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.
This is a preview of subscription content, access via your institution.
Buy single article
Instant access to the full article PDF.
Tax calculation will be finalised during checkout.
Subscribe to journal
Immediate online access to all issues from 2019. Subscription will auto renew annually.
Tax calculation will be finalised during checkout.
Marks R. Validating electronic source data in clinical trials. Control Clin Trials. 2004;25;437–446.
Welker J. Implementation of electronic data capture systems: barriers and solution. Contemp Clin Trials. 2007;29;329–336.
Arab L, Hahn H, Henryo J, Chacko E, Winter A, Cambou M. Using the web for recruitment, screen, tracking. data management, and quality control in dietary assessment clinical validation trial. Contemp Clin Trials. 2007;31:138–146.
Lu Z. Technical challenges in designing post-marketing eCRFs to Address clinical safety and pharmacovigilance needs. Contemp Clin Trials. 2010;31:108–118.
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.
Knatterud G, Ricjgikdm F, Gerigem S, et al. Guidelines for quality assurance in multicenter trials: a position paper. Control Clin Trials. 1993;19:477–493.
Moher D, Jada A, Nichol G, Penman M, Tugwell P, Walsh S. Assessing the quality of randomized controlled trials: an annotated bibliography of scales and checklists. Control Clin Trials.1995;16:62–73.
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.
Lee H, Choi I. Effect analysis of electronic clinical trial systems using measurement indicator of efficiency. Journal of Korea Contents Association. 2011;11(1).
Pavlovic I, Kern T, Miklavcic D. Comparison of paper-based and electronic data collection process in clinical trials: costs simulation study. Contemp Clin Trials. 2009;30:300–316.
Ene-Idordache B, Carminati S, Antiga L, et al. Developing regulatory-compliant electronic case report forms for clinical trials: experience with demand trial. Journal of America Information Association. 2009;16:404–408.
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.
Prokscha S. Practical Guide to Clinical Data Management. London: Taylor and Francis; 2007.
US Food and Drug Administration. Guide for Industry; Computerized Systems Used in Clinical Investigations (CSUCI). Washington, DC: FDA; 2005.
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.
Korean Good Clinical Practice. Korea: KFDA; 2009.
Okoli C, Pawlowski S. The Delphi method as a research tool: an example, design considerations and applications. Inform Manage.2004;42:15–42.
Schmidt R. Managing Delphi surveys using nonparametric statistical techniques. Decision Sci. 1997;28(3):763–774.
Stanley R, Lillis F, Zuspan S, et al. Development and implementation of a performance measure tool in an academic pediatric research network. Contemp Clinl Trials. 2010;31:429–437.
Edmondson A, Bohmer R, Pisano G. Disrupted routines: team learning and new technology implementation in hospitals. Admin Sci Quart. 2001;46(4):685–716.
Marray J, Hammon J. Delphi: a versatile methodology for conducting qualitative research. Rev High Educ. 1995;18(4):423–436.
About this article
Cite this article
Lee, H., Lee, S. An Exploratory Evaluation Framework for e-Clinical Data Management Performance. Ther Innov Regul Sci 46, 555–564 (2012). https://doi.org/10.1177/0092861512452119
- clinical trials
- data management
- electronic data capture system
- performance metrics