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To EDC and Beyond

Ross Rothmeier at Covance evaluates electronic data capture as part of an electronic trial management system: what lies ahead for EDC and what is required for its success 

In 2009, the European Medicines Agency (EMA) approved 20 new active substances (NAS), the cost of each NAS close to €1 billion (1,2). Drug sponsors are under increasing pressure to reduce drug development costs while managing more streamlined clinical trials. In an effort to promote a more efficient review, and possibly reductions in paper-based and postage costs, some sponsors have used the electronic common technical document (eCTD) and found that it has resulted in faster submissions (3). In addition to the eCTD, some sponsors are also replacing the paperbased system with an electronic data capture (EDC) system that is used by investigators to collect study data during a clinical trial.

BENEFITS OF EDC

The primary benefits of EDC can include lower operational costs, more efficient processes and better data quality. The data does not need to be transfered from the paper forms, and with edit-checks incorporated into the EDC software, there are fewer errors and queries for the data management team, more efficient monitoring for clinical research associates, and more detailed trial information for project managers (4,5). Another benefit of EDC is often improved timelines for getting clean patient data, especially when integrating with data from other sources like interactive voice or web response (IVR/IWR) and lab data.

By integrating these three systems when a patient is randomised, a reliable and consistent subject identifier can tie the data together and reduce the need for reconciliation or delays caused by waiting for data from one system before entering it into another.

Figure 1 shows how a sponsor uses EDC and may include the following steps:

  • A clinical trial using EDC requires comprehensive planning, including selecting the interfaces needed for connecting data outside the EDC system.
  • With some exceptions, data are typically captured in a source document – such as a patient chart – and then transcribed to an electronic case report form (eCRF) in the EDC application. Although EDC has built-in edit checks, these data are reviewed by trained data management specialists and verified against the source by monitors (5).
  • Data from other sources are loaded onto a combined database. Whether integrated with the EDC application database or a central database, the integration process must be monitored for accuracy and verified to ensure the correct data have been received and loaded into the central database.
  • Data from the clinical trial must be reconciled with other key systems, such as severe adverse event (SAE) and clinical trial management systems (CTMS). While the processes used to achieve this goal differ, it is important to ensure the events and data in the clinical system are consistent with data in the other key systems.
  • To aid analysis, some data are given a numerical code (typically found in WHOMED, SNOMED or MeDRA dictionaries) through a coding system. The coding process can also identify data discrepancies and spelling, drug name, or event interpretation errors.

CHALLENGES EDC MUST OVERCOME

In order to reap the benefits of EDC, thoughtful, advanced planning is often required. Companies which have successfully used EDC defined the roles and goals that EDC would present before beginning a clinical trial. Furthermore, they devised solutions to potential challenges ahead of time. Planning considerations include selecting the hardware and software, vendors, data to be measured and assembling a good help desk to handle any challenges that arise during the clinical trial. The front-end planning does require investing significant money upfront and a sponsor may not reap the benefits for some time (6). In addition, a sponsor may have different vendors for different software and hardware, which makes compatibility increasingly difficult. Even with extensive planning, a team leader for an EDC project needs to convince the clinical research staff that the new way of collecting data will produce benefits to the clinical trial.

In addition to planning, a sponsor has to ensure that the EDC system complies with regulatory guidelines, specifically Annex 11 and Directive 95/46/EC which requires the sponsor to demonstrate that the electronic records are valid and have an audit trail to show when and where data were modified, as well as appropriate controls over the privacy of patient data in the system (7). Furthermore, the Good Clinical Practice guidelines recommend that electronic data systems have appropriate safeguards in place, the existence of standard operating procedures that describe how to use these electronic data systems, and that the systems are validated (8).

INTEGRATING EDC & OTHER SYSTEMS INTO ETMS

Although careful planning and training is helpful in implementing EDC, the growth and accessibility of the internet has been useful too. Major EDC vendors have taken advantage of this development by designing web-based software, which circumvents the problem of different computer operating systems or hardware across multi-centre sites. With major EDC vendors basing their software on the internet, this growth is a vital contributor to continued and accelerated adoption of EDC.

EDC also appears to be changing how clinical trials are conducted. Although it can be a useful data collection tool, integrating it with other data related to the trial is more desirable. With the globalisation of clinical trials, it is even more essential to manage data and the trials in as close to real-time as possible. As clinical trials become more complex, a sponsor will need to integrate EDC and other systems into a broader, more comprehensive solution, such as an electronic trial management system (ETMS).

