 person-days (37.5%) involving prescriptions from multiple prescribers, there were 1390 overdoses (7.0 per 100 000 person-days), and among 33 093 859 person-days (62.5%) involving prescriptions from 1 prescriber, there were 1302 overdoses (3.9 per 100 000 person-days). Overdose risk was increased 1.8-fold (95% CI, 1.6-1.9) on person-days of overlap involving prescriptions from multiple prescribers vs 1 prescriber. The association between multiple prescribers and increased risk of overdose persisted in adjusted analyses (adjusted odds ratio, 1.20; 95% CI, 1.10-1.31; AME, 0.91 per 100 000 person-days of overlap; 95% CI, 0.46-1.37).

CONCLUSIONS AND RELEVANCE

This study found that among patients already at increased risk of overdose owing to concurrent treatment with opioids and benzodiazepines, overdose risk was increased further when multiple prescribers were responsible for this treatment regimen compared with 1 prescriber. This increased risk was not fully accounted for by differences in prescribing patterns, demographics, or comorbidities. This finding suggests that other factors, such as poor care coordination, may be associated with the increase in risk.

Characterizing trends in methamphetamine-related health care use when there is no ICD code for "methamphetamine use disorder"

BACKGROUND AND AIMS

The recent surge in methamphetamine use highlights the need for timely data on its health effects and healthcare service use impact. However, there is no ICD code for methamphetamine use. This study quantifies the positive predictive value of ICD-9-CM and ICD-10-CM psychostimulant codes for methamphetamine use.

METHODS

A retrospective chart review of 220 adults aged 18 and older who had an inpatient admission with a psychostimulant-associated billing diagnosis at an urban safety-net hospital. Diagnoses were categorized as either methamphetamine-related or involving another specific psychostimulant. The positive predictive value of both ICD-9-CM or ICD-10-CM psychostimulant diagnosis codes for methamphetamine use was calculated.

RESULTS

ICD-9-CM and ICD-10-CM psychostimulant codes had high positive predictive values of 78.2% (95% CI 70.3%-86.0%) and 85.5% (95% CI 78.8%-92.1%), respectively, for methamphetamine use. The most common non-methamphetamine psychostimulant in our cohort was khat, a cathinone-containing plant native to East Africa, accounting for psychostimulant-related diagnosis in 16 of the 220 hospitalizations.

CONCLUSIONS

The high predictive values of psychostimulant codes for methamphetamine use support the application of administrative data in measuring methamphetamine-related healthcare use, as well as co-morbid health conditions and treatment patterns.

Dental Opioid Prescriptions and Overdose Risk in Patients and Their Families

INTRODUCTION

It is unknown whether dental opioid prescriptions are associated with opioid overdose in patients or their family members, who may have access to patients' opioids.

METHODS

During July-October 2020, the 2011-2018 IBM MarketScan Dental, IBM MarketScan Commercial, and Medicaid Multi-State Databases were analyzed. Two analyses were conducted. In the patient analysis, dental procedures for privately and publicly insured patients aged 13-64 years were identified. The exposure was ≥1 initial prescription (dispensed opioid prescription within 3 days of the procedure). The association between the exposure and ≥1 overdose within 90 days of the procedure was evaluated using logistic regression. In the family analysis, procedures for privately insured patients in family plans were identified. The association between the exposure and ≥1 overdose in a family member within 90 days was evaluated using logistic regression. In both analyses, the average marginal effect of the exposure was calculated, representing the change in the probability of the outcome if all versus if no procedures were associated with ≥1 initial prescription.

RESULTS

The patient analysis included 8,544,098 procedures. When ≥1 initial prescription did and did not occur, the 90-day risk of overdose was 5.8 versus 2.2 per 10,000 procedures (average marginal effect=1.5, 95% CI=1.2, 1.8). The family analysis included 3,461,469 procedures. When ≥1 initial prescription did and did not occur, the 90-day risk of overdose in a family member was 1.7 versus 1.0 per 10,000 procedures (average marginal effect=0.4, 95% CI=0.1, 0.7).

CONCLUSIONS

Findings further highlight the importance of avoiding unnecessary dental opioid prescribing.

Adverse Events And Emergency Department Opioid Prescriptions In Adolescents

Understanding the risks associated with opioid prescription in adolescents is critical for informing opioid policy, but the risks are challenging to quantify given the lack of randomized trial data. Using a regression discontinuity design, we exploited a discontinuous increase in opioid prescribing in the emergency department (ED) when adolescents transition from "child" to "adult" at age eighteen to estimate the effect of an ED opioid prescription on subsequent opioid-related adverse events. We found that adolescent patients just over age eighteen were similar to those just under age eighteen, but they were 9.7 percent more likely to be prescribed an opioid and 12.6 percent more likely to have an adverse opioid-related event, defined as overdose, diagnosis of opioid use disorder, or long-term opioid use, within one year. We estimated a 14.1 percent increased risk for an adverse outcome when "adults" just over age eighteen were prescribed opioids that would not have been prescribed if they were just under age eighteen and considered "children." Our results suggest that differences in care provided in pediatric versus adult care settings may be important to understanding prescribers' roles in the opioid epidemic.

Differences and similarities between emergency department syndromic surveillance and hospital discharge data for nonfatal drug overdose

PURPOSE

Emergency department syndromic surveillance and hospital discharge data have been used to detect and monitor nonfatal drug overdose, yet few studies have assessed the differences and similarities between these two data sources.

