Data Sharing and Reuse of Health Data for Research

Abstract

Facilitating the reuse and sharing of electronic health data for research is an important foundation for reengineering and streamlining research processes and will be critical to accelerating learning health cycles and broadening the knowledge that can be used to improve healthcare and patient health outcomes. In this chapter, data sharing refers to sharing data between partners and systems (not necessarily sharing of research results) in ways that preserve the meaning and integrity of the data. A range of ethical, legal, and technical considerations have thus far hindered the development and application of approaches for such reuse and data sharing, in general. However, standards adoption and technical capabilities are progressing, and incentives are now beginning to align to facilitate data sharing. Principles and values of data sharing and the responsible use of data and data standards have been published, and there is recognition of the value of “real-world data” (RWD) to generate additional evidence upon which to base clinical decisions. These will require broad adoption, adherence, communication, and collective support to positively transform research processes and informatics.

Participants in clinical research studies typically expect and want their data to be shared widely and appropriately such that we can all learn. Based on learning from research results, it is expected that patient care will be improved. This is the basis for learning health systems (LHS), in which research is clearly a vital component. The knowledge gained from sharing the results of research can inform healthcare and clinical decisions to complete the learning cycle.

This chapter will describe the benefits and implementation considerations of reusing health data, particularly that from electronic health records (EHR), for clinical research, bio-surveillance, pharmacovigilance, outcome assessments, public health, quality reporting, and other research-related studies. Use cases are provided to illustrate the positive impact that data reuse and sharing will have for patients, clinicians, research sponsors, regulatory agencies, insurers, and all involved in LHS. Consensus-based principles for data sharing, technical aspects, and business requirements are also provided, along with specific examples of data sharing collaborations, initiatives, and tools. In the future, we hope that research will become embedded within health systems and that organizations will continue to embrace, harmonize, and broadly adopt standards and technologies to meet this challenge.

Appendix

Examples of Collaborations, Initiatives, and Tools Related to Data Sharing in Clinical Research

In this section, we describe some important (national and global) collaborations, initiatives, and tools related to reusing clinical data for purposes of streamlining research. This list is not intended to be exhaustive.

