A Validated Logistic Regression Model to Identify Coronary Heart Disease patients (CHD) within Primary Care Databases in the United Kingdom

Krish Thiru, P. Donnan, F. Sullivan

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

    2 Citations (Scopus)

    Abstract

    We established the optimal search strategy for identifying coronary heart disease (CHD) patients within the Electronic Patient Record (EPR) of 'paperless' family practices in the UK. Multiple logistic regression modelling (MLRM) and Receiver Operating Characteristic (ROC) curves were used to develop the query. The selected search strategy was validated at 2 additional paperless family practices.

    Original languageEnglish
    Title of host publicationAMIA 2003 Symposium Proceedings
    PublisherAmerican Medical Informatics Association
    Pages1030
    Number of pages1
    Publication statusPublished - 2003
    EventAMIA Annual Symposium 2003 - Marriott Wardman Park, Washington, United States
    Duration: 8 Nov 200312 Nov 2003
    https://knowledge.amia.org/amia-55142-a2003a-1.616734?qr=1

    Conference

    ConferenceAMIA Annual Symposium 2003
    CountryUnited States
    CityWashington
    Period8/11/0312/11/03
    Internet address

    Fingerprint Dive into the research topics of 'A Validated Logistic Regression Model to Identify Coronary Heart Disease patients (CHD) within Primary Care Databases in the United Kingdom'. Together they form a unique fingerprint.

    Cite this