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www.expresspharmaonline.com FORTNIGHTLY INSIGHT FOR PHARMA PROFESSIONALS
16-31 December 2007  
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Emerging Trends in EDC

Electronic Data Capture (EDC) systems have improved efficiency and accuracy of clinical trials. The next step is to merge EDC with Electronic Medical Record (EMR) systems. An analysis of the tools at hand

Subbaraju Sagi

The adoption of Electronic Medical Records (EMRs) in both hospitals and private practice is on a steady incline. Alongside the growth in EMR, Electronic Data Capture (EDC) systems are today used in an estimated 30-35 percent of clinical trials, again in both hospitals and private practices.

The use of EDC technologies provides the opportunity to significantly enhance clinical trial conduct through improved efficiency and accuracy, as well as the potential for real-time response to possible adverse situations. The data captured in clinical trial systems may be based upon a prior electronic source (eSource), such as EMR.

Unfortunately, many of the EMR systems that manage the electronic source today cannot be used reliably for clinical research purposes because of the variability among these systems and the fact that they are not required to meet regulatory requirements for clinical trials. Therefore, the data that are in the EMR system have to be printed or hand-transcribed and re-entered into the EDC system. The duplication of tasks, generation of paper and associated costs and inefficiencies, will only grow with the increasing use of electronic data sources. With the transformation in healthcare, data collection migrating from a paper world to EDC one, the scenario begs the question, "How can EDC integrate with these systems at sites and avoid redundant data collection?"

The eClinical Forum (www.eclinicalforum.com) and PhRMA EDC/eSource taskforce is very much active in formulating standards around integrating aspects of clinical trial data with healthcare data. This article has reference to many of the survey work and visionary publications of these groups.

EDC background

EDC is a technique for collecting clinical trial data in such a way that they are delivered to the sponsor in electronic form instead of paper. This includes the following scenarios—

l Information that is first recorded on paper by the investigator's staff or the patient, is subsequently entered into a computer at the investigator's site, and is delivered electronically to the sponsor or sponsor's representative (such as a CRO) without a hand-written case report form. The computerised system into which the site enters the clinical trial data is generally provided and maintained by the sponsor or a third-party vendor.

  • Clinical laboratory data that are transmitted to the sponsor electronically and batch-loaded into the sponsor's database (includes other electronic data such as device data)
  • Patient data that are directly captured by instrumentation
  • Electronic Patient Reported Outcome (ePRO) i.e., information that is entered by the patient directly into an electronic device, such as Personal Digital Assistant (PDA), or directly into a web-based system
  • Information that is entered by the investigator's staff directly into a computer, without first writing the data on paper (i.e., electronic source (eSource) data) and which must then be backfilled to the patient's permanent record (paper or EMR) in order to satisfy regulatory obligations.

The use of EDC by the bio-pharmaceutical industry to conduct prospective clinical trials on new drug candidates is growing as bio-pharmaceutical companies face increasing pressure to bring new, innovative products to market faster and in a more cost-conscious manner than ever before. At the same time, increasing concern over product safety has resulted in the need for more and longer trials, causing costs and time-to-market to increase. The use of EDC is seen as a way to improve data quality and drive efficiency in the clinical research process.

eSource Background

The capture of patient data into electronic systems, initially used for patient care purposes, is emerging and has great potential to be a source of data for clinical trials, enabling automated transfer. Today, there are a number of interchangeable terms used to describe such systems. The terms Electronic Health Record (EHR), Electronic Medical Record (EMR), Electronic Patient Record (EPR), Clinical Patient Record (CPR) and Lifetime Clinical Record (LCR) are all used by various individuals and organisations, at times to mean the same thing and at other times to mean different things. In the remainder of this article, EHR will mean eSource data captured in a format that enables structured electronic transfer to clinical research systems. Using this definition, other eSource data commonplace today such as ePROs and central laboratory data are not considered parts of EHR data, as these data are not captured within the EHR initially, although they could be integrated with it subsequently.

The vision—EHR/EDC integrated system

The existing "transitional" or "emerging" environment of EHR and EDC systems both being used in an investigator's office may at times seem like a step backward. For multiple reasons, the same data is being entered and maintained in up to three or four different places. Healthcare practices may first involve a process in which the provider hand-writes information on a patient chart, which is then entered into their EHR system at a different time. This same information may be printed off the EHR system and transcribed for entry into the EDC system. At the end of the study, regulations require that the data in the EDC system remain with the investigator, so it is often printed or copied to a CD for inclusion with the patient's medical information.