ARO Council and Global Network	The Academic Research Organization Council and Global Network brings together Japan, Taiwan, Singapore, South Korea, Europe, and the USA with strategic initiatives toward harmonization and standardization of data to streamline clinical research and accelerate academic innovation to overcome intractable diseases [46].
ASTER	The Adverse Drug Event Spontaneous Triggered Event Reporting (ASTER) study was a proof of concept for the model of using data from electronic health records to generate automated safety reports, replacing the current system of manual ADE reporting. The CDISC-IHE Retrieve Form for Data Capture (RFD) formed the basis for the data sharing from EHRs to directly populate MedWatch forms. The time to report an AE was reduced from 34 min to less than 1 min [41].
BRIDG Model	The Biomedical Research Integrated Domain Group (BRIDG) Model is an information model that represents the domain of protocol-driven research. It provides a shared view of the concepts of basic, preclinical, clinical, and translational research, including genomics. This information model is an ISO, CDISC, and HL7 standard. It supports development of data interchange standards and technology solutions that can enable semantic interoperability for biomedical and clinical research and bridges research and the healthcare arena. Currently there is work being done to develop HL7 FHIR research resources, which will be harmonized with the BRIDG model [47, 48].
CAMD	Coalition Against Major Diseases (CAMD) is an initiative of the Critical Path Institute (C-Path). “CAMD is a public-private partnership aimed at creating new tools and methods that can be applied to increase the efficiency of the development process of new treatments for Alzheimer’s disease (AD) and related neurodegenerative disorders with impaired cognition and function. CAMD has the following areas of focus: (1) qualification of objective biomarkers, including both biochemical and observational digital biosensor measures of health, (2) development of common data standards, (3) creation of integrated databases for clinical trials data, and (4) development of quantitative model-based tools for therapeutics development” [49].
CDISC	Clinical Data Interchange Standards Consortium (CDISC) is a standards development organization focused on developing global data standards for clinical research. Its mission is to develop and support global, platform-independent data standards that enable information system interoperability to improve medical research and related areas of healthcare. CDISC has successfully collaborated with multiple other stakeholder groups to initiate and develop industry-accepted standards, such as BRIDG. CDISC standards are now required for data in regulatory submissions to FDA and Japan’s PMDA [50].
C-Path	The Critical Path Institute (C-Path) is a nonprofit, public-private partnership with the Food and Drug Administration (FDA). C-Path’s aim is to accelerate the pace and reduce the costs of medical product development through the creation of new data standards, measurement standards, and method standards that aid in the scientific evaluation of the efficacy and safety of new therapies.”CAMD is an example of one of C-Path’s projects, many of which are executed through consortia [51].
CFAST	The Coalition For Accelerating Standards and Therapies (CFAST) was initiated by C-Path and CDISC to develop global therapeutic area standards that augment the foundational standards for clinical research. Contributing organizations included FDA, EMA, PMDA, NCI, IMI, and TransCelerate BioPharma [52]. The resulting standards are published in CDISC Therapeutic Area User Guides and through CDISC SHARE, with specifications cited in the FDA and PMDA Data Standards Catalogs.
Common Protocol Template	The Common Protocol Template (CPT), developed by TransCelerate Biopharma Inc. in collaboration with stakeholders, is a harmonized and streamlined approach to the format and content of clinical trial protocols. It aims to ease interpretation by the study sites and global regulatory authorities while enabling downstream automation of many clinical processes and alignment to industry data standards. It has now been harmonized with an FDA/NIH protocol template and will become an ICH project [53].
CORBEL	The CORBEL (Coordinated Research Infrastructures Building Enduring Life-Science Services) consortium is an 11 major new biological and medical research infrastructures (BMS RI) in Europe, which plan to create a platform for harmonized user access to technologies, samples, and data services required for biomedical research [54].
DataSphere	Project DataSphere LLC, which is not-for-profit initiative of the CEO Roundtable on Cancer’s Life Sciences Consortium (LSC), has developed a free digital library/data laboratory to share and analyze patient-level comparator arm data from phase III cancer clinical trials. “Prostate Dream Cancer Challenge confirmed that an open-access model empowers global communities of scientists from diverse backgrounds and promotes crowd-sourced solutions to important clinical problems” [55, 56].
Duke University eSource study	A proof-of-concept study that aimed to quantify the benefits of the secondary use of EHR data for clinical research. Findings showed a 37% reduction in time, significant reduction in resource needs and zero data quality issues [23].
ECRIN	The European Clinical Research Infrastructure Network (ECRIN) provides investigators support from trial preparation to implementation navigating the fragmented health and legal systems of individual European countries in order to conduct multinational trials. ECRIN led the CORBEL project on consensus-based principles for sharing clinical trial data, results of which were published in December 2017 in the British Medical Journal Open [57].
EHR4CR	“The EHR4CR project, funded by the Innovative Medicines Initiative (IMI) and the European Federation of Pharmaceutical Industries and Associations (EFPIA) in collaboration with 34 partners (academic and industrial) and 2 subcontractors is one of the largest public-private partnerships aiming at providing adaptable, reusable and scalable solutions (tools and services) for reusing data from Electronic Health Record systems for Clinical Research” [58].
