Electronic data capture

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An electronic data capture (EDC) system is a computerized system designed for the collection of clinical data in electronic format for use mainly in human clinical trials. [1] EDC replaces the traditional paper-based data collection methodology to streamline data collection and expedite the time to market for drugs and medical devices. EDC solutions are widely adopted by pharmaceutical companies and contract research organizations (CRO).

Contents

Typically, EDC systems provide:

EDC systems are used by life sciences organizations, broadly defined as the pharmaceutical, medical device and biotechnology industries in all aspects of clinical research, [2] but are particularly beneficial for late-phase (phase III-IV) studies and pharmacovigilance and post-market safety surveillance.

EDC can increase data accuracy and decrease the time to collect data for studies of drugs and medical devices. [3] The trade-off that many drug developers encounter with deploying an EDC system to support their drug development is that there is a relatively high start-up process, followed by significant benefits over the duration of the trial. As a result, for an EDC to be economical the saving over the life of the trial must be greater than the set-up costs. This is often aggravated by two conditions:

  1. that initial design of the study in EDC does not facilitate the decrease in costs over the life of the study due to poor planning or inexperience with EDC deployment; and
  2. initial set-up costs are higher than anticipated due to initial design of the study in EDC due to poor planning or experience with EDC deployment.

The net effect is to increase both the cost and risk to the study with insignificant benefits. However, with the maturation of today's EDC solutions, much of the earlier burdens for study design and set-up have been alleviated through technologies that allow for point-and-click, and drag-and-drop design modules. With little to no programming required, and reusability from global libraries and standardized forms such as CDISC's CDASH, deploying EDC can now rival the paper processes in terms of study start-up time. [4] As a result, even the earlier phase studies have begun to adopt EDC technology.

History

EDC is often cited as having its origins in remote data entry (RDE) software, which surfaced in the life sciences market in the late 1980s and early 1990s. [5] However, its origins might be tracked to a contract research organization known then as Institute for Biological Research and Development (IBRD). Drs. Nichol, Pickering, and Bollert offered "a controlled system for post-marketing surveillance (PMS) of newly approved (NDA) pharmaceutical products," with surveillance data being "entered into an electronic data base on site" at least as early as 1980. [6]

Clinical research data—patient data collected during the investigation of a new drug or medical device is collected by physicians, nurses, and research study coordinators in medical settings (offices, hospitals, universities) throughout the world. Historically, this information was collected on paper forms which were then sent to the research sponsor (e.g., a pharmaceutical company) for data entry into a database and subsequent statistical analysis environment. [1] [7] [8] However, this process had a number of shortcomings: [5] [8]

To address these and other concerns, RDE systems were invented so that physicians, nurses, and study coordinators could enter the data directly at the medical setting. By moving data entry out of the sponsor site and into the clinic or other facility, a number of benefits could be derived: [5]

These early RDE systems used "thick client" software—software installed locally on a laptop computer's hardware—to collect the patient data. The system could then use a modem connection over an analog phone line to periodically transmit the data back to the sponsor, and to collect questions from the sponsor that the medical staff would need to answer. [5]

Though effective, RDE brought with it several shortcomings as well. The most significant shortcoming was that hardware (e.g., a laptop computer) needed to be deployed, installed, and supported at every investigational (medical) site. [8] This became expensive for sponsors and complicated for medical staff. Usability and space constraints led to a lot of dissatisfaction among medical practitioners. With the rise of the internet in the mid-1990s, the obvious solution to some of these issues was the adoption of web-based software that could be accessed using existing computers at the investigational sites. EDC represents this new class of software.

Current landscape

The EDC landscape has continued to evolve from its evolution from RDE in the late 1990s. Today, the market consists of a variety of new and established software providers. Many of these providers offer specialized solutions targeting certain customer profiles or study phases. Modern features of EDC now include features like cloud data storage, role-based permissions, and case report form designers, [1] as well as clinical trials analytics, interactive dashboards, and electronic medical record integration.

