The Next Step for EDC

From January through November 2008, the US Food and Drug Administration (FDA) approved 17 new molecular entities (NME),¹ with each NME costing approximately $1.3 billion.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 drug 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 drug sponsors are also replacing the paper-based 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 sof EDC are lower operational costs, more efficient processes, and better data quality. The data doesn't have to be entered from the paper forms, and with edit-checks incorporated into the EDC software, there are fewer errors and queries for the data management team,⁴ more efficient monitoring for Clinical Research Associates, and more detailed trial information for Project Managers.⁵ Another benefit of EDC is improved timelines for getting clean patient data, especially when integrating Interactive Voice or Web Response (IVR/IWR) and lab data. By integrating these three systems when a patient is randomized, 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.

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

• The 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 are verified against the source by monitors.⁶

• Data from other sources are loaded into 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 trial must be reconciled with other key systems, such as Severe Adverse Event (SAE) and Clinical Trial Management Systems (CTMS). While the processes to achieve this goal differ, it is important to ensure the events and data in the clinical system are consistent with data in these other key systems (e.g., SAE, CTMS).

• 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 spite of the benefits of EDC, there are some problems in the clinical trials process that need addressing. Incorporating EDC into clinical trials requires selecting a team leader and extensive planning across different teams. Companies who have successfully used EDC defined the roles and challenges that EDC would present before beginning a clinical trial. Furthermore, they devised solutions to those 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 challenges that arise during the clinical trial. The front-end planning requires investing significant money up-front and a sponsor may not reap the benefits for some time.⁷ In addition, a sponsor may have different vendors for different software and hardware, which makes compatibility increasingly difficult. Even with extensive planning, the team leader needs to convince the clinical research staff that the new way of collecting data will produce benefits to the clinical trial. The leader should also provide ongoing training to the clinical research staff so that EDC is used correctly.⁸

In addition to planning and training, a sponsor has to ensure that the EDC system complies with regulatory guidelines, specifically 21 CFR 11, 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, plus appropriate controls over the system.⁹ 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.¹⁰

Integrating into ETMS

Although careful planning and training is helpful to 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 multicenter sites. With major EDC vendors basing their software on the Internet, this growth is a vital contributor to continued and accelerated adoption of EDC.

And EDC appears to be changing how clinical trials are conducted. Although EDC can be a useful data collection tool for clinical trials, integrating it into a CTMS is more desirable. With the globalization 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 at the National Institute of Health's Center 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.¹¹

With increased Internet accessibility, sponsors are using 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 randomization numbers, order drug supplies, and even collect patient data.¹² These integrated technologies represent the present and future direction of clinical trials consisting of a centralized system with near real-time sharing of clinical trial information.

Of these technologies, EHR has potential to change how data are collected in clinical trials, particularly for clinical trial sites in health care settings. Because EHRs are required to collect demographic data, medical history, laboratory data, narratives, and adverse events,^13,14 it would make sense to reuse them in a clinical trial. 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.¹⁵ Another potential benefit of EHR adoption and integration with EDC is that the clinical trial participant recruitment process could be streamlined. For example, study participants could log onto a secure Web site and answer an eligibility screening questionnaire¹⁶ instead of completing and mailing a form, waiting, and then participating in a phone interview. In addition, one doesn't need to worry about storing paperwork or searching for a document within the paperwork. Information can be shared more quickly when using EDC, which can be helpful to trial monitoring.¹⁷

In spite of these benefits, adoption of EHR systems by the health care industry has been slow. For example, a random sample of 2758 U.S. physicians surveyed identified only 4% had a comprehensive EHR system whereas 13% had a basic EHR system.¹⁸ Although EHRs may be complex to install, the new workflows can be beneficial with fewer transcriptions of data. A 2005 survey by the American Hospital Association of 903 hospitals found that teaching hospitals use IT (including EHRs) more so than nonteaching hospitals.¹⁹

