1. Characterizing Pain Points in Clinical Data Management and Assessing the Impact of Mid-Study Updates
- Author
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Kenneth A. Getz, Van C. Willis, Zachary Smith, Jane L. Snowdon, Rezzan Hekmat, Beth Harper, Dilhan Weeraratne, and Robert DiCicco
- Subjects
Clinical data management ,Computer science ,Mid-study updates ,Pain ,030226 pharmacology & pharmacy ,01 natural sciences ,010104 statistics & probability ,03 medical and health sciences ,0302 clinical medicine ,Drug Development ,Surveys and Questionnaires ,Humans ,Pharmacology (medical) ,Operations management ,0101 mathematics ,Pharmacology, Toxicology and Pharmaceutics (miscellaneous) ,Data Management ,Original Research ,Protocol (science) ,Public Health, Environmental and Occupational Health ,Correction ,Unstructured data ,Clinical trial ,Clinical data science ,Ibm watson - Abstract
Background The causes, degree and disruptive nature of mid-study database updates and other pain points were evaluated to understand if and how the clinical data management function is managing rapid growth in data volume and diversity. Methods Tufts Center for the Study of Drug Development (Tufts CSDD)—in collaboration with IBM Watson Health—conducted an online global survey between September and October 2020. Results One ninty four verified responses were analyzed. Planned and unplanned mid-study updates were the top challenges mentioned and their management was time intensive. Respondents reported an average of 4.1 planned and 3.7 unplanned mid-study updates per clinical trial. Conclusion Mid-study database updates are disruptive and present a major opportunity to accelerate cycle times and improve efficiency, particularly as protocol designs become more flexible and the diversity of data, most notably unstructured data, increases.
- Published
- 2021