Future

In 2013, the U.S. Food and Drug Administration (FDA) introduced its eSource guidance, which suggests methods of capturing clinical trial data electronically from the very beginning and moving it to the cloud, as opposed to EDC's more traditional method of capturing data initially on paper and transcribing it into the EDC system. [9] [10] Adoption of eSource was initially slow, with the FDA producing a webinar in July 2015 to further promote the guidance. [9] Efforts like the TransCelerate eSource Initiative (in 2016) have been founded "to facilitate the understanding of the eSource landscape and the optimal use of electronic data sources in the industry to improve global clinical science and global clinical trial execution for stakeholders." [10] A 2017 study by the Tufts Center for the Study of Drug Development suggested that with the following three years a "majority of [surveyed clinical information] companies" (growing from 38 percent to 84 percent) planned to incorporate eSource data. [11] With 87 percent of research sites (2017) stating that eSource would be "helpful" or "very helpful" if integrated with today's EDC, [12] a shift away from EDC (or EDC taking a more complementary role) may be possible.

See also

Related Research Articles

<span class="mw-page-title-main">Clinical trial</span> Phase of clinical research in medicine

Clinical trials are prospective biomedical or behavioral research studies on human participants designed to answer specific questions about biomedical or behavioral interventions, including new treatments and known interventions that warrant further study and comparison. Clinical trials generate data on dosage, safety and efficacy. They are conducted only after they have received health authority/ethics committee approval in the country where approval of the therapy is sought. These authorities are responsible for vetting the risk/benefit ratio of the trial—their approval does not mean the therapy is 'safe' or effective, only that the trial may be conducted.

<span class="mw-page-title-main">Health informatics</span> Computational approaches to health care

Health informatics is the study and implementation of computer structures and algorithms to improve communication, understanding, and management of medical information. It can be view as branch of engineering and applied science.

A hospital information system (HIS) is an element of health informatics that focuses mainly on the administrational needs of hospitals. In many implementations, a HIS is a comprehensive, integrated information system designed to manage all the aspects of a hospital's operation, such as medical, administrative, financial, and legal issues and the corresponding processing of services. Hospital information system is also known as hospital management software (HMS) or hospital management system.

<span class="mw-page-title-main">Electronic health record</span> Digital collection of patient and population electronically stored health information

An electronic health record (EHR) is the systematized collection of patient and population electronically stored health information in a digital format. These records can be shared across different health care settings. Records are shared through network-connected, enterprise-wide information systems or other information networks and exchanges. EHRs may include a range of data, including demographics, medical history, medication and allergies, immunization status, laboratory test results, radiology images, vital signs, personal statistics like age and weight, and billing information.

Pharmacovigilance, also known as drug safety, is the pharmaceutical science relating to the "collection, detection, assessment, monitoring, and prevention" of adverse effects with pharmaceutical products. The etymological roots for the word "pharmacovigilance" are: pharmakon and vigilare. As such, pharmacovigilance heavily focuses on adverse drug reactions (ADR), which are defined as any response to a drug which is noxious and unintended, including lack of efficacy. Medication errors such as overdose, and misuse and abuse of a drug as well as drug exposure during pregnancy and breastfeeding, are also of interest, even without an adverse event, because they may result in an adverse drug reaction.

The Clinical Data Interchange Standards Consortium (CDISC) is a standards developing organization (SDO) dealing with medical research data linked with healthcare, to "enable information system interoperability to improve medical research and related areas of healthcare". The standards support medical research from protocol through analysis and reporting of results and have been shown to decrease resources needed by 60% overall and 70–90% in the start-up stages when they are implemented at the beginning of the research process.

A remote data entry (RDE) system is a computerized system designed for the collection of data in electronic format. The term is most commonly applied to a class of software used in the life sciences industry for collecting patient data from participants in clinical research studies—research of new drugs and/or medical devices.

