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

Wastewater Surveillance for Xylazine in Kentucky

Introduction

In the U.S., xylazine, the veterinary non-opioid sedative, has emerged as a major threat to people who use illicitly manufactured fentanyl and other drugs. The aim of this study was to compare wastewater detection of xylazine with other public health and safety surveillance data from 2019 to 2023 in Kentucky.

Methods

Wastewater samples from 5 rest areas, 2 truck weigh stations, and 4 wastewater treatment plants were tested for xylazine. Wastewater xylazine positivity rates were compared with xylazine-positive submission rates from the National Forensic Laboratory Information System and Kentucky's fatal overdoses in 6-month periods (Period 1=January-June; Period 2=July-December).

Results

Xylazine was detected in 61.6% (424 of 688) of daily wastewater samples from roadway sites/wastewater treatment plants. For roadways, detection increased from 55% (Period 1, 2021) to 94% (Period 1, 2023), and wastewater treatment plants had an overall detection of 25.8% (n=66 samples, Periods 1 and 2, 2022). Increasing roadway positivity corresponded to trends in National Forensic Laboratory Information System xylazine-positive submission rates: from 0.19 per 1,000 submissions (Period 1, 2019) to 2.9 per 1,000 (Period 2, 2022, latest available). No deaths from xylazine were reported publicly in Kentucky, although this study's authors identified 1-4 deaths (true count suppressed) in the overdose surveillance system, which, in back-of-the-envelope comparisons with other states, is far fewer than expected.

Conclusions

Wastewater signals indicate broad geographic exposure to xylazine in Kentucky, yet health outcomes data suggest otherwise. These findings may inform regional, national, and international efforts to incorporate wastewater-based drug surveillance. Harm-reduction activities along roadways and other suitable locations may be needed.

Association of medications for opioid use disorder with reduced risk of repeat opioid overdose in Medicaid: A cohort study

INTRODUCTION

Following a nonfatal opioid overdose, patients are at high risk for repeat overdose. The objective of this study was to examine the association of MOUD after nonfatal opioid overdose with risk of repeat overdose in the following year.

METHODS

This retrospective cohort study analyzed Missouri Medicaid claims from July 2012 to December 2021. The study identified opioid overdoses occurring between 2013 and 2020 using diagnosis codes for opioid poisoning in an inpatient or emergency department setting. The study implemented Cox models with a time-varying covariate for post-overdose receipt of MOUD.

RESULTS

During the study period, MOUD receipt after overdose more than tripled, from 4.8 % to 18.9 %. Overall, only 12.1 % of patients received MOUD in the year after index. MOUD during follow-up was associated with significantly lower risk of repeat overdose (HR = 0.34, 95 % CI = 0.14-0.82). Out of 3017 individuals meeting inclusion criteria, 13.6 % had a repeat opioid overdose within 1 year. Repeat overdose risk was higher for those whose index overdose involved heroin or synthetic opioids (HR = 1.71, 95 % CI = 1.35-2.15), but MOUD was associated with significantly reduced risk in this group (HR = 0.34, 95 % CI = 0.13-0.92).

CONCLUSIONS

MOUD receipt was associated with reduced risk of repeat overdose. Those whose index overdoses involved heroin or synthetic opioids were at greater risk of repeat overdose, but MOUD was associated with reduced risk in this group.

Promotion of training course on ICD-10 Poisoning coding : necessity to adopt preventive strategies

BACKGROUND

Poisoning is considered the most common cause of referral to emergency departments and hospitalization in the intensive care unit (ICU). Training or retraining of coders and ensuring the positive impact of these trainings in assigning accurate codes to poisoning cases is necessary to adopt practical health measures for optimal management of this disease. The present study aimed to evaluate the impact of holding a training course on poisoning coding rules based on ICD-10 in clinical coders.

METHODS

This study is descriptive and analytical. With the target population included the coders of hospitals affiliated with Shahid Beheshti University of Medical Sciences (N = 45). In order to evaluate the training course on poisoning coding rules, the Conex Input Process Product (CIPP) evaluation model was used. This model was the first goal-oriented approach evaluation model. According to the CIPP model, evaluation of the training course held in four components, including Context factors (course objectives and priority of objectives), Input factors (instructor, curriculum, facilities, equipment, and training location), Process factors (teaching process, learning, management, and support), and Product factors (feedback, knowledge, and skills). A researcher-made questionnaire containing 39 questions with a 5-point Likert scale was used to collect data. The validity of the questionnaire was calculated through content validity, and its reliability was calculated using Cronbach's alpha coefficient (alpha = 90% in all components). In order to analyze the data, descriptive statistics (frequency percentage distribution) and inferential statistics (one-sample t-test) were used.

