Literature DB >> 17287151

Implementation of electronic data capture systems: barriers and solutions.

James A Welker1.   

Abstract

Although increasing in pace, the conversion to Electronic Data Capture (EDC) has been a slow progression. The use of EDC systems should confer improved data integrity, cost savings and a shorter time to study database closure. This will reduce the time to market and cost of new medications. With the current sentiment of the industry suggesting the cost analysis has been accepted to be in favor of EDC, the likely limitation to disseminated use is an inability to implement these systems. If the leadership at the sponsor, clinical research organization and investigator site is cognizant of the barriers to implementation, they can anticipate and mitigate them prior to the users becoming disgruntled and resistant to the new method of data capture. Once understood, barriers such as user input, technical support, user motivation, regulatory requirements, communication with users, timing of implementation, software installation, graphical user interface, identification of bridgers, patient participation, availability of technology, and costs can be better addressed at the beginning of the implementation process and successfully averted. This review discusses these barriers and potential solutions that can assist the clinical trial industry in achieving more wide-spread EDC use and the resulting improvement in operating efficiencies.

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Mesh:

Year:  2007        PMID: 17287151     DOI: 10.1016/j.cct.2007.01.001

Source DB:  PubMed          Journal:  Contemp Clin Trials        ISSN: 1551-7144            Impact factor:   2.226


  35 in total

1.  A computerized data-capture system for animal biosafety level 4 laboratories.

Authors:  Dennis A Bente; Jeremy Friesen; Kyle White; Jordan Koll; Gary P Kobinger
Journal:  J Am Assoc Lab Anim Sci       Date:  2011-09       Impact factor: 1.232

Review 2.  Electronic data capture for registries and clinical trials in orthopaedic surgery: open source versus commercial systems.

Authors:  Jatin Shah; Dimple Rajgor; Shreyasee Pradhan; Mariana McCready; Amrapali Zaveri; Ricardo Pietrobon
Journal:  Clin Orthop Relat Res       Date:  2010-10       Impact factor: 4.176

3.  REDLetr: Workflow and tools to support the migration of legacy clinical data capture systems to REDCap.

Authors:  William D Dunn; Jake Cobb; Allan I Levey; David A Gutman
Journal:  Int J Med Inform       Date:  2016-06-27       Impact factor: 4.046

Review 4.  An automated standardized system for managing adverse events in clinical research networks.

Authors:  Rachel L Richesson; Jamie F Malloy; Kathleen Paulus; David Cuthbertson; Jeffrey P Krischer
Journal:  Drug Saf       Date:  2008       Impact factor: 5.606

5.  DICOM for Clinical Research: PACS-Integrated Electronic Data Capture in Multi-Center Trials.

Authors:  Daniel Haak; Charles-E Page; Sebastian Reinartz; Thilo Krüger; Thomas M Deserno
Journal:  J Digit Imaging       Date:  2015-10       Impact factor: 4.056

6.  Data standards for clinical research data collection forms: current status and challenges.

Authors:  Rachel L Richesson; Prakash Nadkarni
Journal:  J Am Med Inform Assoc       Date:  2011-05-01       Impact factor: 4.497

7.  ClinData Express--a metadata driven clinical research data management system for secondary use of clinical data.

Authors:  Zuofeng Li; Jingran Wen; Xiaoyan Zhang; Chunxiao Wu; Zuogao Li; Lei Liu
Journal:  AMIA Annu Symp Proc       Date:  2012-11-03

8.  HIS-Based Support of Follow-Up Documentation - Concept and Implementation for Clinical Studies.

Authors:  S Herzberg; F Fritz; K Rahbar; L Stegger; M Schäfers; M Dugas
Journal:  Appl Clin Inform       Date:  2011-01-05       Impact factor: 2.342

9.  IT Infrastructure Components for Biobanking.

Authors:  H U Prokosch; A Beck; T Ganslandt; M Hummel; M Kiehntopf; U Sax; F Uckert; S Semler
Journal:  Appl Clin Inform       Date:  2010-11-24       Impact factor: 2.342

10.  Electronic data collection in epidemiological research. The use of REDCap in the Pelotas birth cohorts.

Authors:  Cauane Blumenberg; Aluísio J D Barros
Journal:  Appl Clin Inform       Date:  2016-07-13       Impact factor: 2.342

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