Risk-based Source Data Verification

Risk-Based Source Data Verification is a systematic approach to verifying clinical trial data in which the extent and focus of source data checks are prioritized and tailored according to the level of risk to patient safety and data integrity, distinguishing it from comprehensive or random verification methods by its reliance on proactive risk assessment and targeted monitoring strategies.

9

Publications

256

Citations

57

Authors

28

Institutions

Publications per year

2017–2026

2

Variants

Risk-based Sdv

Authors

57

  1. JW
    Joel Waters

    Target (United States), United States

    3 publications · 89 citations

    3

    h-index

  2. VT
    Vadim Tantsyura

    Target (United States), United States

    3 publications · 89 citations

    3

    h-index

  3. KF
    Kaye Fendt

    PAREXEL International (United States), United States

    3 publications · 89 citations

    3

    h-index

  4. JT
    Jules T. Mitchel

    Target (United States), United States

    3 publications · 89 citations

    3

    h-index

  5. YJ
    Yong Joong Kim

    Oklahoma State University, United States

    2 publications · 55 citations

    2

    h-index

1–5 of 57

Venues

  1. Therapeutic Innovation & Regulatory Science

    TIRS · 6 publications · 164 citations

    6

    h-index

  2. Journal of the American Medical Directors Association

    JAMDA · 1 publications · 40 citations

    1

    h-index

  3. Clinical Trials

    1 publications · 18 citations

    1

    h-index

  4. Drug Information Journal

    DIA · 1 publications · 34 citations

    1

    h-index

1–4