Additional concerns related to EHR adoption include the lack of financial support to implement EHR, although that may change with the $19 billion incentive by the Obama administration for health information technology.²⁰ Other barriers to EHR adoption include how physicians will use EHRs, incompatibility of EHR systems with other systems, the nonexistence of standardized information and code sets, and privacy.²¹ Privacy concerns extend to access, such as recruiting potential clinical trial participants through doctors based on medical records; however, privacy issues may lead to changes in informed consent.²²

Privacy and security concerns related to EHRs are addressed by the Health Information Technology for Economic and Clinical Health Act (HITECH), an act that calls for stricter enforcement of the Health Insurance Portability and Accountability Act (HIPAA).²³ For example, patients must be notified if there are violations of EHR security. However, security and privacy concerns extend beyond HITECH. Some suggest developing a national framework of best practices with an emphasis on ensuring the privacy and safety of the data and increasing transparency on the use of secondary health data, especially with the public.²⁴

The need for standards

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 by developing innovative solutions to enhance interoperability among different systems so that health care 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.²⁵ Having the technology for EDC and EHR systems to be directly linked can reduce the likelihood of transcription errors, save time by decreasing the workload (e.g., repeated data collection, data-entry, monitoring, data reconciliation), and allow data to be transformed and shared quickly.^26,27

To encourage greater compatibility across EHRs, one needs standards. Health Level Seven (HL7), Comite Europeen de Normalisation—Technical Committee (CEN TC) 215, and the American Society for Testing and Materials (ASTM) E31 are working to create such standards.²⁸ Other ongoing key activities that are addressing some of the top barriers to EHR include:

• The Critical Path Initiative of the U.S. FDA (http://www.fda.gov/ScienceResearch/SpecialTopics/CriticalPathInitiative/default.htm): The FDA's effort to use evolving technology and scientific discoveries to improve the drug development process.

• The Clinical Trials Transformation Initiative (https://www.trialstransformation.org/fda-and-duke-collaborate-to-modernize-clinical-trials/): A collaboration between the U.S. FDA and Duke University Medical Center that will modernize the way clinical trials are conducted.

• The Certification Commission for Healthcare Information Technology (CCHIT; http://www.cchit.org/): A recognized certification body for EHRs and their networks.

• The Biomedical Research Integrated Domain Group (BRIDG; ): 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 U.S. FDA as an effort to delineate clinical and medical research domains so that there is a common language across clinical researchers and the equipment used in such research.

The goals of these activities include creation and the 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 (see Figure 2) may result in better data quality, faster access to source data, and a more efficient drug development cycle.

As we evolve toward the ETMS of the future (see Figure 3), there will be some factors that may affect adoption. Government regulation, standards evolution, and 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. Within the industry, the increasing complexity of trial design, changing technology demands, and pressure to reduce costs will help ETMS move forward.

Geoffrey Ross Rothmeier is Senior Director, Global EDC Solutions at Covance, 206 Carnegie Center Drive, Princeton, NJ 08540, e-mail: [email protected].

References

1. Center for Drug Evaluation and Research (CDER) New Molecular Entity (NME) and New Biologics Approval for Calendar Year 2008, http://www.fda.gov/downloads/Drugs/DevelopmentApprovalProcess/HowDrugsareDevelopedandApproved/DrugandBiologicApprovalReports/NMEDrugandNewBiologicApprovals/UCM081805.pdf.

2. J.A. DiMasi and H.G. Grabowski, "The Cost of Biopharmaceutical R&D: Is Biotech Different?" Managerial and Decision Economics, 28, 469-479 (2007).

3. L. Henderson, "Common Ground for eCTD," Applied Clinical Trials, 18 (6) 22-23 (2009).

4. W. Claypool, "Hitting the Sweet Spot," sPharmaceutical Executive Supplement, June 2006.

5. K. Mousley, "EDC and Biopharma Careers—Using Portals and Workflow to Help with Job Functional Changes," EDC Today, 18, 1-6 (2003). http://www.edcmanagement.com/edctoday/EDC%20Today%20Issue%2018.pdf.

