Quantifying Gains in Data Quality for Sampling Plans Used in Clinical Trial Monitoring

被引:0
作者
Dennis W. King
Melynda Hazelwood
机构
[1] STATKING Consulting,
[2] Inc.,undefined
来源
Drug information journal : DIJ / Drug Information Association | 2003年 / 37卷
关键词
Data quality; Data management; Quality assurance; Continuous sampling plans; Clinical monitoring;
D O I
暂无
中图分类号
学科分类号
摘要
Clinical study monitoring is the first level of quality assurance checks on clinical trials data. The clinical study monitor goes to the study site and compares the case report forms to the source documents. Because some clinical trials are very large, the monitor may not be able to do a 100% check of all case report forms versus their corresponding source document. This paper will examine three possible sampling plan scenarios for monitoring case report forms in large studies.
引用
收藏
页码:135 / 141
页数:6
相关论文
共 25 条
  • [21] Quality Assurance in German Hospitals - Federal Quality of Care Monitoring vs. Evaluation of Routine Clinical Data. A Head-to-Head Comparison on the Example of Pressure Ulcers
    Theisen, S.
    Drabik, A.
    Luengen, M.
    Stock, S.
    GESUNDHEITSWESEN, 2011, 73 (12) : 803 - 809
  • [22] Combined CT Image Quality and Radiation Dose Monitoring Program Based On Patient Data to Assess Consistency of Clinical Imaging Across Scanner Models
    Christianson, O.
    Winslow, J.
    Samei, E.
    MEDICAL PHYSICS, 2014, 41 (06) : 558 - +
  • [23] Extended Risk-Based Monitoring Model, On-Demand Query-Driven Source Data Verification, and Their Economic Impact on Clinical Trial Operations
    Tantsyura, Vadim
    Dunn, Imogene McCanless
    Waters, Joel
    Fendt, Kaye
    Kim, Yong Joong
    Viola, Deborah
    Mitchel, Jules
    THERAPEUTIC INNOVATION & REGULATORY SCIENCE, 2016, 50 (01) : 115 - 122
  • [24] Extended Risk-Based Monitoring Model, On-Demand Query-Driven Source Data Verification, and Their Economic Impact on Clinical Trial Operations
    Vadim Tantsyura
    Imogene McCanless Dunn
    Joel Waters
    Kaye Fendt
    Yong Joong Kim
    Deborah Viola
    Jules Mitchel
    Therapeutic Innovation & Regulatory Science, 2016, 50 : 115 - 122
  • [25] Investigating the potential of deep learning for patient-specific quality assurance of salivary gland contours using EORTC-1219-DAHANCA-29 clinical trial data
    Nijhuis, Hanne
    van Rooij, Ward
    Gregoire, Vincent
    Overgaard, Jens
    Slotman, Berend J.
    Verbakel, Wilko F.
    Dahele, Max
    ACTA ONCOLOGICA, 2021, 60 (05) : 575 - 581