Collaboration between these two worlds may work as follows—

  • Pharmaceutical company designs and deploys study at the site using a clinical data management/electronic data capture solution (possibly vendor provided). This solution has an in-built module that employs standard interface definitions developed by a standard committee within biopharmaceutical community and healthcare industries. Using the standard interface definitions, the clinical module can be recognised by any certified EHR system being used by the investigator sites.
  • When a patient comes into the practice, the investigator staff will have access to the patient's entire history, regardless of where the care was given. Any third party diagnostic parameters (such as lab test or x-ray results, patient diary data) will also have been received and stored in the EHR system such that it is readily available to the investigator. The staff will enter all information pertinent to this patient visit. Additional information and screens will be displayed (related to clinical trials) to prompt the staff to collect the additional information and to assist with scheduling and patient visit reminders.
  • The clinical trial patient data will physically reside in both the EHR system and the sponsor's analysis database. Only the EHR system's clinical data module will be considered the source, and it must stay in a validated state under the control of the investigator. Security features surround this module such that it is in compliance with all regulations pertaining to clinical data.
  • At the end of the study, data from this module will be archived in a standard format (perhaps XML or PDF) such that it can be easily read by the investigator and/or an auditor in the future, using standard tools, if need be.

The need to merge these worlds

Benefits of EDC studies (improved data quality, time-to-market, resource efficiency) could be seen by 100 percent—

Currently adopted in about 27 to 30 percent of clinical trials, EDC provides acknowledged benefits over paper CRF data capture. Since a significant portion of the clinical data (e.g., medical history, medical procedures, prescribed medications, vital signs) needed for the trial will already be available in an electronic form through the EHR, the introduction of the clinical research processes in EHR systems and processes will extend and accelerate the existing benefits of EDC into an increasing number of clinical trials and an increasing number of hospitals and healthcare clinics.

Clinical trials available to more physicians—

Additionally, more physicians could become involved in clinical research barring one major hurdle to participation that would be eliminated if clinical data capture were to be straightforward and readily available for those facilities that have adopted EHR systems that include EHR/EDC technology.

Avoid duplicate tasks that increase cost of clinical research (thus increasing costs for marketed medications)—

Significant benefits can be accrued through collaboration of both the healthcare and research worlds by effectively and efficiently sharing data. Without such collaboration and as the use of EHRs grows, both the healthcare sector and bio-pharmaceutical companies will be obliged to spend valuable resources on duplicate tasks, increasing the overall cost of clinical research and its product.

Benefits to patients

All patients whose healthcare provider participates in a nationwide EHR system will reap benefits of that system facilitating clinical research. These benefits are—

  • Potential to address underserved populations through clinical trial recruitment and participation
  • Greater possibility of being identified for a clinical trial because their physician will have better ability to search his/her patient population for inclusion criteria
  • New therapies get to market and reach patients faster due to more efficient clinical research process
  • Higher data quality leads to better safety

Benefits to Investigator staff

  • Patient recruitment—EHR records could be searched for patients satisfying inclusion/exclusion criteria. The assumption is that EHR systems will have the capability to define criteria for selection of patients (e.g., disease, severity, medications taken, medical history, and specific vital signs such as blood pressure)
  • The time required to check-in a patient and complete the medical record will be significantly reduced
  • Data entry will be simplified and more efficient due to a one-time data entry into the EHR system (instead of today's multiple entries) and improved record retrieval
  • Direct transfer of validated data to research systems will be simplified and more efficient due to a common validated interface
  • Information storage will be more efficient as data will be stored electronically saving on space requirements currently needed for paper trials and/or multiple trial/sponsor hardware
  • Serious adverse event (SAE) reporting and management may be simplified and improved as SAEs and associated relevant information, maintained within the EHR could be sent to the sponsor. The sponsor could have the capability to obtain information pertinent to the outcome and causality of the SAE by having real time ongoing access specific to the SAE enabling them to prepare a comprehensive narrative.
  • Regulations and controls surrounding clinical data capture can improve overall quality of all data managed by the EHR system
  • Potential to perform more trials with same level of in-house resource due to efficiency in trial management
  • Investigators will access their data through the use of a single and familiar EHR rather than through different sponsor/vendor developed front-ends, reducing training and ongoing support issues
  • Efficiency in presentation of patients' entire medical history, including data from clinical trial participation
  • Standards will enable data collection and integration to be more consistent and investigators will have a common understanding with regard to data definitions and format when dealing with multiple sponsors

Benefits to regulatory authorities

  • With a nationwide network, regulatory authorities could have the capability to review and audit sites' electronic source data against the data provided by the sponsor, thus reducing need for actual site visits by auditors while giving more transparency to the authorities
  • Refocus workload—the reduction of paperwork will allow for auditors to focus more on areas
  • Facilitated audit trail—standard audit trail information for review with a submission