RESULTS

The findings of this study were presented in four components of context, input, process, and product evaluation. The average criterion for all questions in the questionnaire was considered 3. As a result, the significance level obtained from the one sample t-test was equal to P = 0. 0001.The training course had a favorable effect in terms of context, input, process and products.

CONCLUSION

The knowledge and skills of clinical coders can be enhanced by updating medical knowledge, holding training courses, workshops, seminars, and conducting clinical coder accreditation. Extensive and continuous training for clinical coders is essential due to the impact of code quality on financial forecasting, electronic health records, and conducting research.

The effectiveness of a noninterruptive alert to increase prescription of take-home naloxone in emergency departments

OBJECTIVE

Opioid-related overdose (OD) deaths continue to increase. Take-home naloxone (THN), after treatment for an OD in an emergency department (ED), is a recommended but under-utilized practice. To promote THN prescription, we developed a noninterruptive decision support intervention that combined a detailed OD documentation template with a reminder to use the template that is automatically inserted into a provider's note by decision rules. We studied the impact of the combined intervention on THN prescribing in a longitudinal observational study.

METHODS

ED encounters involving an OD were reviewed before and after implementation of the reminder embedded in the physicians' note to use an advanced OD documentation template for changes in: (1) use of the template and (2) prescription of THN. Chi square tests and interrupted time series analyses were used to assess the impact. Usability and satisfaction were measured using the System Usability Scale (SUS) and the Net Promoter Score.

RESULTS

In 736 OD cases defined by International Classification of Disease version 10 diagnosis codes (247 prereminder and 489 postreminder), the documentation template was used in 0.0% and 21.3%, respectively (P < .0001). The sensitivity and specificity of the reminder for OD cases were 95.9% and 99.8%, respectively. Use of the documentation template led to twice the rate of prescribing of THN (25.7% vs 50.0%, P < .001). Of 19 providers responding to the survey, 74% of SUS responses were in the good-to-excellent range and 53% of providers were Net Promoters.

CONCLUSIONS

A noninterruptive decision support intervention was associated with higher THN prescribing in a pre-post study across a multiinstitution health system.

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.

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.

Long-term Risk of Overdose or Mental Health Crisis After Opioid Dose Tapering

IMPORTANCE

Patients prescribed long-term opioid therapy are increasingly undergoing dose tapering. Recent studies suggest that tapering is associated with short-term risks of substance misuse, overdose, and mental health crisis, although lower opioid dose could reduce risks of adverse events over the longer term.

OBJECTIVE

To assess the longer-term risks of overdose or mental health crisis associated with opioid dose tapering.

DESIGN, SETTING, AND PARTICIPANTS

This is a cohort study using an exposure-crossover analysis. Data were obtained from the OptumLabs Data Warehouse, which includes deidentified medical and pharmacy claims and enrollment records for commercial insurance and Medicare Advantage enrollees, representing a diverse mixture of ages, races, ethnicities, and geographical regions across the US. Participants were US adults who underwent opioid dose tapering from 2008 to 2017 after a 12-month baseline period of stable daily dosing of 50 morphine milligram equivalents or higher and who had at least 1 month of long-term follow-up during a postinduction period beginning 12 months after taper initiation. Data analysis was performed from October 2021 to April 2022.

EXPOSURES

Opioid tapering, defined as 15% or more relative reduction in mean daily dose during any of 6 overlapping 60-day windows within a 7-month follow-up period after the stable baseline period.

MAIN OUTCOMES AND MEASURES

Emergency or hospital encounters for drug overdose or withdrawal and mental health crisis (depression, anxiety, or suicide attempt). Outcome counts were assessed in pretaper and postinduction periods (from 12 to 24 months after taper initiation).

