Opioid-Related Emergency Department Encounters: Patient, Encounter, and Community Characteristics Associated With Repeated Encounters

Balio, Casey P.; Wiley, Kevin; Greene, Marion; Vest, Joshua R.

doi:10.1016/j.annemergmed.2019.12.005

Cited by 8 publications

(9 citation statements)

References 9 publications

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“…In this context, the first strength of our study is the use of an extensive nationwide insurance claims database that contains all ED and prescription records in Korea. In addition, considering the importance of ED visits as a surveillance method for opioid-related harm in other countries [ 41 , 42 ], this study could confirm the possibility of using ED data to monitor opioid-related events in Korea by identifying the association between NIOA use and ED visits.…”

Section: Discussionmentioning

confidence: 75%

Risk Factors for Emergency Department Presentations after the Initiation of Opioid Analgesics in Non-Cancer Patients in Korea: A Nationwide Study

et al. 2023

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Background and Objectives: Opioid use in Korea is lower than in other developed countries. However, recent studies have reported an increase in opioid prescriptions and the number of chronic opioid users. The current status of adverse events (AEs) associated with opioid analgesics in Korea is unclear. This nested case–control study aimed to evaluate the influence of opioid analgesic use patterns on all emergency department (ED) visits and opioid-related ED visits after opioid analgesic initiation using the national claims database. Materials and Methods: Adult non-cancer patients who initiated non-injectable opioid analgesics (NIOA) between January 2017 and June 2018 were included. We defined the case group as patients who visited the ED within six months of opioid initiation, and the control group was selected in a 1:1 ratio using an exact matching method. Results: A total of 97,735 patients (13.58%) visited the ED within six months of NIOA initiation. Nearly 32% of cases were linked to opioid-related AEs. The most frequent AEs were falls and fractures (61.27%). After adjusting for covariates, opioid initiation at the ED was associated with all-cause or opioid-related ED visits (adjusted odds ratio (aOR) = 3.19, 95% confidence interval (CI) = 3.09–3.29; aOR = 3.82, 95% CI = 3.62–4.04, respectively). Chronic NIOA use was associated with all-cause and opioid-related ED visits (aOR = 1.32, 95% CI = 1.23–1.40; aOR = 1.56, 95% CI = 1.39–1.76, respectively). Conclusion: This study found that 13% of non-cancer patients visited the ED within six months of NIOA initiation. In addition, the NIOA use pattern was significantly associated with all-cause and opioid-related ED visits.

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Section: Discussionmentioning

confidence: 75%

Risk Factors for Emergency Department Presentations after the Initiation of Opioid Analgesics in Non-Cancer Patients in Korea: A Nationwide Study

et al. 2023

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“…There were approximately 50,000 opioid overdose deaths reported in 2019, and the recent COVID-19 pandemic has seen increases in opioid-related deaths [ 2 , 3 ]. Patients with opioid misuse disproportionately utilize emergency medical services, with almost 1.5 million opioid-related emergency department (ED) encounters annually [ 4 , 5 , 6 ]. ED patients have been found to have more severe substance use patterns compared with patients seen in the primary care setting [ 7 ].…”

Section: Introductionmentioning

confidence: 99%

The Identification of Subphenotypes and Associations with Health Outcomes in Patients with Opioid-Related Emergency Department Encounters Using Latent Class Analysis

Chhabra

Smith

Maloney

et al. 2022

IJERPH

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The emergency department (ED) is a critical setting for the treatment of patients with opioid misuse. Detecting relevant clinical profiles allows for tailored treatment approaches. We sought to identify and characterize subphenotypes of ED patients with opioid-related encounters. A latent class analysis was conducted using 14,057,302 opioid-related encounters from 2016 through 2017 using the National Emergency Department Sample (NEDS), the largest all-payer ED database in the United States. The optimal model was determined by face validity and information criteria-based metrics. A three-step approach assessed class structure, assigned individuals to classes, and examined characteristics between classes. Class associations were determined for hospitalization, in-hospital death, and ED charges. The final five-class model consisted of the following subphenotypes: Chronic pain (class 1); Alcohol use (class 2); Depression and pain (class 3); Psychosis, liver disease, and polysubstance use (class 4); and Pregnancy (class 5). Using class 1 as the reference, the greatest odds for hospitalization occurred in classes 3 and 4 (Ors 5.24 and 5.33, p < 0.001) and for in-hospital death in class 4 (OR 3.44, p < 0.001). Median ED charges ranged from USD 2177 (class 1) to USD 2881 (class 4). These subphenotypes provide a basis for examining patient-tailored approaches for this patient population.