Postmarketing surveillance (PMS), also known as post market surveillance, is the practice of monitoring the safety of a pharmaceutical drug or medical device after it has been released on the market and is an important part of the science of pharmacovigilance. Since drugs and medical devices are approved on the basis of clinical trials, which involve relatively small numbers of people who have been selected for this purpose – meaning that they normally do not have other medical conditions which may exist in the general population – postmarketing surveillance can further refine, or confirm or deny, the safety of a drug or device after it is used in the general population by large numbers of people who have a wide variety of medical conditions.

A case report form is a paper or electronic questionnaire specifically used in clinical trial research. The case report form is the tool used by the sponsor of the clinical trial to collect data from each participating patient. All data on each patient participating in a clinical trial are held and/or documented in the CRF, including adverse events.

A clinical data management system or CDMS is a tool used in clinical research to manage the data of a clinical trial. The clinical trial data gathered at the investigator site in the case report form are stored in the CDMS. To reduce the possibility of errors due to human entry, the systems employ various means to verify the data. Systems for clinical data management can be self-contained or part of the functionality of a CTMS. A CTMS with clinical data management functionality can help with the validation of clinical data as well as helps the site employ for other important activities like building patient registries and assist in patient recruitment efforts.

A Clinical Trial Management System (CTMS) is a software system used by biotechnology and pharmaceutical industries to manage clinical trials in clinical research. The system maintains and manages planning, performing and reporting functions, along with participant contact information, tracking deadlines and milestones.

<span class="mw-page-title-main">OpenMRS</span>

OpenMRS is a collaborative open-source project to develop software to support the delivery of health care in developing countries.

A Clinical Research Coordinator (CRC) is a person responsible for conducting clinical trials using good clinical practice (GCP) under the auspices of a Principal Investigator (PI).

The Epidemiology Data Center (EDC) is recognized as an official University Center at the University of Pittsburgh; and is part of the Department of Epidemiology at the University of Pittsburgh Graduate School of Public Health. The EDC was formed in 1980 by Katherine M. Detre, M.D., Dr.P.H., and is currently under the co-direction of Maria Mori Brooks, Ph.D., Steven H. Belle, Ph.D. and Stephen R. Wisniewski, Ph.D.

The following outline is provided as an overview of and topical guide to clinical research:

Patient recruitment includes a variety of services—typically performed by a Patient Recruitment Service Provider—to increase enrollment into clinical trials. Presently, the patient recruitment industry is claimed to total $19 billion per year.

A clinical trial portal is a web portal or enterprise portal that primarily serves sponsors and investigators in a clinical trial. Clinical portals can be developed for a particular study, however study-specific portals may be part of larger, clinical sponsor or Contract Research Organization (CRO) portals that cover multiple trials. A clinical portal is typically developed by a sponsor or CRO to facilitate centralized access to relevant information, documentation and online applications by investigational sites participating in a trial, as well as for the monitors, study managers, data managers, medical, safety and regulatory staff that help plan, conduct, manage and review the trial.

Medidata Solutions is an American technology company that develops and markets software as a service (SaaS) for clinical trials. These include protocol development, clinical site collaboration and management; randomization and trial supply management; capturing patient data through web forms, mobile health (mHealth) devices, laboratory reports, and imaging systems; quality monitor management; safety event capture; and monitoring and business analytics. Headquartered in New York City, Medidata has locations in China, Japan, Singapore, South Korea, the United Kingdom, and the United States.

Clinical data management (CDM) is a critical process in clinical research, which leads to generation of high-quality, reliable, and statistically sound data from clinical trials. Clinical data management ensures collection, integration and availability of data at appropriate quality and cost. It also supports the conduct, management and analysis of studies across the spectrum of clinical research as defined by the National Institutes of Health (NIH). The ultimate goal of CDM is to ensure that conclusions drawn from research are well supported by the data. Achieving this goal protects public health and increases confidence in marketed therapeutics.

