Statistical Analysis of County-Level Contributing Factors to Opioid-Related Overdose Deaths in the United States

Haedong Kim; Hui Yang

doi:10.1109/EMBC44109.2020.9176465

Statistical Analysis of County-Level Contributing Factors to Opioid-Related Overdose Deaths in the United States

Haedong Kim, Hui Yang

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Scopus citations

Abstract

This paper examines county-level characteristic factors contributing to opioid-related overdose deaths in the United States. We categorized factors into three groups: demographic, socio-economic, and health care environmental group. These features were used as predictors to model the overdose deaths from all types of opioids including prescription (e.g., oxycodone and hydrocodone) and illicit opioids (e.g., heroin and fentanyl) to investigate general trend, as well as separate models for heroin and fentanyl. Multilevel mixed-effect regression was adopted to adequately model grouping effect across counties.

Original language	English (US)
Title of host publication	42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society
Subtitle of host publication	Enabling Innovative Technologies for Global Healthcare, EMBC 2020
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	5860-5863
Number of pages	4
ISBN (Electronic)	9781728119908
DOIs	https://doi.org/10.1109/EMBC44109.2020.9176465
State	Published - Jul 2020
Event	42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society, EMBC 2020 - Montreal, Canada Duration: Jul 20 2020 → Jul 24 2020

Publication series

Name	Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Volume	2020-July
ISSN (Print)	1557-170X

Conference

Conference	42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society, EMBC 2020
Country/Territory	Canada
City	Montreal
Period	7/20/20 → 7/24/20

All Science Journal Classification (ASJC) codes

Signal Processing
Biomedical Engineering
Computer Vision and Pattern Recognition
Health Informatics

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10.1109/EMBC44109.2020.9176465

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Kim, H., & Yang, H. (2020). Statistical Analysis of County-Level Contributing Factors to Opioid-Related Overdose Deaths in the United States. In 42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society: Enabling Innovative Technologies for Global Healthcare, EMBC 2020 (pp. 5860-5863). Article 9176465 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS; Vol. 2020-July). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EMBC44109.2020.9176465

Kim, Haedong ; Yang, Hui. / Statistical Analysis of County-Level Contributing Factors to Opioid-Related Overdose Deaths in the United States. 42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society: Enabling Innovative Technologies for Global Healthcare, EMBC 2020. Institute of Electrical and Electronics Engineers Inc., 2020. pp. 5860-5863 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS).

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title = "Statistical Analysis of County-Level Contributing Factors to Opioid-Related Overdose Deaths in the United States",

abstract = "This paper examines county-level characteristic factors contributing to opioid-related overdose deaths in the United States. We categorized factors into three groups: demographic, socio-economic, and health care environmental group. These features were used as predictors to model the overdose deaths from all types of opioids including prescription (e.g., oxycodone and hydrocodone) and illicit opioids (e.g., heroin and fentanyl) to investigate general trend, as well as separate models for heroin and fentanyl. Multilevel mixed-effect regression was adopted to adequately model grouping effect across counties.",

author = "Haedong Kim and Hui Yang",

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series = "Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS",

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Kim, H & Yang, H 2020, Statistical Analysis of County-Level Contributing Factors to Opioid-Related Overdose Deaths in the United States. in 42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society: Enabling Innovative Technologies for Global Healthcare, EMBC 2020., 9176465, Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, vol. 2020-July, Institute of Electrical and Electronics Engineers Inc., pp. 5860-5863, 42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society, EMBC 2020, Montreal, Canada, 7/20/20. https://doi.org/10.1109/EMBC44109.2020.9176465

Statistical Analysis of County-Level Contributing Factors to Opioid-Related Overdose Deaths in the United States. / Kim, Haedong; Yang, Hui.
42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society: Enabling Innovative Technologies for Global Healthcare, EMBC 2020. Institute of Electrical and Electronics Engineers Inc., 2020. p. 5860-5863 9176465 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS; Vol. 2020-July).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AB - This paper examines county-level characteristic factors contributing to opioid-related overdose deaths in the United States. We categorized factors into three groups: demographic, socio-economic, and health care environmental group. These features were used as predictors to model the overdose deaths from all types of opioids including prescription (e.g., oxycodone and hydrocodone) and illicit opioids (e.g., heroin and fentanyl) to investigate general trend, as well as separate models for heroin and fentanyl. Multilevel mixed-effect regression was adopted to adequately model grouping effect across counties.

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Kim H, Yang H. Statistical Analysis of County-Level Contributing Factors to Opioid-Related Overdose Deaths in the United States. In 42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society: Enabling Innovative Technologies for Global Healthcare, EMBC 2020. Institute of Electrical and Electronics Engineers Inc. 2020. p. 5860-5863. 9176465. (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS). doi: 10.1109/EMBC44109.2020.9176465

Statistical Analysis of County-Level Contributing Factors to Opioid-Related Overdose Deaths in the United States

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