At present, there is a lack of a unified and canonical global definition for Real-World Data. The general consensus is that Real-World Data encompasses day-to-day data collection practices from patients in a medical setting. This could also include data collected in randomized or controlled clinical trial settings.

Regulatory agencies similarly differ in their definition and approach to Real-World Data:

Food and Drug Administration: United States

The Food and Drug Administration (FDA) defines Real-World Data (RWD) as any and all healthcare data related to patient health and care delivery. This includes any data from or contained within electronic health records (EHR), billing claims, disease registries, consumer wearables, and remote diagnostic or monitoring equipment.

European Medicines Agency

The European Medicines Agency (EMA) has a wider definition of RWD. It refers to health-related data from a diverse population, from sources like medical records, registries, biobanks, administrative, surveys, observational studies, insurance, mobile apps, and more.

The EMA has yet to release a regulatory framework for RWD, but actively promotes its use within clinical studies and clinical decision-making. The EMA is focused on tackling globalized medicine and the data protection risks it poses across supply chains and research and development, particularly through external EU network regulators for medical datasets, services, and products that exit and enter the European Economic Area (EEA). Furthermore, the EMA is working closely with regulators like the World Health Organization (WHO) and non-EU regulators to build international capacity.

Pharmaceuticals and Medical Devices Agency: Japan

The Japanese Pharmaceuticals and Medical Devices Agency (PMDA) more loosely defines RWD as data relating to patient health status and care delivery which is routinely collected from a variety of sources[1]. This includes data from the National Claims Database (NDB), which covers 120 million Japanese citizens, and the Clinical Innovation Network (CIN), which targets rare disease research and development[2].

Central Drugs Standard Control Organization: India

The Indian Central Drugs Standard Control Organization (CDSCO) offers little information on their website concerning Real-World Data, namely due to a lack of regulation by the central government. India is, however, making progress with digitalizing its healthcare system and regulating patient medical data with the Digital Information Security in Healthcare Act (DISHA)[3]. This regulation is currently under public consultation and refers to RWD as “Digital Health Data”.

DISHA defines Real-World Data as information concerning the physical or mental health of individuals; information around health service provision; information concerning organ or bodily substance donations; information on testing or examination of organs and bodily substances; information collected during the course of health service delivery; and information on the clinical establishment accessed by the individual[4].

Ministry of Health: Israel

The Israeli Ministry of Health (MOH) has started drafting legislation around medical data protection with Resolution 3079[5].

The legislation refers to health data that directly or indirectly relates to a person’s overall physical or mental health, including smoking, exercise regimens, and diet; identifying items such as first and last names, identity documents, driver’s license numbers, facial images, or contact details; identifiable information that may include health data or identifying items that can be cross-referenced to reveal an identity; and anonymized data that has been sufficiently de-identified for use in research and clinical trials.

International Cooperation Around Real-World Data

Despite differing approaches and definitions between medical regulators across countries, there is plenty of international cooperation around Real-World Data.

Pharmaceutical Inspection Co-operation Scheme (PIC/S)

The Pharmaceutical Inspection Co-operation Scheme (PIC/S)[6] is driving international development, implementation and maintenance of harmonized good manufacturing practice (GMP) standards and quality medical systems. PIC/S members operate together in parallel using standardized inspection procedures to increase the consistency and safety of manufactured pharmaceuticals, with more than 50 participating authorities across Europe, Africa, America, Asia, and Oceania regions[7].

Ministry of Health, Labor, and Welfare Pharmaceutical and Medical Devices Act (MHLW, PMD)

The Japanese Ministry of Health, Labor and Welfare (MHLW) Pharmaceutical and Medical Devices (PMD) Act is pioneering an international strategic plan for the promotion of regulatory science and global capacity building[8]. This uses Real-World Data sourced from the International Medical Device Regulators Forum (IMDRF) to minimize the reassessment of devices that have a proven efficacy but have undergone slight changes. It also simplifies regulatory approval for foreign medical devices through the foreign manufacturer registration (FMR), where classifications I to IV dictate whether reviews or assessments are necessary. The classifications aim to define generic definitions and classifications for medical devices, minimizing the regulatory assessment burden for a faster go-to-market.

Health Canada

Health Canada holds memberships across numerous international medical regulatory bodies. This includes the International Coalition of Medicines Regulatory Authorities (ICMRA), the International Council for Harmonization (ICH), the Canada-United States Regulatory Cooperation Council (RCC) and Medical Device Single Audit Program (MDSAP). Health Canada engages internationally to leverage resources and knowledge, ensure consistency with international regulatory practices and standards, and reduce risks associated with therapeutics marketed in Canada[9]. All these bodies share Real-World Data with the aim of improving international regulatory strategies.