METHODS

The Centers for Disease Control and Prevention Drug Overdose Surveillance and Epidemiology system data from 14 states were used to compare these two sources at estimating monthly overdose burden and trends from January 2018 through December 2019 for nonfatal all drug, opioid-, heroin-, and stimulant-involved overdoses.

RESULTS

Compared to discharge data, syndromic data captured 13.3% more overall emergency department visits, 67.8% more all drug overdose visits, 15.6% more opioid-involved overdose visits, and 78.8% more stimulant-involved overdose visits. Discharge data captured 18.9% more heroin-involved overdoses. Significant trends were identified for all drug (Average Monthly Percentage Change [AMPC]=1.1, 95% CI=0.4,1.8) and stimulant-involved overdoses (AMPC=2.4, 95% CI=1.2,3.7) in syndromic data; opioid-involved overdoses increased in both discharge and syndromic data (AMPC_Discharge=0.9, 95% CI=0.2,1.7; AMPC_Syndromic=1.9, CI=1.1,2.8).

CONCLUSIONS

Results demonstrate that discharge data may be better for reporting counts, yet syndromic data are preferable to detect changes quickly and to alert practitioners and public health officials to local overdose clusters. These data sources do serve complementary purposes when examining overdose trends.

Coprescription of Opioids With Other Medications and Risk of Opioid Overdose

Polypharmacy is common among patients taking prescription opioids long-term, and the codispensing of interacting medications may further increase opioid overdose risk. To identify nonopioid medications that may increase opioid overdose risk in this population, we conducted a case-crossover-based screening of electronic claims data from IBM MarketScan and Optum Clinformatics Data Mart spanning 2003 through 2019. Eligible patients were 18 years of age or older and had at least 180 days of continuous enrollment and 90 days of prescription opioid use immediately before an opioid overdose resulting in an emergency room visit or hospitalization. The main analysis quantified the odds ratio (OR) between opioid overdose and each nonopioid medication dispensed in the 90 days immediately before the opioid overdose date after adjustment for prescription opioid dosage and benzodiazepine codispensing. Additional analyses restricted to patients without cancer diagnoses and individuals who used only oxycodone for 90 days immediately before the opioid overdose date. The false discovery rate (FDR) was used to account for multiple testing. We identified 24,866 individuals who experienced opioid overdose. Baclofen (OR 1.56; FDR < 0.01; 95% confidence interval (CI), 1.29 to 1.89), lorazepam (OR 1.53; FDR < 0.01; 95% CI, 1.25 to 1.88), and gabapentin (OR 1.16; FDR = 0.09; 95% CI, 1.04 to 1.28), among other nonopioid medications, were associated with opioid overdose. Similar patterns were observed in noncancer patients and individuals who used only oxycodone. Interventions may focus on prescribing safer alternatives when a potential for interaction exists.

Using ICD-10-CM codes to detect illicit substance use: A comparison with retrospective self-report

BACKGROUND

Understanding whether International Classification of Disease, 10th Revision, Clinical Modification (ICD-10-CM) codes can be used to accurately detect substance use can inform their use in future surveillance and research efforts.

METHODS

Using 2015-2018 data from a retrospective cohort study of 602 safety-net patients prescribed opioids for chronic non-cancer pain, we calculated the sensitivity and specificity of using ICD-10-CM codes to detect illicit substance use compared to retrospective self-report by substance (methamphetamine, cocaine, opioids [heroin or non-prescribed opioid analgesics]), self-reported use frequency, and type of healthcare encounter.

RESULTS

Sensitivity of ICD-10-CM codes for detecting self-reported substance use was highest for methamphetamine (49.5 % [95 % confidence interval: 39.6-59.5 %]), followed by cocaine (44.4 % [35.8-53.2 %]) and opioids (36.3 % [28.8-44.2 %]); higher for participants who reported more frequent methamphetamine (intermittent use: 27.7 % [14.6-42.6 %]; ≥weekly use: 67.2 % [53.7-79.0 %]) and opioid use (intermittent use: 21.4 % [13.2-31.7 %]; ≥weekly use: 52.6 % [40.8-64.2 %]); highest for outpatient visits (methamphetamine: 43.8 % [34.1-53.8 %]; cocaine: 36.8 % [28.6-45.6 %]; opioids: 33.1 % [25.9-41.0 %]) and lowest for emergency department visits (methamphetamine: 8.6 % [4.0-15.6 %]; cocaine: 5.3 % [2.1-10.5 %]; opioids: 6.3 % [3.0-11.2 %]). Specificity was highest for methamphetamine (96.4 % [94.3-97.8 %]), followed by cocaine (94.0 % [91.5-96.0 %]) and opioids (85.0 % [81.3-88.2 %]).

CONCLUSIONS

ICD-10-CM codes had high specificity and low sensitivity for detecting self-reported substance use but were substantially more sensitive in detecting frequent use. ICD-10-CM codes to detect substance use, particularly those from emergency department visits, should be used with caution, but may be useful as a lower-bound population measure of substance use or for capturing frequent use among certain patient populations.

Dual-trajectories of opioid and gabapentinoid use and risk of subsequent drug overdose among Medicare beneficiaries in the United States: a retrospective cohort study

BACKGROUND AND AIMS

Little is known about opioid and gabapentinoid (OPI-GABA) use duration and dose patterns' associations with adverse outcome risks. We examined associations between OPI-GABA dose and duration trajectories and subsequent drug overdose.

DESIGN

Retrospective cohort study.

SETTING

US Medicare.