ELIXIR	ELIXIR “unites Europe’s leading life science organizations in managing and safeguarding the increasing volume of data being generated by publicly funded research. It coordinates, integrates and sustains bioinformatics resources across its member states and enables users in academia and industry to access services that are vital for their research.” ECRIN and ELIXIR are both part of the CORBEL consortium [59].
Health Level Seven (HL7)	Health Level Seven is an international standards organization dedicated to the development and interoperability of health information through products such as V2 and Fast Healthcare Interoperability Resources (FHIR) [10].
Healthcare Link and IHE-CDISC integration profiles	Under the leadership of Rebecca Kush and Landen Bain, CDISC launched the Healthcare Link Initiative to create a means of better linking healthcare and clinical research through standards. As a part of Healthcare Link, Integrating the Health Enterprise (IHE) and CDISC created the Retrieve Form Data Capture (RFD) and Retrieve Protocol for Execution (RPE) standards that a majority of electronic health record systems were configured for as part of Meaningful Use (MU) requirements [16, 60]. BRIDG also supports the Healthcare Link philosophy.
i2b2	Informatics for Integrating Biology and the Bedside (i2b2) is an NIH-funded National Center for Biomedical Computing (NCBC) aimed to develop an informatics framework based on Massachusetts General Hospital’s Research Patient Data Registry (RPDR) [61].
IDDO	The Infectious Diseases Data Observatory (IDDO) builds upon the success of WorldWide Antimalarial Resistance Network (WWARN) to provide a global collaborative data platform for the benefit of clinical care and research of communicable diseases [62].
I~HD	The European Institute for Innovation Through Health Data (I~HD) arose out of the IMI’s Electronic Health Records for Clinical Research (EHR4CR), SemanticHealthNet, and other projects to become an organization of reference and does so through services such as the Interoperability Asset Register, an online service that contains documents, templates, clinical models, technical specifications, and software pertaining to the interoperability of health information [63].
IMI	Innovative Medicine Initiative is a public- private partnership between the European Union and European Federation of Pharmaceutical Industries and Associations (EFPIA) that has resulted in over 100 projects generating 60+ project tools and 2000+ publications [64].
LHC	The goal of the Learning Health Community (LHC) is to improve the health of the individual and population through rapid cycle improvements to a learning health system (LHS) from the information and knowledge gained from data collected from clinical research, individuals, population health, and care delivery. The LHC will leverage existing opportunities such as meaningful use and personal health records and strive to create a harmonization among stakeholders to facilitate data sharing for the good of the individual and the population, promising to empower personalized medicine [44, 65].
OHDSI	Observational Health Data Sciences and Informatics (OHDSI ) strives to share observational healthcare data through common data models and development of tools for data analytics and visualization [66]. OHDSI arose from initial work to develop the OMOP model, which is no longer an active project. The OMOP Common data Model is maintained by OHDSI.
OneMind	OneMind is dedicated to disseminating donor funding for brain disease and injury research including the data standardization, curation, and mining necessary for regulatory approvals. Standardization of the data from two mega-studies conducted at separate NIH institutes (National Institute of Neurological Disorders and Stroke and National Institute of Mental Health) allows for the data to be merged into a “collaboratory” at the completion of the studies [67].
PCORI	The Patient-Centered Outcomes Research Institute funds comparative clinical effectiveness research in order to change clinical practice and improve patient outcomes. The PCORI program consists of five areas of focus: clinical effectiveness and decision science, healthcare delivery and disparities research, evaluation and analysis, engagement, and research infrastructure known as PCORnet [68].
SHARE	The Shared Health and Research Electronic (SHARE) library is a metadata repository and associated tools and services that enables users of CDISC to access the standards in various formats that are human- and machine-readable [27].
Sentinel	The Food and Drug Administration’s (FDA) Sentinel Initiative is a national electronic system that enables researchers to proactively monitor the safety of FDA-regulated medical products after they reach the market complementing the FDA’s Adverse Event Reporting System. This system compiles data from multiple sources such as claims data, registries, and EHRs using a distributed data model that allows the ability to maintain patient privacy and monitor the safety of regulated products [69].
SMART on FHIR	Harvard Medical School and Boston Children’s Hospital initiated an interoperability project in 2010, with a goal of “developing a platform to enable medical applications to be written once and run unmodified across different healthcare IT systems.” This was named Substitutable Medical Applications and Reusable Technologies (SMART). In 2013, the platform was modified to adopt the FHIR standard that was emerging at that time. The new platform was called “SMART on FHIR”.
TRANSFoRm	The Translational Research and Patient Safety in Europe (TRANSFoRm) project is the European learning health system initiative aimed to develop a digital infrastructure, method, model, and standards for three areas of focus of a LHS: use of biobank data sets develop genotype and phenotypes for epidemiological studies, embedding regulated clinical trials within the EHR with a focus on patient-reported outcome measures (PROM), and decision support tools for clinical care [70, 71].
Vivli	Designed to reduce barriers to data sharing in clinical research, Vivli, acting as an independent broker, created an independent data repository, cloud-based analytics platform and search engine, based on the gatekeeper model, where industry, academia, patient organizations, government, and not-for-profit organization’s researchers can share, access, and host data [72].