scholarly journals VARIABILITY IN CLINICAL RESEARCH DATA MANAGEMENT PRACTICES: LESSONS FROM THE MALARIA COMMUNITY

2017 ◽  
Vol 2 (Suppl 2) ◽  
pp. A19.1-A19
Author(s):  
Amélie Julé ◽  
Hazel Ashurst ◽  
Laura Merson ◽  
Piero Olliaro ◽  
Vicki Marsh ◽  
...  
Author(s):  
Mary Banach ◽  
Kaye H Fendt ◽  
Johann Proeve ◽  
Dale Plummer ◽  
Samina Qureshi ◽  
...  

With the focus of the COVID-19 pandemic, we wanted to reach all stakeholders representing communities concerned with good clinical data management practices. We wanted to represent not only data managers but bio-statisticians, clinical monitors, data scientists, informaticians, and all those who collect, organize, analyze, and report on clinical research data. In our paper we will discuss the history of clinical data management in the US and its evolution from the early days of FDA guidance. We will explore the role of biomedical research focusing on the similarities and differences in industry and academia clinical research data management and what we can learn from each other. We will talk about our goals for recruitment and training for the CDM community and what we propose for increasing the knowledge and understanding of good clinical data practice to all – particularly our front-line data collectors i.e., nurses, medical assistants, patients, other data collectors. Finally, we will explore the challenges and opportunities to see CDM as the hub for good clinical data research practices in all of our communities.We will also discuss our survey on how the COVID-19 pandemic has affected the work of CDM in clinical research.


2021 ◽  
pp. 532-543
Author(s):  
Matthias Ganzinger ◽  
Enrico Glaab ◽  
Jules Kerssemakers ◽  
Sven Nahnsen ◽  
Ulrich Sax ◽  
...  

2018 ◽  
Vol 7 (2) ◽  
pp. e1130
Author(s):  
Tania Bardyn ◽  
◽  
Emily Patridge ◽  
Michael Moore ◽  
Jane Koh ◽  
...  

2017 ◽  
Vol 24 (4) ◽  
pp. 737-745 ◽  
Author(s):  
Meredith N Zozus ◽  
Angel Lazarov ◽  
Leigh R Smith ◽  
Tim E Breen ◽  
Susan L Krikorian ◽  
...  

Abstract Objective: To assess and refine competencies for the clinical research data management profession. Materials and Methods: Based on prior work developing and maintaining a practice standard and professional certification exam, a survey was administered to a captive group of clinical research data managers to assess professional competencies, types of data managed, types of studies supported, and necessary foundational knowledge. Results: Respondents confirmed a set of 91 professional competencies. As expected, differences were seen in job tasks between early- to mid-career and mid- to late-career practitioners. Respondents indicated growing variability in types of studies for which they managed data and types of data managed. Discussion: Respondents adapted favorably to the separate articulation of professional competencies vs foundational knowledge. The increases in the types of data managed and variety of research settings in which data are managed indicate a need for formal education in principles and methods that can be applied to different research contexts (ie, formal degree programs supporting the profession), and stronger links with the informatics scientific discipline, clinical research informatics in particular. Conclusion: The results document the scope of the profession and will serve as a foundation for the next revision of the Certified Clinical Data ManagerTM exam. A clear articulation of professional competencies and necessary foundational knowledge could inform the content of graduate degree programs or tracks in areas such as clinical research informatics that will develop the current and future clinical research data management workforce.


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