PARTICIPANTS

Using a 5% sample (2011-16), we identified 71 005 fee-for-service Medicare beneficiaries with fibromyalgia, low back pain, neuropathy and/or osteoarthritis initiating OPIs and/or GABAs [mean age ± standard deviation (SD) = 65.5 ± 14.5 years, female = 68.1%, white = 76.8%].

MEASUREMENTS

Group-based multi-trajectory models identified distinct OPI-GABA use patterns during the year of OPI and/or GABA initiation, based on weekly average standardized daily dose (i.e. OPIs = morphine milligram equivalent, GABAs = minimum effective daily dose). We estimated models with three to 12 trajectories and selected the best model based on Bayesian information criterion (BIC) and Nagin's criteria. We estimated risk of time to first drug overdose diagnosis within 12 months following the index year, adjusting for socio-demographic and health factors using inverse probability of treatment weighted multivariable Cox proportional hazards models.

FINDINGS

We identified 10 distinct trajectories (BIC = -1 176 954; OPI-only = 3, GABA-only = 3, OPI-GABA = 4). Compared with OPI-only early discontinuers (40.6% of the cohort), 1-year drug overdose risk varied by trajectory group: consistent low-dose OPI-only users [16.6%; hazard ratio (HR) = 1.47, 95% confidence interval (CI) = 1.19-1.82], consistent high-dose OPI-only users (1.8%; HR = 4.57, 95% CI = 2.99-6.98), GABA-only early discontinuers (12.5%; HR = 1.39, 95% CI = 1.09-1.77), consistent low-dose GABA-only users (11.0%; HR = 1.44, 95% CI = 1.12-1.85), consistent high-dose GABA-only users (3.1%; HR = 1.43, 95% CI = 0.94-2.17), early discontinuation of OPIs and consistent low-dose GABA users (6.9%; HR = 1.24, 95% CI = 0.90-1.69), consistent low-dose OPI-GABA users (3.4%; HR = 2.49, 95% CI = 1.76-3.52), consistent low-dose OPI and high-dose GABA users (3.2%; HR = 2.46, 95% CI = 1.71-3.53) and consistent high-dose OPI and moderate-dose GABA users (0.9%; HR = 7.22, 95% CI = 4.46-11.69).

CONCLUSIONS

Risk of drug overdose varied substantially among US Medicare beneficiaries on different use trajectories of opioids and gabapentinoids. High-dose opioid-only users and all consistent opioid and gabapentinoid users (regardless of doses) had more than double the risk of subsequent drug overdose compared with opioid-only early discontinuers.

Increasing Naloxone Prescribing in the Emergency Department Through Education and Electronic Medical Record Work-Aids

BACKGROUND

Emergency department (ED) visits for opioid overdose continue to rise. Evidence-based harm reduction strategies for opioid use disorder (OUD), such as providing home naloxone, can save lives, but ED implementation remains challenging.

METHODS

The researchers aimed to increase prescribing of naloxone to ED patients with OUD and opioid overdose by employing a model for improvement methodology, a multidisciplinary team, and high-reliability interventions. Monthly naloxone prescribing rates among discharged ED patients with opioid overdose and OUD-related diagnoses were tracked over time. Interventions included focused ED staff education on OUD and naloxone, and creation of electronic medical record (EMR)-based work-aids, including a naloxone Best Practice Advisory (BPA) and order set. Autoregressive interrupted time series was used to model the impact of these interventions on naloxone prescribing rates. The impact of education on ED staff confidence and perceived barriers to prescribing naloxone was measured using a published survey instrument.

RESULTS

After adjusting for education events and temporal trends, ED naloxone BPA and order set implementation was associated with a significant immediate 21.1% increase in naloxone prescribing rates, which was sustained for one year. This corresponded to increased average monthly prescribing rates from 1.5% before any intervention to 28.7% afterward. ED staff education had no measurable impact on prescribing rates but was associated with increased nursing perceived importance and increased provider confidence in prescribing naloxone.

CONCLUSIONS

A significant increase in naloxone prescribing rates was achieved after implementation of high-reliability EMR work-aids and staff education. Similar interventions may be key to wider ED staff engagement in harm reduction for patients with OUD.

Concurrent prescriptions for opioids and benzodiazepines and risk of opioid overdose: protocol for a retrospective cohort study using linked administrative data

INTRODUCTION

Opioid overdoses have increased substantially over the last 20 years, with over 400 000 deaths in North America. While opioid prescribing has been a target of research, benzodiazepine and opioid co-intoxication has emerged as a potential risk factor. Our aim was to assess the risk of opioid overdose associated with concurrent use of opioids and benzodiazepines relative to opioids alone.

METHODS AND ANALYSIS

A retrospective cohort study will be conducted using medical claims data from adult residents of Montréal, Canada. We will create a cohort of new users of opioids (ie, no opioid dispensations in prior year) in 2000-2014 from people with at least 2 years of continuous health insurance. Those with any diagnosis or hospitalisation for cancer or palliative care in the 2 years before their first opioid dispensation will be excluded. On each person-day of follow-up, exposure status will be classified into one of four mutually exclusive categories: (1) opioid-only, (2) benzodiazepine-only, (3) both opioid and benzodiazepine (concurrent use) or (4) neither. Opioid overdose will be measured using diagnostic codes documented in the hospital discharge abstract database, physician billing claims from emergency department visits and death records. Using a marginal structural Cox proportional hazards model, we will compare the hazard of overdose during intervals of concurrent opioid and benzodiazepine use to intervals of opioid use alone, adjusted for sociodemographics, medical and psychiatric comorbidities, and substance use disorders.

