Adverse Event Detection

Adverse Event Detection is a clinical analytics method designed to identify unintended patient harm or negative outcomes in electronic health records by systematically distinguishing anomalous clinical events from routine care processes.

794

Publications

61.1K

Citations

4.6K

Authors

1.6K

Institutions

Publications per year

2017–2026

264

Authors

4.6K

  1. DC
    David C. Classen

    University of Utah, United States

    16 publications · 3.3K citations

    16

    h-index

  2. AJ
    Alan J. Forster

    University of Ottawa, Canada

    14 publications · 1.6K citations

    13

    h-index

  3. DW
    David W. Bates

    Brigham and Women's Hospital, United States

    12 publications · 1.9K citations

    11

    h-index

  4. GR
    G. Ross Baker

    University of Toronto, Canada

    8 publications · 443 citations

    8

    h-index

  5. EB
    Ethan Basch

    University of North Carolina at Chapel Hill, United States

    8 publications · 2.2K citations

    8

    h-index

1–5 of 4.6K

Venues

  1. PubMed

    Repository · 41 publications · 3.1K citations

    24

    h-index

  2. BMJ Quality & Safety

    23 publications · 1.4K citations

    21

    h-index

  3. Journal of the American Medical Informatics Association

    JAMIA · 22 publications · 2.4K citations

    19

    h-index

  4. Drug Safety

    24 publications · 815 citations

    19

    h-index

  5. Journal of Patient Safety

    18 publications · 652 citations

    17

    h-index

1–5