A comparison between two approaches to identify opioid use problems: ICD-9 vs. Text-mining approach

Abdullah H. Alzeer, Jay Patel, Brian Dixon, Josette F. Jones, Matthew Bair

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The aim of the research is to ontologically identify and compare the incidence of opioid use problems (OUPs) among patients on long-term opioid therapy using text mining vs. diagnostic coding approaches.

LanguageEnglish (US)
Title of host publicationProceedings - 2018 IEEE International Conference on Healthcare Informatics, ICHI 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages455-456
Number of pages2
ISBN (Electronic)9781538653777
DOIs
StatePublished - Jul 24 2018
Externally publishedYes
Event6th IEEE International Conference on Healthcare Informatics, ICHI 2018 - New York, United States
Duration: Jun 4 2018Jun 7 2018

Other

Other6th IEEE International Conference on Healthcare Informatics, ICHI 2018
CountryUnited States
CityNew York
Period6/4/186/7/18

Fingerprint

Data Mining
International Classification of Diseases
Opioid Analgesics
Incidence
Research
Therapeutics

Keywords

  • Abuse
  • Addiction
  • Opioid
  • Opioid Use Problems
  • Text-mining

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Health Informatics

Cite this

Alzeer, A. H., Patel, J., Dixon, B., Jones, J. F., & Bair, M. (2018). A comparison between two approaches to identify opioid use problems: ICD-9 vs. Text-mining approach. In Proceedings - 2018 IEEE International Conference on Healthcare Informatics, ICHI 2018 (pp. 455-456). [8419433] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICHI.2018.00100

A comparison between two approaches to identify opioid use problems : ICD-9 vs. Text-mining approach. / Alzeer, Abdullah H.; Patel, Jay; Dixon, Brian; Jones, Josette F.; Bair, Matthew.

Proceedings - 2018 IEEE International Conference on Healthcare Informatics, ICHI 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 455-456 8419433.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Alzeer, AH, Patel, J, Dixon, B, Jones, JF & Bair, M 2018, A comparison between two approaches to identify opioid use problems: ICD-9 vs. Text-mining approach. in Proceedings - 2018 IEEE International Conference on Healthcare Informatics, ICHI 2018., 8419433, Institute of Electrical and Electronics Engineers Inc., pp. 455-456, 6th IEEE International Conference on Healthcare Informatics, ICHI 2018, New York, United States, 6/4/18. https://doi.org/10.1109/ICHI.2018.00100
Alzeer AH, Patel J, Dixon B, Jones JF, Bair M. A comparison between two approaches to identify opioid use problems: ICD-9 vs. Text-mining approach. In Proceedings - 2018 IEEE International Conference on Healthcare Informatics, ICHI 2018. Institute of Electrical and Electronics Engineers Inc. 2018. p. 455-456. 8419433 https://doi.org/10.1109/ICHI.2018.00100
Alzeer, Abdullah H. ; Patel, Jay ; Dixon, Brian ; Jones, Josette F. ; Bair, Matthew. / A comparison between two approaches to identify opioid use problems : ICD-9 vs. Text-mining approach. Proceedings - 2018 IEEE International Conference on Healthcare Informatics, ICHI 2018. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 455-456
@inproceedings{c139ff57e1154afca8b6dade538b229d,
title = "A comparison between two approaches to identify opioid use problems: ICD-9 vs. Text-mining approach",
abstract = "The aim of the research is to ontologically identify and compare the incidence of opioid use problems (OUPs) among patients on long-term opioid therapy using text mining vs. diagnostic coding approaches.",
keywords = "Abuse, Addiction, Opioid, Opioid Use Problems, Text-mining",
author = "Alzeer, {Abdullah H.} and Jay Patel and Brian Dixon and Jones, {Josette F.} and Matthew Bair",
year = "2018",
month = "7",
day = "24",
doi = "10.1109/ICHI.2018.00100",
language = "English (US)",
pages = "455--456",
booktitle = "Proceedings - 2018 IEEE International Conference on Healthcare Informatics, ICHI 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

TY - GEN

T1 - A comparison between two approaches to identify opioid use problems

T2 - ICD-9 vs. Text-mining approach

AU - Alzeer, Abdullah H.

AU - Patel, Jay

AU - Dixon, Brian

AU - Jones, Josette F.

AU - Bair, Matthew

PY - 2018/7/24

Y1 - 2018/7/24

N2 - The aim of the research is to ontologically identify and compare the incidence of opioid use problems (OUPs) among patients on long-term opioid therapy using text mining vs. diagnostic coding approaches.

AB - The aim of the research is to ontologically identify and compare the incidence of opioid use problems (OUPs) among patients on long-term opioid therapy using text mining vs. diagnostic coding approaches.

KW - Abuse

KW - Addiction

KW - Opioid

KW - Opioid Use Problems

KW - Text-mining

UR - http://www.scopus.com/inward/record.url?scp=85051140353&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85051140353&partnerID=8YFLogxK

U2 - 10.1109/ICHI.2018.00100

DO - 10.1109/ICHI.2018.00100

M3 - Conference contribution

SP - 455

EP - 456

BT - Proceedings - 2018 IEEE International Conference on Healthcare Informatics, ICHI 2018

PB - Institute of Electrical and Electronics Engineers Inc.

ER -