ETHICS AND DISSEMINATION

This study is approved by the McGill Faculty of Medicine Institutional Review Board and the Commission d'access à l'information (Québec privacy commission). Results will be relevant to clinicians, policymakers and other researchers interested in co-prescribing practices of opioids and benzodiazepines. Study findings will be disseminated at relevant conferences and published in biomedical and epidemiological peer-reviewed journals.

Association of Gabapentinoids With the Risk of Opioid-Related Adverse Events in Surgical Patients in the United States

IMPORTANCE

The use of gabapentinoids in multimodal postoperative analgesia is increasing; however, when coadministered with opioids, these drugs may potentiate central nervous system and respiratory depression.

OBJECTIVE

To evaluate the association between perioperative coadministration of gabapentinoids and opioids with inpatient opioid-related adverse events in surgical patients.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study used propensity score trimming, stratification, and weighting of adults admitted for a major surgery between October 2007 and December 2017 who were treated with opioids on the day of surgery and included in the Premier Research database. Data analysis was conducted from February to April 2020.

EXPOSURE

Gabapentinoids (gabapentin or pregabalin) coadministered with opioids starting the day of surgery vs opioid therapy without gabapentinoids.

MAIN OUTCOMES AND MEASURES

Primary outcome was opioid overdose. Secondary outcomes included respiratory complications, unspecified adverse effects of opioid use, and a composite of these 3 outcomes. Patients were followed up for as long as 30 days from the day of surgery until deviation from the initial treatment regimen or discharge.

RESULTS

Gabapentinoids with opioids were administered to 892 484 of 5 547 667 eligible admissions (16.1%; mean [SD] age, 63.5 [11.8] years; 353 315 [39.6%] men). Among the 4 655 183 patients who received opioids only, the mean (SD) age was 63.7 (14.7) years, and 1 913 284 (41.1%) were men. Overall, 441 overdose events were identified, with absolute risks of 1.4 per 10 000 patients with gabapentinoid exposure and 0.7 per 10 000 patients receiving opioids only. Following propensity score trimming, the cohort included 737 383 patients exposed to gabapentinoids and 3 002 480 patients receiving opioids only. The primary analysis yielded the adjusted hazard ratio of 1.95 (95% CI, 1.49-2.55), and the number needed to treat for an additional overdose to occur was 16 914 patients (95% CI, 11 556-31 537 patients). Adjusted hazard ratios for secondary outcomes were 1.68 (95% CI, 1.59-1.78) for respiratory complications, 1.77 (95% CI, 1.61-1.93) for unspecified adverse effects of opioids, and 1.70 (95% CI, 1.62-1.79) for the composite outcome. The results were consistent across sensitivity analyses and subgroups identified by key clinical factors.

CONCLUSIONS AND RELEVANCE

In this real-world cohort study of patients who underwent major surgery, concomitant use of gabapentinoids with opioids was associated with increased risk of opioid overdose and other opioid-related adverse events; however, the absolute risk of adverse events was low.

Predicting overdose among individuals prescribed opioids using routinely collected healthcare utilization data

Introduction

With increasing rates of opioid overdoses in the US, a surveillance tool to identify high-risk patients may help facilitate early intervention.

Objective

To develop an algorithm to predict overdose using routinely-collected healthcare databases.

Methods

Within a US commercial claims database (2011–2015), patients with ≥1 opioid prescription were identified. Patients were randomly allocated into the training (50%), validation (25%), or test set (25%). For each month of follow-up, pooled logistic regression was used to predict the odds of incident overdose in the next month based on patient history from the preceding 3–6 months (time-updated), using elastic net for variable selection. As secondary analyses, we explored whether using simpler models (few predictors, baseline only) or different analytic methods (random forest, traditional regression) influenced performance.

Results

We identified 5,293,880 individuals prescribed opioids; 2,682 patients (0.05%) had an overdose during follow-up (mean: 17.1 months). On average, patients who overdosed were younger and had more diagnoses and prescriptions. The elastic net model achieved good performance (c-statistic 0.887, 95% CI 0.872–0.902; sensitivity 80.2, specificity 80.1, PPV 0.21, NPV 99.9 at optimal cutpoint). It outperformed simpler models based on few predictors (c-statistic 0.825, 95% CI 0.808–0.843) and baseline predictors only (c-statistic 0.806, 95% CI 0.787–0.26). Different analytic techniques did not substantially influence performance. In the final algorithm based on elastic net, the strongest predictors were age 18–25 years (OR: 2.21), prior suicide attempt (OR: 3.68), opioid dependence (OR: 3.14).

Conclusions

We demonstrate that sophisticated algorithms using healthcare databases can be predictive of overdose, creating opportunities for active monitoring and early intervention.

Characteristics and outcomes of hospitalizations and readmissions for opioid dependence and overdose: nationally representative data

BACKGROUND

Despite the increasing rates of morbidity, mortality, and costs from the opioid addiction crisis, there is a paucity of literature on nationwide patterns of opioid abuse and dependence admissions and readmissions. We sought to investigate common comorbidities, readmission rates, and variables associated with readmission following index admission for opioid overdose or dependence. Methods: The 2013 Nationwide Readmission Database is a national database including data on more than 14 million US admissions. We used International Classification of Disease, Ninth Revision, Clinical Modification codes to identify index opioid abuse or dependence admissions, readmissions, and medical co-morbidities. We summarized all-cause readmission rates and reasons for readmission following index opioid dependence or overdose admission. We performed multivariable logistic regression, testing the association between characteristics of index admission and readmission. Results: 64,426 individuals were admitted for drug overdose or dependence during 2013. Of those, 30.1% were readmitted for all causes within one year and 8.7% were readmitted for opioid overdose or dependence within that year. The most common primary diagnoses on the readmission record were infection, kidney failure, drug related admission, and psychiatric admission. Predictors of readmission were smoking, male sex, younger age, alcohol, bipolar disorder, non-opioid drug use, admission to teaching hospitals in metropolitan areas, and discharge against medical advice. Conclusion: There is a high all-cause readmission rate following index admission for opioid overdose or dependence and a greater likelihood of readmission among young males with psychiatric comorbidities in metropolitan areas. Targeted interventions to address psychiatric comorbidities and transitions of care may be needed for the high-risk opioid dependence and overdose population.