<span class="mw-page-title-main">Phases of clinical research</span> Clinical trial stages using human subjects

The phases of clinical research are the stages in which scientists conduct experiments with a health intervention to obtain sufficient evidence for a process considered effective as a medical treatment. For drug development, the clinical phases start with testing for drug safety in a few human subjects, then expand to many study participants to determine if the treatment is effective. Clinical research is conducted on drug candidates, vaccine candidates, new medical devices, and new diagnostic assays.

References

  1. 1 2 3 Hamad, F. (2017). "Chapter 13: Health information systems: Clinical data capture and document architecture". In Urquhart, C.; Hamad, F.; Tbaishat, D.; Yeoman, A. (eds.). Information Systems: Process and Practice. Facet Publishing. pp. 233–53. ISBN   9781783302413 . Retrieved 24 May 2018.
  2. ↑ David Handelsman. "Electronic Data Capture: When Will It Replace Paper?". SAS Institute Inc. Archived from the original on 2009-12-17. Retrieved 2010-09-03.
  3. ↑ Thomas Bart. "Comparison of Electronic Data Capture with Paper Data Collection – Is There Really an Advantage?" (PDF). Business Briefing, Pharmatech. Archived from the original (PDF) on 2013-09-03. Retrieved 2013-02-25.
  4. ↑ Brigitte Walther; Safayet Hossin; John Townend; Neil Abernethy; David Parker; David Jeffries (2011). "Comparison of Electronic Data Capture (EDC) with the Standard Data Capture Method for Clinical Trial Data". PLOS ONE . 6 (9): e25348. Bibcode:2011PLoSO...625348W. doi: 10.1371/journal.pone.0025348 . PMC   3179496 . PMID   21966505.
  5. 1 2 3 4 Hyde, A.W. (1998). "The Changing Face of Electronic Data Capture: From Remote Data Entry to Direct Data Capture". Therapeutic Innovation & Regulatory Science. 32 (4): 1089–1092. doi:10.1177/009286159803200429. S2CID   70356966.
  6. ↑ Nichol, F.R.; Pickering, B.I.; Bollert, J.A. (1980). "Post-marketing surveillance of approved pharmaceuticals in the United States". Contemporary Clinical Trials. 1 (2): 178. doi:10.1016/0197-2456(80)90061-6.
  7. ↑ Walther, B.; Hossin, S.; Townend, J.; et al. (2011). "Comparison of Electronic Data Capture (EDC) with the Standard Data Capture Method for Clinical Trial Data". PLOS ONE. 6 (9): e25348. Bibcode:2011PLoSO...625348W. doi: 10.1371/journal.pone.0025348 . PMC   3179496 . PMID   21966505.
  8. 1 2 3 Waterfield, E. (2000). "Chapter 4: Data Capture". In Rondel, R.K.; Varley, S.A.; Webb, C.F. (eds.). Clinical Data Management. John Wiley & Sons. pp. 75–88. ISBN   9780471983293 . Retrieved 24 May 2018.
  9. 1 2 Neuer, A. (November 2015). "At the Source" (PDF). International Clinical Trials. pp. 40–44. Archived from the original (PDF) on 2 May 2018. Retrieved 24 May 2018.
  10. 1 2 Kellar, E.; Bornstein, S.M.; Caban, A.; et al. (2016). "Optimizing the Use of Electronic Data Sources in Clinical Trials: The Landscape, Part 1". Therapeutic Innovation & Regulatory Science. 50 (6): 682–696. doi: 10.1177/2168479016670689 . PMID   30231749.
  11. ↑ "Industry Research Shows 97% of Companies to Increase Use of Real-world Patient Data for More Accurate Decision-making". Business Wire. 7 November 2017. Retrieved 24 May 2018.
  12. ↑ Nomlzu, R. (29 September 2017). "Getting Your Site Ready for eSource". InSite. CRIO. Archived from the original on 25 May 2018. Retrieved 24 May 2018.
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