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“…Emergency departments (EDs) are often at the forefront of this opioid epidemic, treating individuals who present with overdose, secondary complications, requests for treatment, or unrelated acute care needs 2 – 4 . Yet, despite the well-recognized importance of the ED in caring for patients with opioid-related illness, significant knowledge gaps exist concerning the current characteristics and typology, or phenotypes, of opioid-related presentations within EDs, their interrelationships, and associated outcomes 5 …”

Section: Introductionmentioning

confidence: 99%

“…[2][3][4] Yet, despite the well-recognized importance of the ED in caring for patients with opioid-related illness, significant knowledge gaps exist concerning the current characteristics and typology, or phenotypes, of opioid-related presentations within EDs, their interrelationships, and associated outcomes. 5 Routine screening for opioid-related disease is rare in EDs and current methods to identify patients or visits have proven inadequate as combinations of International Classification of Disease (ICD) codes lack the desired sensitivity and/or specificity for further use. [6][7][8] Development of computable opioid-related phenotypes within electronic health records (EHR) is a promising method to address these gaps, particularly based on EHR data commonly acquired within the ED setting.…”

Section: Introductionmentioning

confidence: 99%

Identifying Opioid-Related Electronic Health Record Phenotypes for Emergency Care Research and Surveillance: An Expert Consensus Driven Concept Mapping Process

et al. 2022

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Background: Case identification for many areas of opioid research and surveillance in the emergency department (ED) is challenging as patients are often undifferentiated with nonspecific symptoms and diagnostic codes have proven to be inaccurate. Opioid-related phenotypes based on combinations of electronic health record data are a promising method to address this gap but lack a consensus-based conceptual framework to aid organization and prioritization. Methods: To achieve consensus around opioid-related phenotype topics in the ED, we used a hybrid scheme that employed modified Delphi and conceptual mapping methods. The combined iterative process used three rounds of electronic meetings and questionnaires to generate consensus recommendations and concept mappings based on the opinions and feedback of the 9 member Delphi panel. Mean importance and feasibility scores based on 5-point Likert scales (1 = relatively unimportant (infeasible) to 5 = extremely important (feasible)) for each statement/phenotype were calculated. We used multidimensional scaling to produce a point map of the phenotype concepts and hierarchical cluster analysis to generate concept maps. Results: After the first round, 120 initial phenotype concepts were proposed which were reduced to 73 concepts after normalization by the research team. Opioid overdose (9.54, SD = 0.9) had the highest combined importance and feasibility score. A final labeled 12-cluster solution was determined to be the most parsimonious description of the content by the research team. Three key groups emerged: opioid overdose, other opioid-specific phenotypes (opioid use disorder, opioid misuse, and opioid withdrawal) with significant concept overlap and opioid use-related phenotypes (homelessness, falls, infections, and suicidality). Conclusions: Using an expert consensus driven concept mapping process we identified specific opioid phenotype concepts within an overlapping schema that carry high priority for development and validation to advance emergency care opioid-related research and surveillance.

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Opioid-Related Emergency Department Encounters: Patient, Encounter, and Community Characteristics Associated With Repeated Encounters

Cited by 8 publications

References 9 publications

Risk Factors for Emergency Department Presentations after the Initiation of Opioid Analgesics in Non-Cancer Patients in Korea: A Nationwide Study

Risk Factors for Emergency Department Presentations after the Initiation of Opioid Analgesics in Non-Cancer Patients in Korea: A Nationwide Study

The Identification of Subphenotypes and Associations with Health Outcomes in Patients with Opioid-Related Emergency Department Encounters Using Latent Class Analysis

Identifying Opioid-Related Electronic Health Record Phenotypes for Emergency Care Research and Surveillance: An Expert Consensus Driven Concept Mapping Process

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