An Exploratory Evaluation Framework for e-Clinical Data Management Performance
Electronic data management is becoming important to reduce the overall cost and run-time of clinical trials with enhanced data quality. It is also imperative to meet regulated guidelines for the overall quality and safety of electronic clinical trials. The purpose of this paper is to develop an exploratory performance evaluation framework for e-clinical data management. This study performs a Delphi survey for 3 iterative rounds to develop an exploratory framework based on key informants’ knowledge. Four key metrics in the areas of infrastructure, intellectual preparation, study implementation, and study completion covering major aspects of clinical trial processes are proposed. Performance measures evaluate the extent of regulation compliance, data quality, cost, and efficiency of the electronic data management process. They also provide measurement indicators for each evaluation item. Based on the key metrics, the performance evaluation framework is developed in three major areas involved in clinical data management—clinical site, monitoring, and data coordinating center. From this initial attempt to evaluate the extent of electronic data management in clinical trials by a Delphi survey, further empirical studies are planned and recommended.
Keywordsclinical trials data management electronic data capture system performance metrics
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- 5.Broeck J, Cunningham S, Eeckels R, Herbst K. Data cleaning: detecting, diagnosing, and editing data abnormality. PLoS Med. 2005;2(10):966–970. https://doi.org/www.plosmedicine.org/article/info%3Adoi%2F10.1371%2Fjournal.pmed.0020267. Accessed June 8, 2012.Google Scholar
- 8.Nahm M, Pieper C, Cunningham M. Quantifying data quality for clinical trials using electronic data. PLoS Med. 2008;3(8):1–8. https://doi.org/www.plosone.org/article/info:doi%2F10.1371%2Fjournal.pone.0003049. Accessed June 8, 2012.Google Scholar
- 12.Dixon S. Leveraging next generation technologies to effectively conduct post marketing surveillance. Paper presented at: The 14th Annual Workshop in DIA Japan for Clinical Data Management: New Genesis of CDM to Drive Worldwide Clinical Studies; January 27–28, 2011; Tokyo, Japan.Google Scholar
- 13.Prokscha S. Practical Guide to Clinical Data Management. London: Taylor and Francis; 2007.Google Scholar
- 14.US Food and Drug Administration. Guide for Industry; Computerized Systems Used in Clinical Investigations (CSUCI). Washington, DC: FDA; 2005.Google Scholar
- 15.International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use Guidance for Industry. E6 Good Clinical Practice. https://doi.org/www.ich.org/products/guidelines/efficacy/efficacy-single/article/good-clinical-practice.html. Accessed June 8, 2012.
- 16.Korean Good Clinical Practice. Korea: KFDA; 2009.Google Scholar