A model for this is underway in the US at the National Institute of Health’s Centre for Biomedical Informatics and Information Technology as part of their cancer biomedical informatics grid (CaBIG) initiative. They have implemented an ETMS-like program with appropriate controls and standards that shares information between cancer researchers and the clinical community, such as clinical laboratory data, patient registration and scheduling, and adverse event reporting (9).

With increased internet accessibility, sponsors are now able to use other technologies with EDC, such as IVR/ IWR systems, direct data capture (DDC), and electronic health records (EHR). A variety of IVR/IWR solutions are being used in clinical trials to assign patient randomisation numbers, order drug supplies and even collect patient data (10). These integrated technologies represent the present and future direction of clinical trials consisting of a centralised system with near real-time sharing of clinical trial information. Of these technologies, EHR has the potential to change how data are collected in clinical trials, particularly for clinical trial sites in healthcare settings. Because EHRs are required to collect demographic data, medical history, laboratory data, narratives and adverse events, it would make sense to re-use them in a clinical trial (11,12). Using EHRs as secondary data in clinical trials can save time by collecting certain data once and circumventing manual data entry. In addition, EHRs can provide information about drug interactions and outcomes, lab results and real-time analysis of adverse events (13). Information can be shared more quickly when using EDC, which can be helpful to trial monitoring (14).

In spite of these benefits, adoption of EHR systems by the healthcare industry has been slow. For example, a random sample of 2,758 US physicians surveyed identified that only four per cent had a comprehensive EHR system whereas 13 per cent had a basic EHR system (15). Although EHRs may be complex to install, the new workflows can be beneficial with fewer transcriptions of data, for example. Other barriers to EHR adoption include how physicians will use EHRs, incompatibility of EHR systems with other systems, the non-existence of standardised information and code sets, and privacy (16).

THE NEED FOR STANDARDS THAT SUPPORT AN ETMS

Bridging the gap between EHR and EDC for clinical trials is a great opportunity, but requires clinical trial systems to exchange data with, or be embedded within EHR systems. Integrating the healthcare enterprise (IHE) initiative is one way of addressing this problem, developing innovative solutions to enhance interoperability among different systems so that healthcare professionals can access reliable patient data. For example, the retrieve form for data capture (RFD) is a system that can extract EHR data for EDC (17). Having the technology for EDC and EHR systems directly linked can reduce the likelihood of transcription errors, save time by decreasing the workload (reducing repeated data collection, data-entry, monitoring and data reconciliation), and allow data to be transformed and shared quickly (13,18).

To encourage greater compatibility across EHRs, standards are required. Health Level Seven (HL7), Comité Européen de Normalisation – Technical Committee (CEN TC) 215, and the American Society for Testing and Materials (ASTM) E31 are working to create such standards (20). Other ongoing key activities that are addressing some of the top barriers to EHR include:

  • The Critical Path Initiative of the US FDA is an effort to use evolving technology and scientific discoveries to improve the drug development process.
  • The Clinical Trials Transformation Initiative is a collaboration between the FDA and Duke University Medical Centre which is working on modernising the way clinical trials are conducted.
  • The Certification Commission for Healthcare Information Technology (CCHIT) is a recognised certification body for EHRs and their networks.
  • The Biomedical Research Integrated Domain Group (BRIDG) is a collaboration among the Clinical Data Interchange Standards Consortium (CDISC), the HL7 Regulated Clinical Research Information Management Technical Committee (RCRIM TC), the National Cancer Institute (NCI), and the US FDA aiming to delineate clinical and medical research domains so that there is a common language across researchers and equipment used in such research.

The goals of these activities include the creation and use of data standards, providing a consistent certification standard for applications that use them, and appropriate data controls under the guidance and support of the FDA.

THE ETMS OF THE FUTURE

With technological advances available, innovative market leaders have the potential to develop products that can integrate IVR/IWR, DDC, EDC and EHR into an ETMS for a sponsor. Integrating these technologies into a single toolset will enable a sponsor to collect more data at multiple study sites and transmit it quickly to a central location. If a sponsor can design a quality and efficient clinical trial using ETMS, then demand for ETMS is likely to increase. A simpler ETMS process may result in better data quality, faster access to source data, and a more efficient drug development cycle (see Figures 2 and 3).

