ArticleJournal of general internal medicine2021
Predicting Mortality Risk After a Hospital or Emergency Department Visit for Nonfatal Opioid Overdose.
Article in Journal of general internal medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 13 citations in OpenAlex.
- Timely Receipt of New Medication Treatment After Acute Care Encounters for Opioid Overdose in the U.S. Medicaid Population.Journal of general internal medicine · 2026Article
- Leveraging the 72-Hour Rule Change to Support Transition From Hospital to Opioid Treatment Program.JAMA network open · 2025Article
- Integrating multiple data sources to predict all-cause readmission or mortality in patients with substance misuse.PLOS digital health · 2025Article
- Identifying emergency department patients at high risk for opioid overdose using natural language processing and machine learning.Journal of substance use and addiction treatment · 2025Article
- Evaluating the predictive performance of different data sources to forecast overdose deaths at the neighborhood level with machine learning in Rhode Island.Preventive medicine · 2025Article
- A systematic review of machine learning applications in predicting opioid associated adverse events.NPJ digital medicine · 2025Article
- Rates of buprenorphine prescribing and racial disparities among patients with opioid overdose.Drug and alcohol dependence reports · 2024Article
- Overdose and mortality risk following a non-fatal opioid overdose treated by Emergency Medical Services in King County, Washington.Drug and alcohol dependence · 2023Article
- Opportunities for opioid overdose prediction: building a population health approach.The Lancet. Digital health · 2022Article
Corrections and comments
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Authors and funding
11 authors at 4 institutions in 1 country.
Funding
Abstract
backgroundSurvivors of opioid overdose have substantially increased mortality risk, although this risk is not evenly distributed across individuals. No study has focused on predicting an individual's risk of death after a nonfatal opioid overdose.
objectiveTo predict risk of death after a nonfatal opioid overdose. DESIGN AND
participantsThis retrospective cohort study included 9686 Pennsylvania Medicaid beneficiaries with an emergency department or inpatient claim for nonfatal opioid overdose in 2014-2016. The index date was the first overdose claim during this period. EXPOSURES, MAIN OUTCOME, AND MEASURES: Predictor candidates were measured in the 180 days before the index overdose. Primary outcome was 180-day all-cause mortality. Using a gradient boosting machine model, we classified beneficiaries into six subgroups according to their risk of mortality (< 25th percentile of the risk score, 25th to < 50th, 50th to < 75th, 75th to < 90th, 90th to < 98th, ≥ 98th). We then measured receipt of medication for opioid use disorder (OUD), risk mitigation interventions (e.g., prescriptions for naloxone), and prescription opioids filled in the 180 days after the index overdose, by risk subgroup. KEY
resultsOf eligible beneficiaries, 347 (3.6%) died within 180 days after the index overdose. The C-statistic of the mortality prediction model was 0.71. In the highest risk subgroup, the observed 180-day mortality rate was 20.3%, while in the lowest risk subgroup, it was 1.5%. Medication for OUD and risk mitigation interventions after overdose were more commonly seen in lower risk groups, while opioid prescriptions were more likely to be used in higher risk groups (both p trends < .001).
conclusionsA risk prediction model performed well for classifying mortality risk after a nonfatal opioid overdose. This prediction score can identify high-risk subgroups to target interventions to improve outcomes among overdose survivors.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.