Associations Between the Specialty of Opioid Prescribers and Opioid Addiction, Misuse, and Overdose Outcomes

OBJECTIVE

To examine associations between opioid prescriber specialty and patient likelihood of opioid use disorder (OUD), opioid misuse, and opioid overdose.

DESIGN

Longitudinal retrospective study using Pennsylvania Medicaid data (2007-2015).

METHODS

We constructed an incident cohort of 432,110 enrollees initiating prescription opioid use without a history of OUD or overdose six months before opioid initiation. We attributed patients to one of 10 specialties using the first opioid prescriber's specialty or, alternatively, the specialty of the dominant prescriber writing the majority of the patient's opioid prescriptions. We estimated adjusted rates for OUD, misuse, and overdose, adjusting for demographic variables and medical (including pain) and psychiatric comorbidities.

RESULTS

The unadjusted incidence rates of OUD, misuse, and overdose were 7.13, 4.73, and 0.69 per 100,000 person-days, respectively. Patients initiating a new episode of opioid treatment with Pain Medicine/Anesthesiology (6.7 events, 95% confidence interval [CI] = 5.5 to 8.2) or Physical Medicine and Rehabilitation (PM&R; 6.1 events, 95% CI = 5.1 to 7.2) had higher adjusted rates for OUD per 100,000 person-days compared with Primary Care practitioners (PCPs; 4.4 events, 95% CI = 4.1 to 4.7). Patients with index prescriptions from Pain Medicine/Anesthesiology (15.9 events, 95% CI = 13.2 to 19.3) or PM&R (15.8 events, 95% CI = 13.5 to 18.4) had higher adjusted rates for misuse per 100,000 person-days compared with PCPs (9.6 events, 95% CI = 8.8 to 10.6). Findings were largely similar when patients were attributed to specialty based on dominant prescriber.

CONCLUSIONS

Differences in opioid-related risks by specialty of opioid prescriber may arise from differences in patient risk factors, provider behavior, or both. Our findings inform targeting of opioid risk mitigation strategies to specific practitioner specialties.

State Policies for Prescription Drug Monitoring Programs and Adverse Opioid-related Hospital Events

BACKGROUND

State policies to optimize prescriber use of Prescription Drug Monitoring Programs (PDMPs) have proliferated in recent years. Prominent policies include comprehensive mandates for prescriber use of PDMP, laws allowing delegation of PDMP access to office staff, and interstate PDMP data sharing. Evidence is limited regarding the effects of these policies on adverse opioid-related hospital events.

OBJECTIVE

The objective of this study was to assess the effects of 3 PDMP policies on adverse opioid-related hospital events among patients with prescription opioid use.

RESEARCH DESIGN

We examined 2011-2015 data from a large national commercial insurance database of privately insured and Medicare Advantage patients from 28 states with fully operating PDMPs by the end of 2010. We used a difference-in-differences framework to assess the probabilities of opioid-related hospital events and association with the implementation of PDMP policies. The analysis was conducted for adult patients with any prescription opioid use, a subsample of patients with long-term prescription opioid use, and stratified by older (65+) versus younger patients.

RESULTS

Comprehensive use mandates were associated with a relative reduction in the probability of opioid-related hospital events by 28% among patients with any opioid and 21% among patients with long-term opioid use. Such reduction was greater (in relative terms) among older patients despite the lower rate of these events among older than younger patients. Delegate laws and interstate data sharing were associated with limited change in the outcome.

CONCLUSION

Comprehensive PDMP use mandates were associated with meaningful reductions in opioid-related hospital events among privately insured and Medicare Advantage adults with prescription opioid use.

Using machine learning to predict risk of incident opioid use disorder among fee-for-service Medicare beneficiaries: A prognostic study

OBJECTIVE

To develop and validate a machine-learning algorithm to improve prediction of incident OUD diagnosis among Medicare beneficiaries with ≥1 opioid prescriptions.

METHODS

This prognostic study included 361,527 fee-for-service Medicare beneficiaries, without cancer, filling ≥1 opioid prescriptions from 2011-2016. We randomly divided beneficiaries into training, testing, and validation samples. We measured 269 potential predictors including socio-demographics, health status, patterns of opioid use, and provider-level and regional-level factors in 3-month periods, starting from three months before initiating opioids until development of OUD, loss of follow-up or end of 2016. The primary outcome was a recorded OUD diagnosis or initiating methadone or buprenorphine for OUD as proxy of incident OUD. We applied elastic net, random forests, gradient boosting machine, and deep neural network to predict OUD in the subsequent three months. We assessed prediction performance using C-statistics and other metrics (e.g., number needed to evaluate to identify an individual with OUD [NNE]). Beneficiaries were stratified into subgroups by risk-score decile.