As we evolve toward the ETMS of the future, certain factors may affect adoption. Government regulation, evolution of data standards, and the industry’s tendency to cautiously adopt new technology will continue to influence the speed at which ETMS is adopted, but the changes are already underway. The industry is overcoming some of the obstacles to ETMS adoption, and the increasing complexities of trial design, changing technology demands, and pressures to reduce costs should help ETMS move forward. Those companies that understand the ETMS landscape and are willing to integrate these technologies, including EDC, will lead the way. References

  1. Performance of the agency’s scientific procedures: Survey 2009 for medical products for human use, http://www.ema.europa.eu/pdfs/general/manage/MB2010/66MB/7887310en.pdf, accessed 14 April, 2010
  2. DiMasi JA and Grabowski HG, The Cost of Biopharmaceutical R&D: Is Biotech Different?, Managerial and Decision Economics 28: pp469-479, 2007
  3. Henderson L, Common Ground for eCTD, Applied Clinical Trials 18(6): pp22-23, 2009
  4. Claypool W, Hitting the Sweet Spot, Pharmaceutical Executive Supplement, 9-10 June 2006
  5. Mousley K, EDC and Biopharma Careers – Using Portals and Workflow to Help with Job Functional Changes, EDC Today 18: pp1-6, 2003, http://www.edcmanagement.com/edctoday/EDC%20Today%20Issue%2018.pdf, accessed 28 August, 2009
  6. Park J, Are We There Yet?, Pharmaceutical Executive pp56-68, 2006
  7. Annex 11 Computerized systems (http://ec.europa.eu/enterprise/sectors/pharmaceuticals/files/eudralex/vol-4/pdfs-en/anx11_en.pdf), Directive 95/46/EC of the European Parliament and of the Council, http://ec.europa.eu/justice_home/fsj/privacy/docs/95-46-ce/dir1995-46_part1_en.pdf, accessed 14 April, 2010
  8. Food and Drug Administration, Guidance for Industry, E6 Good Clinical Practice: Consolidated Guidance, FDA, Rockville, MD, April 1996, http://www.fda.gov/downloads/Drugs/GuidanceComplianceRegulatoryInformation/Guidances/ucm073122.pdf, accessed 5 August, 2009
  9. Clinical Trials Management Systems (CTMS), Newcomer Information, https://cabig.nci.nih.gov/workspaces/CTMS/?pid=primary.2006-10-24.9768040952&sid=ctmsws&status=True, accessed 10 August, 2009
  10. McEntegart D, Forced Randomization: When Using Interactive Voice Response Systems, Applied Clinical Trials, 1 October 2003
  11. Healthcare Information and Management Systems Society (HIMSS) Web site, http://www.himss.org/ASP/index.asp, accessed 1 August, 2009
  12. Committee on Data Standards for Patient Safety, Institute of Medicine of the National Academies, Key capabilities of an electronic health record system. Letter Report, http://www.providersedge.com/ehdocs/ehr_articles/Key_Capabilities_of_an_EHR_System.pdf, accessed 28 August, 2009
  13. Yamamoto K, Matsumoto S, Tada H et al, A Data Capture System for Outcome Studies that Integrates with Electronic Health Records: Development and Potential Uses, Journal of Medical Systems 32: pp423-427, 2008
  14. Sahoo U and Bhatt A, Electronic Data Capture (EDC) – A New Mantra for Clinical Trials, Quality Assurance 10: pp117-121, 2003
  15. DesRoches CM, Campbell EG, Rao SR et al, Electronic Health Records in Ambulatory Care – A National Survey of Physicians, New England Journal of Medicine 359(1): pp50-60, 2008
  16. Healthcare Financial Management Association, Overcoming Barriers to Electronic Health Record Adoption, (http://www.hfma.org/NR/rdonlyres/480C921F-8D33-48E8-A33F-1512A40F2CC8/0/ehr.pdf)
  17. IHE IT Infrastructure Technical Framework Supplement 2006-2007, September, 2006, http://www.ihe.net/Technical_Framework/upload/IHE_ITI_TF_Suppl_RFD_TI_2006_09_25.pdf, accessed 13 August, 2009
  18. Kush R, Alschuler L, Ruggeri R et al, Implementing Single Source: The STARBRITE Proof-of-Concept Study, Journal of the American Medical Informatics Association 14: pp662- 673, 2007
  19. Electronic Health Records Overview, National Institutes of Health, National Center for Research Resources, April 2006, http://www.ncrr.nih.gov/publications/informatics/EHR.pdf, accessed 1 August, 2009

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Ross Rothmeier is Senior Director of Global EDC Solutions at Covance, and is responsible for organising and leading their electronic data capture portfolio of projects. With a wide array of technical and process experience, his career focus has been aimed at electronic capture since 1993 where he led the global EDC strategy for Parke-Davis Pharmaceuticals in Ann Arbor Michigan. Later as Director of Services for PhaseForward Inc, he and his team served client needs for EDC at large and small companies in the pharmaceutical and biotechnology sector. Prior to joining Covance, Ross led the global EDC implementation and strategy for the in-house EDC solution at Novartis Pharmaceuticals.
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