In order to focus development priorities we came up with several use cases for adoption of EHR data in clinical research; some of these are more prospective, but seem as logical conclusions to the full scale integration between the different realms. This is the primary opportunity. The Swivel Chair definition arises from the requirement to effectively enter data twice; once in the primary healthcare system and again in the EDC system. This is required because of a lack of effective integration between the different systems.
Any solution that will succeed will need to present a hybrid approach to combining the data from EHR systems with that entered by the site themselves. Protocol feasibility is the collection of a pool of anonymised patient data from EHR systems, A subset of the data is available for querying, so that sponsors can validate the choice of eligibility criteria for directional information; few or none results implies that using the existing criteria the sites and thereby the sponsor are going to have difficulty meeting recruitment targets.
Again, this information is purely directional. For example, it won't give information about projected recruitment rates, as an example. The primary motivation for this use case is to proactively avoid protocol amendments.
This is one of the more developed use cases across the industry; subject recruitment remains a challenging and expensive part of clinical trial execution.
This use case is based around a pool of consented patient data that can be queried to identify subjects and sites where the study will be able to recruit successfully.
Initiatives such as Sync4Science present an interesting opportunity as patients can consent to share their data for the purposes of investigational research—this can only improve the opportunities for incorporating these subjects in clinical trials. Targeted phenotypic identification of patient cohorts using EHR systems will facilitate faster recruitment by both identifying more suitable subject candidates and reducing the number of subjects failing screening procedures for clinical studies.
Embi et al. This is an interesting use case that will foster a closer relationship between the sponsor and the sites. In the US there are large fines for billing research costs to Medicaid; the use case here presents a mechanism for the site to be able to access the list of procedures that are per protocol and thereby can be passed on to the sponsor for payment. This is a more speculative use case; in simple terms it involves preparing a protocol and then gathering information from historical EHR records.
This is of interest for Observational research where signals may be exposed based on larger patient data sources. Initiatives such as Sync4Science will be an important tool for this in the future; this is because the Sync4Science applies the consent directly to the Patient and they remain in control of their data. This is another speculative use case, but one that we expect to become more operational in the next years.
Simply put, the genotypic information for a pool of patients is aggregated and then clustered on the basis of patterns of Single Nucleotide Polymorphisms SNP. The phenotypic information for the different clusters are then compared where the data is sourced for historic EHR records.
This will be increasingly important off the back of initiatives around personalized medicine e. GWAS may help in identifying different drug response based on an individual's genome. An example of this is the 'super-responder' where a subject has an aberrant response to a medication; in a clinical trial the response may be classified as an outlier and not be included in the study report.
A main component of EHR systems is the ability to handle billing information for reimbursement by insurance companies. We'll keep this going with a few more posts. Whether EHRs can be successfully applied to the conventional drug development in pivotal, registration trials remains to be seen and will depend on demonstration of data quality and validity, as well as realization of expected efficiencies.
The CRT is a strategic forum for high-level dialogues between academia, regulators, industry, and ESC leadership to identify and discuss key strategic issues for the future of cardiovascular health in Europe and other parts of the world. We acknowledge Colin Freer for his participation in the meeting.
The opinions expressed in this paper are those of the authors and cannot be interpreted as the opinion of any of the organizations that employ the authors. Martin R. Jude Medical, and Pfizer. Juuso Blomster: Astra Zeneca employee. Sylvie Duclaux: None. Ian Ford: None. Fleur Fritz: None. Samantha Goldman: None. Salim Janmohamed: GSK employee and shareholder. Mark Leenay: Employee of Optum. Alexander Michel: Bayer employee and shareholder.
Seleen Ong: Employee of Pfizer. Jill Pell: None. Mary Ross Southworth: None. Martin Thoenes: Employee of Edwards Lifesciences.
National Center for Biotechnology Information , U. Clinical Research in Cardiology. Clin Res Cardiol. Published online Aug Cowie , 1 Juuso I. Blomster , 2, 3 Lesley H. Juuso I. Lesley H.
Seleen Ong 13 Pfizer Ltd. Jill P. Author information Article notes Copyright and License information Disclaimer. Cowie, Phone: , Email: ku. Corresponding author. Received May 4; Accepted Aug 5. This article has been cited by other articles in PMC. Abstract Electronic health records EHRs provide opportunities to enhance patient care, embed performance measures in clinical practice, and facilitate clinical research. Keywords: Electronic health records, Clinical trials as topic, Pragmatic clinical trials as topic, Cardiovascular diseases.
Introduction Electronic health records EHRs provide opportunities to enhance patient care, to embed performance measures in clinical practice, and to improve the identification and recruitment of eligible patients and healthcare providers in clinical research.
Overview of electronic health records Broadly defined, EHRs represent longitudinal data in electronic format that are collected during routine delivery of health care [ 3 ]. Table 1 Electronic health records in research. Open in a separate window. Electronic health records for research applications Epidemiologic and observational research EHR data have been used to support observational studies, either as stand-alone data or following linkage to primary research data or other administrative data sets [ 3 , 11 — 14 ].
Safety surveillance and regulatory uses Active post-marketing safety surveillance and signal detection are important, emerging applications for EHRs, because they can provide realistic rates of events unlike spontaneous event reports and information on real-world use of drugs [ 20 ]. Prospective clinical research National patient registries that contain data extracted from the EHR are an accepted modality to assess guideline adherence and the effectiveness of performance improvement initiatives [ 26 — 33 ].
Challenges to using electronic health records in clinical trials and steps toward solutions Challenges to using EHRs in clinical trials have been identified, related to data quality and validation, complete data capture, heterogeneity between systems, and developing a working knowledge across systems Table 2.
Table 2 Challenges of using electronic health records in research. Problem Example Potential Solutions Data quality and validation Selecting measurement of interest for a clinical trial when multiple measurements are available e. Data quality and validation Data quality and validation are key factors in determining whether EHRs might be suitable data sources in clinical trials. Timely access to electronic health record data The potential for delays in data access is an important consideration when EHRs are used in clinical trials.
Heterogeneity between systems Patients may be treated by multiple healthcare providers who operate independently of one another. Data security and privacy Privacy issues and information governance are among the most complex aspects of implementing EHRs for clinical research, in part because attitudes and regulations related to data privacy vary markedly around the world.
System capabilities EHRs for use in clinical research need a flexible architecture to accommodate studies of different interventions or disease states. Sustainability The sustainability of EHRs in clinical research will largely depend on the materialization of their promised efficiencies. Role of stakeholders To make the vision of EHRs in clinical trials a reality, stakeholders should collaborate and contribute to the advancement of EHRs for research.
Table 3 Role and influence of stakeholders in advancing the use of electronic health records in clinical research. Stakeholder Contribution Professional societies Training and education Global platform for education at annual meetings or congresses Leverage industry support Public education to foster public support Transform EORP into a prospective trial instrument; generate support from industry who may use this resource for future trials Develop data standards CARDS-revisited Organize working groups charged with generating common EHR templates or data sets, or achieving agreement on minimum standards Lobby regulatory agencies and industry sponsors Clinical trialists and industry Engage other collaborators e.
Conclusion Electronic health records are a promising resource to improve the efficiency of clinical trials and to capitalize on novel research approaches. Conflict of interest Martin R. References 1. Improving clinical trials for cardiovascular diseases: a position paper from the Cardiovascular Roundtable of the European Society of Cardiology. Eur Heart J. Sensible approaches for reducing clinical trial costs. Clin Trials.
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