ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2017
Large-scale Analysis of Opioid Poisoning Related Hospital Visits in New York State.
Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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Who cites it
6 citing papers in PubMed.
- Implementing a Novel Statewide Network to Support Emergency Department-initiated Buprenorphine Treatment.The western journal of emergency medicine · 2022Review
- A spatiotemporal analysis of opioid poisoning mortality in Ohio from 2010 to 2016.Scientific reports · 2021Article
- Opioid Epidemic in the United States: Empirical Trends, and A Literature Review of Social Determinants and Epidemiological, Pain Management, and Treatment Patterns.International journal of MCH and AIDS · 2019Article
- Machine Learning Based Opioid Overdose Prediction Using Electronic Health Records.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2019Article
- Social Media Based Analysis of Opioid Epidemic Using Reddit.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2018Article
- Differences in Opioid Overdose Mortality Rates Among Middle-Aged Adults by Race/Ethnicity and Sex, 1999-2018.Public health reports (Washington, D.C. : 1974)Article
Corrections and comments
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Authors and funding
7 authors.
Funding
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Abstract
Opioid related deaths are increasing dramatically in recent years, and opioid epidemic is worsening in the United States. Combating opioid epidemic becomes a high priority for both the U.S. government and local governments such as New York State. Analyzing patient level opioid related hospital visits provides a data driven approach to discover both spatial and temporal patterns and identity potential causes of opioid related deaths, which provides essential knowledge for governments on decision making. In this paper, we analyzed opioid poisoning related hospital visits using New York State SPARCS data, which provides diagnoses of patients in hospital visits. We identified all patients with primary diagnosis as opioid poisoning from 2010-2014 for our main studies, and from 2003-2014 for temporal trend studies. We performed demographical based studies, and summarized the historical trends of opioid poisoning. We used frequent item mining to find co-occurrences of diagnoses for possible causes of poisoning or effects from poisoning. We provided zip code level spatial analysis to detect local spatial clusters, and studied potential correlations between opioid poisoning and demographic and social-economic factors.
Indexed as
Identifiers
29854119PMC5977648What OpenQuestion holds
Registered trials
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