Characterizing Pain Points in Clinical Data Management and Assessing the Impact of Mid-Study Updates

Ther Innov Regul Sci. 2021 Sep;55(5):1006-1012. doi: 10.1007/s43441-021-00301-z. Epub 2021 May 7.

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 hundred ninety 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.

Keywords: Clinical data management; Clinical data science; Mid-study updates.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Data Management*
  • Drug Development*
  • Humans
  • Pain
  • Surveys and Questionnaires