RESULTS

The training (n = 120,474), testing (n = 120,556), and validation (n = 120,497) samples had similar characteristics (age ≥65 years = 81.1%; female = 61.3%; white = 83.5%; with disability eligibility = 25.5%; 1.5% had incident OUD). In the validation sample, the four approaches had similar prediction performances (C-statistic ranged from 0.874 to 0.882); elastic net required the fewest predictors (n = 48). Using the elastic net algorithm, individuals in the top decile of risk (15.8% [n = 19,047] of validation cohort) had a positive predictive value of 0.96%, negative predictive value of 99.7%, and NNE of 104. Nearly 70% of individuals with incident OUD were in the top two deciles (n = 37,078), having highest incident OUD (36 to 301 per 10,000 beneficiaries). Individuals in the bottom eight deciles (n = 83,419) had minimal incident OUD (3 to 28 per 10,000).

CONCLUSIONS

Machine-learning algorithms improve risk prediction and risk stratification of incident OUD in Medicare beneficiaries.

Adult opioid poisonings by drug, intent, and resource use from the United States National Poison Data System from 2005-2018

INTRODUCTION

Deaths due to an opioid overdose nearly doubled from 2013 to 2017. Our objective is to describe the trends in intent, healthcare resource use, and clinical outcomes among adults with opioid exposures.

MATERIALS AND METHODS

This study is a retrospective analysis of data from the 55 U.S. poison control centers. Adults, >19 years, with an opioid as the primary poisoning agent between 2005 and 2018 were included. These years were divided into three epochs (2005-2009, 2010-2014, and 2015-2018) to describe the trends in frequency, intent, severity, healthcare resource use, and regional differences in U.S. adults affected by prescription and illicit opioid exposures.

RESULTS

A total of 546,049 (54.4%) of the 1,002,947 opioid-related cases reported to the U.S. poison centers met inclusion criteria. The percentage of patients with a moderate/major clinical effect increased in each epoch (24.4, 29.13, and 35.3%) as did the proportion of patients with illicit opioids (coded as heroin) as their primary substance (2.89, 5.47, and 13.95%). Illicit opioid use was associated with increased frequency of moderate/major clinical effects (54.2 vs. 27.4%), need for an ICU procedure (11.4 vs. 6.8%), and death (3.9 vs. 1.2%) compared with prescription opioid use. Suicidal intent (34.88%) followed by misuse/abuse (26.26%) were the most frequent intents. Misuse/abuse increased in frequency over each epoch in the study period (23.1 vs. 26.12 vs. 30.3%). Discussion and conclusions: The severity of clinical effects and death following acute opioid poisonings increased over the study period, driven by suicidal intent and an increasing proportion of illicit opioid cases. This study highlights the importance of developing strategies to address suicide prevention in addition to the continued focus on opioid use disorder.

Incidence of Treatment for Opioid Use Disorder Following Nonfatal Overdose in Commercially Insured Patients

IMPORTANCE

Timely initiation and referral to treatment for patients with opioid use disorder seen in the emergency department is associated with reduced mortality. It is not known how often commercially insured adults obtain follow-up treatment after nonfatal opioid overdose.

OBJECTIVE

To investigate the incidence of follow-up treatment following emergency department discharge after nonfatal opioid overdose and patient characteristics associated with receipt of follow-up treatment.

DESIGN, SETTING, AND PARTICIPANTS

A retrospective cohort study was conducted using an administrative claims database for a large US commercial insurer, from October 1, 2011, to September 30, 2016. Data analysis was performed from May 1, 2019, to September 26, 2019. Adult patients discharged from the emergency department after an index opioid overdose (no overdose in the preceding 90 days) were included. Patients with cancer and without continuous insurance enrollment were excluded.

MAIN OUTCOMES AND MEASURES

The primary outcome was follow-up treatment in the 90 days following overdose, defined as a combined outcome of claims for treatment encounters or medications for opioid use disorder (buprenorphine and naltrexone). Analysis was stratified by whether patients received treatment for opioid use disorder in the 90 days before the overdose. Logistic regression models were used to identify patient characteristics associated with receipt of follow-up treatment. Marginal effects were used to report the average adjusted probability and absolute risk differences (ARDs) in follow-up for different patient characteristics.

RESULTS

A total of 6451 patients were identified with nonfatal opioid overdose; the mean (SD) age was 45.0 (19.3) years, 3267 were women (50.6%), and 4676 patients (72.5%) reported their race as non-Hispanic white. A total of 1069 patients (16.6%; 95% CI, 15.7%-17.5%) obtained follow-up treatment within 90 days after the overdose. In adjusted analysis of patients who did not receive treatment before the overdose, black patients were half as likely to obtain follow-up compared with non-Hispanic white patients (ARD, -5.9%; 95% CI, -8.6% to -3.6%). Women (ARD, -1.7%; 95% CI, -3.3% to -0.5%) and Hispanic patients (ARD, -3.5%; 95% CI, -6.1% to -0.9%) were also less likely to obtain follow-up. For each additional year of age, patients were 0.2% less likely to obtain follow-up (95% CI, -0.3% to -0.1%).

CONCLUSIONS AND RELEVANCE

Efforts to improve the low rate of timely follow-up treatment following opioid overdose may seek to address sex, race/ethnicity, and age disparities.

Measuring problem prescription opioid use among patients receiving long-term opioid analgesic treatment: development and evaluation of an algorithm for use in EHR and claims data

Objective

Opioid surveillance in response to the opioid epidemic will benefit from scalable, automated algorithms for identifying patients with clinically documented signs of problem prescription opioid use. Existing algorithms lack accuracy. We sought to develop a high-sensitivity, high-specificity classification algorithm based on widely available structured health data to identify patients receiving chronic extended-release/long-acting (ER/LA) therapy with evidence of problem use to support subsequent epidemiologic investigations.

