Data Management in Clinical Research: General Principles and a Guide to Sources

BackgroundAccurate and timely data management (DM) is of key importance in clinical research to generate high-quality and GCP-compliant data for analysis and/or sharing. Our objective is to strengthen the capacity for DM in clinical research in resource-poor settings by organising several teaching initiatives.MethodsOur teaching initiatives have a twofold approach. First, a generic and comprehensive approach with capacity building on various thematical modules. These include a research component (overviewing the research data management procedures) and a technological component (introducing databases and software). In addition, a component on legislation, guidelines and standards specific towards DM is discussed, as well as a project management component on how to organise DM efficiently and timely. Second, we apply a more focused and study-specific approach which details roles and responsibilities in data management, milestones and documentation practices. Both approaches are based upon successful implementation in EDCTP-funded clinical trials, such as the 4ABC, PREGACT and Microbicide Safety Biomarkers studies, as well as the FP7 sponsored NIDIAG project. The target audience comprises various study stakeholders such as data managers, IT administrators, clinicians, laboratory researchers and statisticians, coming from sub-Saharan Africa, South-East Asia and Latin America.ResultsA teaching model for promoting Good Data Management Practices has been developed with theory- and practice-based modules. This model is used at face-to-face workshops in remote settings and has been re-used by colleagues and implemented by other research institutions to promote further capacity building and sustainable development in the South. In addition, it has led to mutual learning and enhanced institutional and personal North-South collaborations.ConclusionThere is a clear case for promoting DM and providing guidelines for Good Data Management Practices. Our twofold approach has enabled the successful conduct of GCP compliant non-commercial clinical trials in the South.

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2069

Journal of Clinical and Translational Science ◽

10.1017/cts.2017.158 ◽

2017 ◽

Vol 1 (S1) ◽

pp. 43-44

Author(s):

Carlton Hornung ◽

Carolyn Thomas Jones ◽

Terri Hinkley ◽

Vicki Ellingrod ◽

Nancy Calvin-Naylor

Keyword(s):

Clinical Research ◽

Data Management ◽

Core Competencies ◽

Safety Data ◽

The United States ◽

Education And Training ◽

Development Ethics ◽

The Impact ◽

And Training ◽

Research Professionals

OBJECTIVES/SPECIFIC AIMS: Clinical research in the 21st century will require a well-trained workforce to insure that research protocols yield valid and reliable results. Several organizations have developed lists of core competencies for clinical trial coordinators, administrators, monitors, data management/informaticians, regulatory affairs personnel, and others. While the Clinical Research Appraisal Inventory assesses the self-confidence of physician scientists to be clinical investigators, no such index exists to assess the competence of clinical research professionals who coordinate, monitor, and administer clinical trials. We developed the Competency Index for Clinical Research Professionals (CICRP) as a general index of competency (ie, GCPs) as well as sub-scales to assess competency in the specific domains of Medicines Development; Ethics and Participant Safety; Data Management; and Research Methods. METHODS/STUDY POPULATION: We analyzed data collected by the Joint Task Force on the Harmonization of Core Competencies from a survey of research professionals working in the United States and Canada. Respondents reported how competent they believed themselves to be on 51 clinical research core competencies. Factor analyzes identified 20 core competencies that defined a Competency Index for Clinical Research Professionals—General (CICRP-General, ie, GCPs) and 4 subindices that define specialized research functions: Medicines Development; Ethics and Participant Safety; Data Management; and Research Concepts. RESULTS/ANTICIPATED RESULTS: Factor analysis identified 20 core competencies that defined a Competency Index for Clinical Research Professionals—General (CICRP-General, ie, GCPs) and 4 subindices that define specialized research functions: Medicines Development; Ethics and Participant Safety; Data Management; and Research Concepts. DISCUSSION/SIGNIFICANCE OF IMPACT: These indices can be used to gage an individual’s readiness to perform general as well as more advanced research functions; to assess the education and training needs of research workers; and to evaluate the impact of education and training programs on the competency of research coordinators, monitors, and other clinical research team members.