RESULTS

The study included 21 515 tapering events among 19 377 patients with a mean (SD) of 9.1 (2.7) months of postinduction follow-up per event (median [IQR], 10 [8-11] months). Patients had a mean (SD) age of 56.9 (11.2) years, 11 581 (53.8%) were female, and 8217 (38.2%) had commercial insurance (vs Medicare Advantage). In conditional negative binomial regression analyses, adjusted incidence rate ratios for the postinduction period compared with the pretaper period were 1.57 (95% CI, 1.42-1.74) for overdose or withdrawal and 1.52 (95% CI, 1.35-1.71) for mental health crisis.

CONCLUSIONS AND RELEVANCE

These findings suggest that opioid tapering was associated with increased rates of overdose, withdrawal, and mental health crisis extending up to 2 years after taper initiation.

Opioid overdose survivors: Medications for opioid use disorder and risk of repeat overdose in Medicaid patients

BACKGROUND

Patients with medically-treated opioid overdose are at high risk for subsequent adverse outcomes, including repeat overdose. Understanding factors associated with repeat overdose can aid in optimizing post-overdose interventions.

METHODS

We conducted a longitudinal, retrospective cohort study using NJ Medicaid data from 2014 to 2019. Medicaid beneficiaries aged 12-64 with an index opioid overdose from 2015 to 2018 were followed for one year for subsequent overdose. Exposures included patient demographics; co-occurring medical, mental health, and substance use disorders; service and medication use in the 180 days preceding the index overdose; and MOUD following index overdose.

RESULTS

Of 4898 individuals meeting inclusion criteria, 19.6% had repeat opioid overdoses within one year. Index overdoses involving heroin/synthetic opioids were associated with higher repeat overdose risk than those involving prescription/other opioids only (HR = 1.44, 95% CI = 1.22-1.71). Risk was higher for males and those with baseline opioid use disorder diagnosis or ED visits. Only 21.7% received MOUD at any point in the year following overdose. MOUD was associated with a large decrease in repeat overdose risk among those with index overdose involving heroin/synthetic opioids (HR = 0.30, 95% CI = 0.20-0.46). Among those receiving MOUD at any point in follow-up, 10.5% (112/1065) experienced repeat overdose versus 22.1% (848/3833) for those without MOUD.

CONCLUSIONS

Repeat overdose was common among individuals with medically-treated opioid overdose. Risk factors for repeat overdose varied by type of opioid involved in index overdose, with differential implications for intervention. MOUD following index opioid overdose involving heroin/synthetic opioids was associated with reduced repeat overdose risk.

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

OBJECTIVES

We assessed the differences between the first version of the Centers for Disease Control and Prevention (CDC) opioid surveillance definition for suspected nonfatal opioid overdoses (hereinafter, CDC definition) and the North Carolina Disease Event Tracking and Epidemiologic Collection Tool (NC DETECT) surveillance definition to determine whether the North Carolina definition should include additional International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) codes and/or chief complaint keywords.

METHODS

Two independent reviewers retrospectively reviewed data on North Carolina emergency department (ED) visits generated by components of the CDC definition not included in the NC DETECT definition from January 1 through July 31, 2018. Clinical reviewers identified false positives as any ED visit in which available evidence supported an alternative explanation for patient presentation deemed more likely than an opioid overdose. After individual assessment, reviewers reconciled disagreements.

RESULTS

We identified 2296 ED visits under the CDC definition that were not identified under the NC DETECT definition during the study period. False-positive rates ranged from 2.6% to 41.4% for codes and keywords uniquely identifying ≥10 ED visits. Based on uniquely identifying ≥10 ED visits and a false-positive rate ≤10.0%, 4 of 16 ICD-10-CM codes evaluated were identified for NC DETECT definition inclusion. Only 2 of 25 keywords evaluated, "OD" and "overdose," met inclusion criteria to be considered a meaningful addition to the NC DETECT definition.

PRACTICE IMPLICATIONS

Quantitative and qualitative trends in coding and keyword use identified in this analysis may prove helpful for future evaluations of surveillance definitions.

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 of Dose Tapering With Overdose or Mental Health Crisis Among Patients Prescribed Long-term Opioids

Importance

Opioid-related mortality and national prescribing guidelines have led to tapering of doses among patients prescribed long-term opioid therapy for chronic pain. There is limited information about risks related to tapering, including overdose and mental health crisis.

Objective

To assess whether there are associations between opioid dose tapering and rates of overdose and mental health crisis among patients prescribed stable, long-term, higher-dose opioids.

