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Simplifying Electronic Data Capture in Clinical Trials: Workflow Embedded Image and Biosignal File Integration and Analysis via Web Services


To improve data quality and save cost, clinical trials are nowadays performed using electronic data capture systems (EDCS) providing electronic case report forms (eCRF) instead of paper-based CRFs. However, such EDCS are insufficiently integrated into the medical workflow and lack in interfacing with other study-related systems. In addition, most EDCS are unable to handle image and biosignal data, although electrocardiography (EGC, as example for one-dimensional (1D) data), ultrasound (2D data), or magnetic resonance imaging (3D data) have been established as surrogate endpoints in clinical trials. In this paper, an integrated workflow based on OpenClinica, one of the world’s largest EDCS, is presented. Our approach consists of three components for (i) sharing of study metadata, (ii) integration of large volume data into eCRFs, and (iii) automatic image and biosignal analysis. In all components, metadata is transferred between systems using web services and JavaScript, and binary large objects (BLOBs) are sent via the secure file transfer protocol and hypertext transfer protocol. We applied the close-looped workflow in a multicenter study, where long term (7 days/24 h) Holter ECG monitoring is acquired on subjects with diabetes. Study metadata is automatically transferred into OpenClinica, the 4 GB BLOBs are seamlessly integrated into the eCRF, automatically processed, and the results of signal analysis are written back into the eCRF immediately.

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  10. Vietnam, Indonesia, South Africa, Turkey, and Argentina


  1. Pavlović I, Kern T, Miklavcic D: Comparison of paper-based and electronic data collection process in clinical trials: costs simulation study. Contemp Clin Trials 30(4):300–316, 2009

    PubMed  Article  Google Scholar 

  2. Langer S, Bartholmai B: Imaging informatics: challenges in multi-site imaging trials. J Digit Imaging 24(1):151–159, 2011

    PubMed  Article  PubMed Central  Google Scholar 

  3. Uppoor RS, Mummaneni P, Cooper E, Pien HH, Sorensen AG, Collins J, et al: The use of imaging in the early development of neuropharmacological drugs: a survey of approved NDAs. Clin Pharmacol Ther 84(1):69–74, 2007

    PubMed  Article  Google Scholar 

  4. Baker SG, Sargent DJ: Designing a randomized clinical trial to evaluate personalized medicine: a new approach based on risk prediction. J Natl Cancer Inst 102(23):1756–1759, 2010

    PubMed  Article  PubMed Central  Google Scholar 

  5. Leroux H, McBride S, Gibson S: On selecting a clinical trial management system for large scale, multicenter, multi-modal clinical research study. Stud Health Technol Inform 168:89–95, 2011

    PubMed  Google Scholar 

  6. Franklin JD, Guidry A, Brinkley JF: A partnership approach for electronic data capture in small-scale clinical trials. J Biomed Inform 44:103–108, 2011

    Article  Google Scholar 

  7. de Carvalho EC, Batilana AP, Claudino W, Reis LF, Schmerling RA, Shah J, Pietrobon R: Workflow in clinical trial sites & its association with near miss events for data quality: ethnographic, workflow & systems simulation. PLoS One 7(6):e39671, 2012

    PubMed  Article  Google Scholar 

  8. Fenstermacher D, Street C, McSherry T, Nayak V, Overby C, Feldman M: The cancer biomedical informatics grid (caBIG). Conf Proc IEEE Eng Med Biol Soc 1:743–746, 2005

    PubMed  Google Scholar 

  9. El-Ghatta SB, Cladé T, Snyder JC: Integrating clinical trial imaging data resources using service-oriented architecture and grid computing. Neuroinformatics 8(4):251–259, 2010

    PubMed  Article  PubMed Central  Google Scholar 

  10. El Fadly A, Rance B, Lucas N, Mead C, Chatellier G, Lastic P, et al: Integrating clinical research with the Healthcare Enterprise: from the RE-USE project to the EHR4CR platform. J Biomed Inform 44:S94, 2011

    PubMed  Article  Google Scholar 

  11. Deserno TM, Samsel C, Haak D, Spitzer K: Data, function, and context integration of OpenClinica using web services. Proc GMDS 2012 (in German)

  12. Haak D, Gehlen J, Sripad P, Marx N, Deserno TM: Extension of OpenClinica for context-related integration of large data volume. Proc GMDS 2013 (in German)

  13. Deserno TM, Haak D, Samsel C, Gehlen J, Kabino K: Integration image management and analysis into OpenClinica using web services. Proc SPIE 2013; 8674: 0F1-10

  14. Hallaraker O, Vigna G: Detecting malicious JavaScript code in Mozilla. ICECCS Proc. 2005; 85–94

  15. Flanagan D: JavaScript: The Definitive Guide. O’Reilly Media, Inc, 2011

  16. Ullmann C: Calling Cross Domain Web Services in AJAX. Technical Report 2006. Available from:

  17. Brinzarea-Iamandi B, Darie C: AJAX and PHP: Building Modern Web Applications: Build User-Friendly Web 2.0 Applications with JavaScript and PHP. Packt Pub; 2009

  18. Breil B, Kenneweg J, Fritz F, Bruland P, Doods D, Trinczek B, et al: Multilingual medical data models in ODM format: a novel form-based approach to semantic interoperability between routine healthcare and clinical research. Appl Clin Inform 3:276–289, 2012

    PubMed  Article  CAS  PubMed Central  Google Scholar 

  19. Fegan GW, Lang TA: Could an open-source clinical trial data-management system be what we have all been looking for? PLoS Med 5(3):e6, 2008

    PubMed  Article  PubMed Central  Google Scholar 

  20. Reboussin D, Espeland MA: The science of web-based clinical trial management. Clin Trials 2(1):1–2, 2005

    PubMed  Article  Google Scholar 

  21. Musick BS, Robb SL, Burns DS, Stegenga K, Yan M, McCorkle KJ, Haase JE: Development and use of a web-based data management system for a randomized clinical trial of adolescents and young adults. Comput Inform Nurs 29(6):337–343, 2011

    PubMed  Article  PubMed Central  Google Scholar 

  22. Cai J, Chang Z, Wang Z, Paul Segars W, Yin FF: Four-dimensional magnetic resonance imaging (4D-MRI) using image-based respiratory surrogate: a feasibility study. Med Phys 38(12):6384–6394, 2011

    PubMed  Article  PubMed Central  Google Scholar 

  23. Aryanto KY, Broekema A, Oudkerk M, van Ooijen PM: Implementation of an anonymisation tool for clinical trials using a clinical trial processor integrated with an existing trial patient data information system. Eur Radiol 22(1):144–151, 2012

    PubMed  Article  PubMed Central  Google Scholar 

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This research was partly supported by European Foundation for the Study of Diabetes (EFSD 74550-94555).

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Correspondence to Daniel Haak.

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Haak, D., Samsel, C., Gehlen, J. et al. Simplifying Electronic Data Capture in Clinical Trials: Workflow Embedded Image and Biosignal File Integration and Analysis via Web Services. J Digit Imaging 27, 571–580 (2014).

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  • Clinical trial
  • Image analysis
  • Workflow
  • Electronic data capture
  • Web services
  • OpenClinica