Methods

Outpatient medical records of a probability sample of 2,000 Kaiser Permanente Washington patients receiving ≥60 days’ supply of ER/LA opioids in a 90-day period from 1 January 2006 to 30 June 2015 were manually reviewed to determine the presence of clinically documented signs of problem use and used as a reference standard for algorithm development. Using 1,400 patients as training data, we constructed candidate predictors from demographic, enrollment, encounter, diagnosis, procedure, and medication data extracted from medical claims records or the equivalent from electronic health record (EHR) systems, and we used adaptive least absolute shrinkage and selection operator (LASSO) regression to develop a model. We evaluated this model in a comparable 600-patient validation set. We compared this model to ICD-9 diagnostic codes for opioid abuse, dependence, and poisoning. This study was registered with ClinicalTrials.gov as study NCT02667262 on 28 January 2016.

Results

We operationalized 1,126 potential predictors characterizing patient demographics, procedures, diagnoses, timing, dose, and location of medication dispensing. The final model incorporating 53 predictors had a sensitivity of 0.582 at positive predictive value (PPV) of 0.572. ICD-9 codes for opioid abuse, dependence, and poisoning had a sensitivity of 0.390 at PPV of 0.599 in the same cohort.

Conclusions

Scalable methods using widely available structured EHR/claims data to accurately identify problem opioid use among patients receiving long-term ER/LA therapy were unsuccessful. This approach may be useful for identifying patients needing clinical evaluation.

Eye-Related Emergency Department Visits and The Opioid Epidemic: a 10-Year Analysis

PURPOSE

To describe the epidemiology of Emergency Department (ED) visits related to opioid abuse with primary ophthalmic diagnoses in the United States (US).

METHODS

This retrospective cross-sectional study used National ED Sample (NEDS) (2006-2015), a representative sample of all US EDs, to analyze and compare the epidemiology of primary ophthalmic diagnoses in opioid abusers and a control group of non-opioid users. National incidence and descriptive statistics were calculated for demographics and prevalent diagnoses. Multivariable logistic regression was used to compare outcomes between primary ophthalmic diagnoses in opioid and non-opioid abusers.

RESULTS

An estimated 10,617 visits had a primary ophthalmic diagnosis and an accompanying opioid abuse diagnosis, and the incidence increased from 0.2 in 2006 to 0.6 per 100,000 US population in 2015. Opioid abuse group had more adults (6,747:63.5%) and middle-aged (3,361:31.7%) patients, while in controls adults (7,905,003:40.4%) and children (4,068,534:20.8%) were affected more. Leading etiologies were similar: traumatic and infectious etiologies were most common; however, opioid abuse patients had more severe ophthalmic diagnoses such as orbital fractures (8.4%), orbital cellulitis (7.4%), globe injury (3.4%) and endophthalmitis (3.2%) compared to controls. Patients in the opioid abuse group were also more likely to be admitted (adjusted Odds Ratio [aOR], 28.38 [95% CI, 24.50-32.87]).

CONCLUSIONS

In the era of opioid crisis, an increase in ED visits with ophthalmic complaints is seen, with increasing direct and indirect costs on the healthcare system. More research is needed to establish causality and devise strategies to lower this burden.

ICD-10-CM-Based Definitions for Emergency Department Opioid Poisoning Surveillance: Electronic Health Record Case Confirmation Study

OBJECTIVES

Valid opioid poisoning morbidity definitions are essential to the accuracy of national surveillance. The goal of our study was to estimate the positive predictive value (PPV) of case definitions identifying emergency department (ED) visits for heroin or other opioid poisonings, using billing records with International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) codes.

METHODS

We examined billing records for ED visits from 4 health care networks (12 EDs) from October 2015 through December 2016. We conducted medical record reviews of representative samples to estimate the PPVs and 95% confidence intervals (CIs) of (1) first-listed heroin poisoning diagnoses (n = 398), (2) secondary heroin poisoning diagnoses (n = 102), (3) first-listed other opioid poisoning diagnoses (n = 452), and (4) secondary other opioid poisoning diagnoses (n = 103).

RESULTS

First-listed heroin poisoning diagnoses had an estimated PPV of 93.2% (95% CI, 90.0%-96.3%), higher than secondary heroin poisoning diagnoses (76.5%; 95% CI, 68.1%-84.8%). Among other opioid poisoning diagnoses, the estimated PPV was 79.4% (95% CI, 75.7%-83.1%) for first-listed diagnoses and 67.0% (95% CI, 57.8%-76.2%) for secondary diagnoses. Naloxone was administered in 867 of 1055 (82.2%) cases; 254 patients received multiple doses. One-third of all patients had a previous drug poisoning. Drug testing was ordered in only 354 cases.

CONCLUSIONS

The study findings suggest that heroin or other opioid poisoning surveillance definitions that include multiple diagnoses (first-listed and secondary) would identify a high percentage of true-positive cases.

Association of Opioid Prescribing Patterns With Prescription Opioid Overdose in Adolescents and Young Adults

IMPORTANCE

Safe opioid prescribing practices are critical to mitigate the risk of prescription opioid overdose in adolescents and young adults. However, studies that examine opioid prescribing patterns associated with prescription opioid overdose have mostly focused on older adults. The generalizability of these studies to adolescents and young adults is unclear.

