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Validation of an alcohol misuse classifier in hospitalized patients.

Daniel To | Brihat Sharma | Niranjan Karnik | Cara Joyce | Dmitriy Dligach | Majid Afshar
Alcohol (Fayetteville, N.Y.) | 2020

Current modes of identifying alcohol misuse in hospitalized patients rely on self-report questionnaires and diagnostic codes that have limitations, including low sensitivity. Information in the clinical notes of the electronic health record (EHR) may further augment the identification of alcohol misuse. Natural language processing (NLP) with supervised machine learning has been successful at analyzing clinical notes and identifying cases of alcohol misuse in trauma patients.

Pubmed ID: 31574300

Research resources used in this publication

None found

Additional research tools detected in this publication

Antibodies used in this publication

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Associated grants

  • Agency: NLM NIH HHS, United States
    Id: R01 LM010090
  • Agency: NIDA NIH HHS, United States
    Id: UG1 DA049467
  • Agency: NIDA NIH HHS, United States
    Id: R01 DA041071
  • Agency: NCATS NIH HHS, United States
    Id: UL1 TR002389
  • Agency: NIAAA NIH HHS, United States
    Id: K23 AA024503
  • Agency: NLM NIH HHS, United States
    Id: R01 LM012973

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cTAKES (tool)

RRID:SCR_006379

An open-source natural language processing system for information extraction from electronic medical record clinical free-text. This is a system through which one creates one or more pipelines to process clinical notes and to identify clinical named entities. It processes clinical notes, identifying types of clinical named entities, drugs, diseases/disorders, signs/symptoms, anatomical sites and procedures. Each named entity that is found is given attributes for the text span, the ontology mapping code, the context (family history of, current, unrelated to patient), and negated/not negated. cTAKES is built on the UIMA framework. cTAKES 2.5 does not provide a GUI of its own for installation or processing. The cTAKES documentation shows how to use the GUIs provided by the UIMA framework, and how to run cTAKES from a command line. Before using cTAKES you need to know that cTAKES does not provide any mechanisms of its own to handle patient data securely. It is assumed that cTAKES is installed on a system that can process patient data, or that any data being processed by cTAKES has already been through a deidentification step in order to comply with any applicable laws. The tool has been developed and deployed at Mayo Clinic since early 2000.

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