6. Ibid.

7. J. Park, ed, "Are We There Yet?" Pharmaceutical Executive, July 2006, 56-68.

8. J.A. Welker, "Implementation of Electronic Data Capture Systems: Barriers and Solutions," Contemporary Clinical Trials, 28, 329-336 (2007).

9. Code of Federal Regulations, Title 21, Part 11, Electronic Records; Electronic Signatures (U.S. Government Printing Office, Washington, DC), http://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfcfr/CFRSearch.cfm?CFRPart=11&showFR=1.

10. The 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 .

11. Clinical Trials Management Systems (CTMS), Newcomer Information, https://cabig.nci.nih.gov/workspaces/CTMS/?pid=primary.2006-10-24.9768040952&sid=ctmsws&status=True.

12. D. McEntegart, "Forced Randomization: When Using Interactive Voice Response Systems," Applied Clinical Trials, October 2003.

13. Healthcare Information and Management Systems Society (HIMSS) Web site, http://www.himss.org/ASP/index.asp/.

14. 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.

15. K. Yamamoto, S. Matsumoto, H. Tada et al., "A Data Capture System for Outcome Studies that Integrates with Electronic Health Records: Development and Potential Uses," Journal of Medical Systems, 32, 423-427 (2008).

16. K.S. Smith, D. Eubanks, A. Petrik et al., "Using Web-based Screening to Enhance Efficiency of HMO Clinical Trial Recruitment in Women Aged Forty or Older," Clinical Trials, 4, 102-105 (2007).

17. U. Sahoo and A. Bhatt, "Electronic Data Capture (EDC)—A New Mantra for Clinical Trials," Quality Assurance, 10 117-121 (2003).

18. C.M. DesRoches, E.G. Campbell, S.R. Rao et al., "Electronic Health Records in Ambulatory Care–A National Survey of Physicians," New England Journal of Medicine, 359 (1) 50-60 (2008).

19. American Hospital Association, "Forward Momentum. Hospitals Use of Information Technology," www.aha.org/aha/content/2005/pdf/FINALNonEmbITSurvey105.pdf.

20. Department of Health and Human Services, Funding Highlights, http://www.whitehouse.gov/omb/assets/fy2010_new_era/Department_of_Health_and_Human_Services1.pdf.

21. Healthcare Financial Management Association, "Overcoming Bariers to Electronic Health Record Adoption," http://www.hfma.org/NR/rdonlyres/480C921F-8D33-48E8-A33F-1512A40F2CC8/0/ehr.pdf.

22. J. Armitage, R. Souhami, L. Friedman et al., "The Impact of Privacy and Confidentiality Laws on the Conduct of Clinical Trials," Clinical Trials, 5, 70-74 (2008).

23. http://www.cms.hhs.gov/SecurityStandard/Downloads/SecurityGuidanceforRemoteUseFinal122806rev.pdf.

24. C. Safran, M. Bloomrosen, W.E. Hammond et al., "Toward a National Framework for the Secondary Use of Health Data: An American Medical Informatics Association White Paper," Journal of the American Medical Informatics Association, 14 (1) 1-9 (2007).

25. IHE IT Infrastructure Technical Framework Supplement 2006-2007, September, http://www.ihe.net/Technical_Framework/upload/IHE_ITI_TF_Suppl_RFD_TI_2006_09_25.pdf.

26. R. Kush, L. Alschuler, R. Ruggeri et al., "Implementing Single Source: The STARBRITE Proof-of-Concept Study," Journal of the American Medical Informatics Association, 14, 662-673 (2007).

27. K. Yamamoto, S. Matsumoto, H. Tada et al., "A Data Capture System for Outcome Studies that Integrates with Electronic Health Records: Development and Potential Uses," Journal of Medical Systems, 32, 423-427 (2008).

28. Electronic Health Records Overview, National Institutes of Health, National Center for Research Resources, April 2006, http://www.ncrr.nih.gov/publications/informatics/EHR.pdf.