OBJECTIVE

To identify opioid prescribing patterns associated with prescription opioid overdose in adolescents and young adults.

DESIGN, SETTING, AND PARTICIPANTS

This retrospective cohort study assessed privately insured patients aged 12 to 21 years with opioid prescription claims in the IBM MarketScan Commercial Claims and Encounters database between July 1, 2009, and October 1, 2017, and no cancer diagnosis. Data analysis was performed from January 1 to April 30, 2019.

MAIN OUTCOMES AND MEASURES

The outcome was a treated opioid overdose as indicated by diagnosis codes. On the basis of days supplied, opioid prescription claims were converted to person-days (the unit of analysis) on which opioid exposure would occur if patients took medications as prescribed. Logistic regression with clustered SEs at the patient level was used to model the occurrence of overdose on a person-day as a function of daily opioid dosage category (<30, 30-59, 60-89, 90-119, or ≥120 morphine milligram equivalents), concurrent benzodiazepine use, and extended-release or long-acting opioid use. Regressions controlled for demographic characteristics, year, opioid use within 180 days, and comorbidities (mental health disorder, substance use disorder, and other chronic condition).

RESULTS

A total of 2 752 612 patients (mean [SD] age at cohort entry, 17.2 [2.5] years; 1 451 918 [52.8%] female) participated in the study. Patients had 4 686 355 opioid prescription claims, corresponding to 21 605 444 person-days. Overdose occurred on 255 person-days among 249 patients (0.01% of the sample). Each increase in daily opioid dosage category was associated with higher overdose risk (adjusted odds ratio [AOR], 1.18; 95% CI, 1.05-1.31). Compared with no use, both concurrent benzodiazepine use (AOR, 1.83; 95% CI, 1.24-2.71) and extended-release or long-acting opioid use (AOR, 2.01; 95% CI, 1.16-3.46) were associated with increased overdose risk.

CONCLUSIONS AND RELEVANCE

The findings suggest that when prescribing opioids to adolescents and young adults, practitioners could potentially mitigate overdose risk by using the lowest effective daily dosage, avoiding concurrent opioid and benzodiazepine prescribing, and relying on short-acting opioids. Findings are broadly consistent with prior opioid safety studies focused on older adults.

Incidence and predictors of drug overdoses among a cohort of >10,000 patients treated for substance use disorder

BACKGROUND

Drug overdoses remain a significant public health burden throughout the world. This study assessed the incidence and predictors of non-fatal and fatal drug overdoses among patients with an opioid use, treated for drug use disorders (DUD) at public treatment centers in Denmark.

METHODS

A consecutive cohort of patients (n = 11,199) were tracked from date of first registered enrollment between the year 2000 and 2010 to first registered drug overdose, death or December 31st 2010, whichever occurred first. Competing-risks regression models were fitted to estimate the sub hazard ratios (SHRs) of non-fatal and fatal drug overdoses and confounding risk factors.

RESULTS

A total of 3186 (28%) patients experienced a non-fatal drug overdose during follow-up, and 572 (6%) died from an overdose. Use of benzodiazepines (SHR: 1.15 95% CI 1.03, 1.28) was significantly associated with non-fatal overdose. Intravenous drug use and previous hospitalization for a non-fatal overdose increased the risk of later non-fatal (SHR: 1.57 95% CI 1.42, 1.73) and fatal overdoses (SHR: 1.43 95% CI 1.12, 1.82).

CONCLUSIONS

Patients who use opioids remain at risk of overdoses for a long time after discharge from drug treatment. Besides relevant monitoring and psychosocial support in opioid maintenance treatment, there is a need for informing and educating opioid users in risk factors and preventive measures in settings where they are often difficult to access for traditional treatment services.

Predictors of Overdose Death Among High-Risk Emergency Department Patients With Substance-Related Encounters: A Data Linkage Cohort Study

STUDY OBJECTIVE

Persons with substance use disorders frequently utilize emergency department (ED) services, creating an opportunity for intervention and referral to addiction treatment and harm-reduction services. However, EDs may not have the appropriate tools to distinguish which patients are at greatest risk for negative outcomes. We link hospital ED and medical examiner mortality databases in one state to identify individual-level risk factors associated with overdose death among ED patients with substance-related encounters.

METHODS

This retrospective cohort study linked Maryland statewide ED hospital claims records for adults with nonfatal overdose or substance use disorder encounters in 2014 to 2015 with medical examiner mortality records in 2015 to 2016. Logistic regression was used to identify factors in hospital records associated with risk of opioid overdose death. Predicted probabilities for overdose death were calculated for hypothetical patients with different combinations of overdose and substance use diagnostic histories.

RESULTS

A total of 139,252 patients had substance-related ED encounters in 2014 to 2015. Of these patients, 963 later experienced an opioid overdose death, indicating a case fatality rate of 69.2 per 10,000 patients, 6 times higher than that of patients who used the ED for any cause. Factors most strongly associated with death included having both an opioid and another substance use disorder (adjusted odds ratio 2.88; 95% confidence interval 2.04 to 4.07), having greater than or equal to 3 previous nonfatal overdoses (adjusted odds ratio 2.89; 95% confidence interval 1.54 to 5.43), and having a previous nonfatal overdose involving heroin (adjusted odds ratio 2.24; 95% confidence interval 1.64 to 3.05).

CONCLUSION

These results highlight important differences in overdose risk among patients receiving care in EDs for substance-related conditions. The findings demonstrate the potential utility of incorporating routine data from patient records to assess risk of future negative outcomes and identify primary targets for initiation and linkage to lifesaving care.