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The Evolution of Clinical Data Management to Clinical Data Science: A Reflection Paper on the impact of the Clinical Research industry trends on Clinical Data Management

As SCDM is celebrating its 25th year anniversary, the SCDM Innovation Committee seeks to raise awareness on the upcoming industry trends affecting Clinical Data Management (CDM) and prepare for its evolution toward Clinical Data Science. In the context of this reflection paper, Clinical Data Science is defined as the strategic discipline enabling data driven Clinical Research approaches and ensuring subject protection as well as the reliability and credibility of trial results. Clinical Data Science encompasses  processes, domain expertise, technologies, data analytics and Good Clinical Data Management Practices essential to prompt decision making throughout the life cycle of Clinical Research.

The target audience for this reflection paper is broad‐based clinical data management professionals ‐ from Subject Matter Experts (SMEs) executing CDM activities for their clinical studies to CDM Leaders setting the direction for their organizations.

eSource in Clinical Research: A Data Management Perspective on the Use of Mobile Health Technology

Electronic source data (eSource) in the form of mHealth technologies used for study participant data collection is gaining momentum within the clinical research setting. To effectively adopt mHealth technologies as new data sources, we propose a principles-based approach to the evaluation of eSource, as outlined in the following key areas: technology, people, processes, and standards. We also outline regulatory considerations to provide general guidelines for adoption. All roles, participants, and processes in the clinical trials enterprise will be affected by changes in technology involving new standards, data flows, and data sources. Clinical data managers will see their roles expand and will be positioned to drive the process changes necessary for adopting successful mobile technologies. Mobile health will be a game changer in the conduct of clinical research—one that benefits both the trial participants and the research.

The goal of this paper is to provide data management professionals with a framework to evaluate and implement mHealth technologies using eSource principles. In this paper, we introduce mHealth technology as it relates to the data management discipline, and we hope to stimulate discussion of mHealth to continue SCDM’s dialog on eSource and clinical data innovation.

eSource Implementation in Clinical Research: A Data Management Perspective

SCDM proudly presents its White Paper on eSource Implementation in Clinical Research.

SCDM has described constructive principle and best practices for different modalities organized by processes, people and technology to address the challenges coming from the transformation from the traditional paper CRF collection model to electronic data capture.

The White Paper presents various data collection modalities of eSource and relevant considerations for successful implementation.

SCDM would like to thank the following individuals who collaborated on the SCDM eSource Taskforce to produce this manuscript:

Linda King (Co-Chair), Demetris Zambas (Co-Chair), Sanjay Bhardwaj, Charlene Dark, Begona Gonzalez, Shannon Labout, Evonne Roberts, Ralph Russo, Dorian Tisdale, Steve Ward, and Guang-Liang Wang.

Editorial assistance was provided by Lori S. Brix.

The SCDM eSource Taskforce would like to offer their appreciation and special thanks to:

  • Angela Eberhardt, Darlene Kalinowski, and Wendy Schroeder.
  • The individuals and organizations who offered their feedback and comments during the public comment period.
  • The Data Management Network Europe.
  • The EMA Inspector’s Working Group for their review and comments.
  • Jun Wang on behalf of the China FDA.
  • The US FDA eData team for their encouragement on this project.
  • The SCDM Board of Trustees for their feedback and overall support for the eSource Taskforce and this publication.