Design, Setting, and Participants

Retrospective cohort study using deidentified medical and pharmacy claims and enrollment data from the OptumLabs Data Warehouse from 2008 to 2019. Adults in the US prescribed stable higher doses (mean ≥50 morphine milligram equivalents/d) of opioids for a 12-month baseline period with at least 2 months of follow-up were eligible for inclusion.

Exposures

Opioid tapering, defined as at least 15% relative reduction in mean daily dose during any of 6 overlapping 60-day windows within a 7-month follow-up period. Maximum monthly dose reduction velocity was computed during the same period.

Main Outcomes and Measures

Emergency or hospital encounters for (1) drug overdose or withdrawal and (2) mental health crisis (depression, anxiety, suicide attempt) during up to 12 months of follow-up. Discrete time negative binomial regression models estimated adjusted incidence rate ratios (aIRRs) of outcomes as a function of tapering (vs no tapering) and dose reduction velocity.

Results

The final cohort included 113 618 patients after 203 920 stable baseline periods. Among the patients who underwent dose tapering, 54.3% were women (vs 53.2% among those who did not undergo dose tapering), the mean age was 57.7 years (vs 58.3 years), and 38.8% were commercially insured (vs 41.9%). Posttapering patient periods were associated with an adjusted incidence rate of 9.3 overdose events per 100 person-years compared with 5.5 events per 100 person-years in nontapered periods (adjusted incidence rate difference, 3.8 per 100 person-years [95% CI, 3.0-4.6]; aIRR, 1.68 [95% CI, 1.53-1.85]). Tapering was associated with an adjusted incidence rate of 7.6 mental health crisis events per 100 person-years compared with 3.3 events per 100 person-years among nontapered periods (adjusted incidence rate difference, 4.3 per 100 person-years [95% CI, 3.2-5.3]; aIRR, 2.28 [95% CI, 1.96-2.65]). Increasing maximum monthly dose reduction velocity by 10% was associated with an aIRR of 1.09 for overdose (95% CI, 1.07-1.11) and of 1.18 for mental health crisis (95% CI, 1.14-1.21).

Conclusions and Relevance

Among patients prescribed stable, long-term, higher-dose opioid therapy, tapering events were significantly associated with increased risk of overdose and mental health crisis. Although these findings raise questions about potential harms of tapering, interpretation is limited by the observational study design.

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.

Descriptive exploration of overdose codes in hospital and emergency department discharge data to inform development of drug overdose morbidity surveillance indicator definitions in ICD-10-CM

Background

In October 2015, discharge data coding in the USA shifted to the International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM), necessitating new indicator definitions for drug overdose morbidity. Amid the drug overdose crisis, characterising discharge records that have ICD-10-CM drug overdose codes can inform the development of standardised drug overdose morbidity indicator definitions for epidemiological surveillance.

Methods

Eight states submitted aggregated data involving hospital and emergency department (ED) discharge records with ICD-10-CM codes starting with T36–T50, for visits occurring from October 2015 to December 2016. Frequencies were calculated for (1) the position within the diagnosis billing fields where the drug overdose code occurred; (2) primary diagnosis code grouped by ICD-10-CM chapter; (3) encounter types; and (4) intents, underdosing and adverse effects.

Results

Among all records with a drug overdose code, the primary diagnosis field captured 70.6% of hospitalisations (median=69.5%, range=66.2%–76.8%) and 79.9% of ED visits (median=80.7%; range=69.8%–88.0%) on average across participating states. The most frequent primary diagnosis chapters included injury and mental disorder chapters. Among visits with codes for drug overdose initial encounters, subsequent encounters and sequelae, on average 94.6% of hospitalisation records (median=98.3%; range=68.8%–98.8%) and 95.5% of ED records (median=99.5%; range=79.2%–99.8%), represented initial encounters. Among records with drug overdose of any intent, adverse effect and underdosing codes, adverse effects comprised an average of 74.9% of hospitalisation records (median=76.3%; range=57.6%–81.1%) and 50.8% of ED records (median=48.9%; range=42.3%–66.8%), while unintentional intent comprised an average of 11.1% of hospitalisation records (median=11.0%; range=8.3%–14.5%) and 28.2% of ED records (median=25.6%; range=20.8%–40.7%).

Conclusion

Results highlight considerations for adapting and standardising drug overdose indicator definitions in ICD-10-CM.