Benefits to sponsor/bio-pharmaceutical industry

  • With the ability to compare safety data from a clinical trial to a much larger baseline (i.e. all EHR patients), there is a potential for improved analysis and projection of long-term safety. This can be accomplished through the sponsor's ability to do large retrospective trials to identify potential safety issues or review post-market product use, via access to information on patients who are using these products. Such retrospective trials would need to be in compliance with patient privacy regulations. New regulations may be required to address how aggregate data can be accessed and by whom.
  • Better access to target patient populations
  • Ease of study execution
  • Utilisation of standardised EHR/EDC components
  • As data transferred to research is a transaction copy of the source data no source data verification (SDV) will be required and queries will be reduced
  • Eliminates redundant computer systems and overhead
  • Application and hardware support, helpdesk, and training will be reduced
  • Archiving requirements will be significantly reduced
  • More of the trial master file will be electronic
  • Sites will already hold research data (as source), therefore, preparation of an archive copy for retention at the site may not be required
  • Pharmacy and patient records will be integrated within the EHR environment allowing drug accountability to be performed electronically via electronic access to dispensing and usage, monitoring of supplies, automated ordering, etc. Randomisation to treatment would be handled external to the EHR
  • Transcription errors are reduced or eliminated
  • EHR/EDC will lead to improved efficiencies with regard to time saving and can contribute to reduced cost in clinical trial execution. This will be achieved through elimination of redundant processes
  • Collect data in a format that lends itself to integration for submission
  • Potential to reference data, required supporting the clinical research, maintained and stored on the EHR rather than duplicating it in the sponsor's database (e.g., medical history, prior medication and procedures). Data necessary to prove efficacy and safety would still exist within the sponsor's submission datasets as well as the EHR.
  • Potential investigator list is expanded to include any physician with a certified EHR/EDC system.

Impact on data management

What do you need to do as a Data Manager/CRA/Programmer/QA personal to prepare for the future of data management?

Education and involvement—you need to educate yourself on what is going on in industry by attending conferences, webinars and other training sessions to learn about what is changing, developing and going out to pasture. Look outside of the usual data management box to see the other potential influences on the profession.

Following is an analysis about potential change/impact on the current clinical research roles and responsibilities that may evolve because of EHR/EDC integration—

1. Roles and responsibilities in all areas will evolve—

  • Clinical Research Associate (CRA)— The traditional work of the CRA will migrate into more of a site relationship management role. The EHR/EDC system removes the need for much of the CRA's time to be spent checking and managing paper CRFs allowing time on-site to be spent more effectively providing protocol and safety training, ensuring GCP compliance, etc. More complex interrogation of the EHR may allow the detection of omitted information such as non-compliance with exclusion criteria, non-reporting of prohibited concomitant medications, etc.
  • Data manager—This role changes to be far more site oriented, as data managers become the liaison between the data and the site staff communicating primarily via the EHR/EDC system. Preparation of ongoing reports for safety and review purposes and programming of extraction algorithms may move this toward a more technical role. New tasks might involve transferring research data back to EHR (e.g., laboratory data). In addition, data managers will have more involvement in protocol development as data definitions will need to be built into the protocol to assist ethics committees/IRBs in reviewing data collection requirements and to enable the development trial-specific EHR modules.
  • Information Technology (IT) support personnel—IT staff will need to be more aware of the total process of clinical trials from eSource through submissions. They will need to be more involved in defining the study protocol, as it will additionally need to specify electronic methods of data collection and identify electronic source.
  • Quality Assurance—QA must audit EHR/EDC systems to ensure appropriate controls exist such that investigators can be accountable for the integrity of the data (eSource) they provide.

2. The informed consent process will change. This will include all that are involved in the process (e.g., sponsor, site, patients and IRB/ethics committees)—

  • Data is moving to patient ownership. The informed consent documentation will need to be adapted to collect patient approval for clinical trial participation
  • Informed consent can be given electronically
  • Some cost may be shifted due to a shift in some responsibilities for activities such as data hosting, on-site validation (data/system), trial module development/configuration

4. Review of data for fraud will change—

  • Fraudulent data will likely be reduced (never eliminated) as sponsors will be able to monitor the timeliness of the data entry and any changes
  • Since the EHR is usually accessible to many medical and nursing staff, it is less vulnerable to fraudulent changes by an individual
  • The sponsor will look for data trends, in order to detect fraud

So what's at stake here? It's the time to re-establish the value proposition for data management/EDC within your organisation. You can choose to take an active role, or to let it happen to you. Actively clarify your goals to reduce stress, focus energies, simplify decisions and prepare for success. Forward-thinking data managers will continue to be invaluable contributors in the growth and success of clinical research. Be one of them and be ready for the next generation of electronic data capture!

(The author is senior product manager at Oracle Life Sciences Applications. He can be reached at subbaraju.sagi@oracle.com)

 


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