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CGO: utilizing and integrating gene expression microarray data in clinical research and data management

Bioinformatics ◽

10.1093/bioinformatics/18.2.327 ◽

2002 ◽

Vol 18 (2) ◽

pp. 327-328 ◽

Cited By ~ 8

Author(s):

K. Bumm ◽

M. Zheng ◽

C. Bailey ◽

F. Zhan ◽

M. Chiriva-Internati ◽

...

Keyword(s):

Gene Expression ◽

Clinical Research ◽

Data Management ◽

Microarray Data ◽

Gene Expression Microarray ◽

Expression Microarray ◽

Gene Expression Microarray Data

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

BMJ Global Health ◽

10.1136/bmjgh-2016-000260.46 ◽

2017 ◽

Vol 2 (Suppl 2) ◽

pp. A19.1-A19

Author(s):

Amélie Julé ◽

Hazel Ashurst ◽

Laura Merson ◽

Piero Olliaro ◽

Vicki Marsh ◽

...

Keyword(s):

Clinical Research ◽

Data Management ◽

Management Practices ◽

Research Data ◽

Research Data Management ◽

Clinical Research Data

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Data Management Procedures in the Asthma Clinical Research Network

Controlled Clinical Trials ◽

10.1016/s0197-2456(01)00170-2 ◽

2001 ◽

Vol 22 (6) ◽

pp. S168-S180 ◽

Cited By ~ 6

Author(s):

Rosanne M Pogash ◽

Susan J Boehmer ◽

Pamela E Forand ◽

Anne-Marie Dyer ◽

Susan J Kunselman

Keyword(s):

Clinical Research ◽

Data Management ◽

Research Network ◽

Clinical Research Network ◽

Management Procedures

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Electronic Data Management for Vaccine Trials in Low Resource Settings: Upgrades, Scalability, and Impact of ODK

Frontiers in Public Health ◽

10.3389/fpubh.2021.665584 ◽

2021 ◽

Vol 9 ◽

Author(s):

Michael Marks ◽

Sham Lal ◽

Hannah Brindle ◽

Pierre-Stéphane Gsell ◽

Matthew MacGregor ◽

...

Keyword(s):

Data Collection ◽

Clinical Research ◽

Data Management ◽

Open Source ◽

Large Scale ◽

Democratic Republic Of Congo ◽

World Health ◽

Electronic Data ◽

Diverse Range ◽

Electronic Data Collection

Background: ODK provides software and standards that are popular solutions for off-grid electronic data collection and has substantial code overlap and interoperability with a number of related software products including CommCare, Enketo, Ona, SurveyCTO, and KoBoToolbox. These tools provide open-source options for off-grid use in public health data collection, management, analysis, and reporting. During the 2018–2020 Ebola epidemic in the North Kivu and Ituri regions of Democratic Republic of Congo, we used these tools to support the DRC Ministère de la Santé RDC and World Health Organization in their efforts to administer an experimental vaccine (VSV-Zebov-GP) as part of their strategy to control the transmission of infection.Method: New functions were developed to facilitate the use of ODK, Enketo and R in large scale data collection, aggregation, monitoring, and near-real-time analysis during clinical research in health emergencies. We present enhancements to ODK that include a built-in audit-trail, a framework and companion app for biometric registration of ISO/IEC 19794-2 fingerprint templates, enhanced performance features, better scalability for studies featuring millions of data form submissions, increased options for parallelization of research projects, and pipelines for automated management and analysis of data. We also developed novel encryption protocols for enhanced web-form security in Enketo.Results: Against the backdrop of a complex and challenging epidemic response, our enhanced platform of open tools was used to collect and manage data from more than 280,000 eligible study participants who received VSV-Zebov-GP under informed consent. These data were used to determine whether the VSV-Zebov-GP was safe and effective and to guide daily field operations.Conclusions: We present open-source developments that make electronic data management during clinical research and health emergencies more viable and robust. These developments will also enhance and expand the functionality of a diverse range of data collection platforms that are based on the ODK software and standards.

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