World Health Organization (WHO)

The World Health Organization (WHO) offers direct access to Real-World Evidence (RWE) generated via Real-World Data through the World Health Data Platform. Internationally relevant datasets are visualized and readily available to enable greater international medical collaboration. The WHO follows a SCORE[10] system of survey, count, optimize, review, and enable to gather RWD, quantify results for RWE, optimize and cleanse health services data, review global progress or performance, and enable the leveraging of data for governmental policy and action.

Reduced Costs and Faster Time-to-Market with Real-World Data for BioPharma

RWD is mainly used by medical artificial intelligence (AI) application developers and drug manufacturers to derive Real-World Evidence (RWE). In that sense, RWD can be viewed as the raw material or fuel source for RWE. Real-World Evidence facilitates AI and drug development through a cost-effective approach that minimizes time-to-market, with most RWE coming via structured clinical trial results. It can also be used to monitor the safety of drugs across treatment lifecycles, and to provide more accurate and reliable health information to patients and the general public.

Edison™ Digital Pharma Solutions is your trusted source for Real-World Data. At present, our team operates across the United States, Canada, the European Union, and the United Kingdom.

European Medicines Agency 5-Year Human Medicines Roadmap

The European Medicines Agency (EMA) has been actively promoting studies on regulatory science and how to apply it to Real-World Data. Moreover, it conducted 88 internal studies and 19 external studies between 2013 and 2019 on RWD and regulatory science.

The EMA is yet to establish a framework, but several publications have been made in this area including a roadmap:

The EMA has established five strategic goals in human medicines[11].

Catalyzing the integration of science and technology during the development of medicines.
Driving collaborative Real-World Evidence (RWE) generation to improve the scientific quality of evaluations.
Promoting patient-centric access to medicines in partnership with international and EEA healthcare systems.
Addressing imminent health threats such as service or pharmaceutical availability and therapeutic challenges.
Enabling and leveraging research and innovations in regulatory science.

Food and Drug Administration Real-World Data and Real-World Evidence Framework

The Food and Drug Administration (FDA) has released a comprehensive RWD and RWE framework in tandem with a Common Data Model Harmonization (CDMH) project[12]. Eight internal studies have been conducted on RWD and RWE usage, with the results guiding the development of an incentive program for RWD and RWE efforts[13].

European Health Data Evidence Network (EHDEN)

Another European initiative is the European Health Data Evidence Network (EHDEN)[14]. The mission is to drive the development of federated networks through a standardized common data model that intelligently orchestrates the administration and distribution of research methodologies. Its end goal is to become a trusted observational research ecosystem that will assist in decision-making to improve patient care and outcomes. To reach this end goal, EHDEN will harmonize more than 100+ million pseudonymized or de-identified healthcare records in the Observational Medical Outcomes Partnership (OMOP) model.

The result is better understanding around clinical outcomes, and the establishment of an open-science collaboration network partnered with academics, industry players, regulators, governments, and non-governmental organizations (NGOs).

Observational Health Data Sciences and Informatic (OHDSI)

The Observational Health Data Sciences and Informatics (OHDSI)[15] program has a mission to improve health by empowering communities to collaboratively generate Real-World Evidence that drives better health decisions and care approaches[16]. It produces a better understanding of health and diseases through a multi-disciplinary collaborative stakeholder network across continents that uses open-source solutions. OHDSI is currently situated at the University of Colombia, and continues the legacy left by the OMOP program[17].

Meanwhile, traditional interventional data collection processes, as seen with randomized controlled trials, mean patients are carefully selected through a set of inclusion and exclusion criteria to be treated at a later date with a specific protocol. The observational Real-World Data, being prospective or retrospective, is based on the recollection of medical data produced during treatment in a clinical setting, where patients may have multiple co-morbidities.

The Edison™ Digital Pharma Solutions Real-World Data View

As previously mentioned, Real-World Data is used to generate Real-World Evidence that assists with the development of medical AI applications and pharmaceuticals. Patient cohorts, from which RWD is collected and RWE is derived, are composed by large volumes of discrete data objects which improve the quality of insight as the diversity of the dataset increases.

Healthcare providers and medical institutions generate large volumes of RWD as they deliver patient care. The vast majority of this data comes from diagnostics and ongoing disease monitoring. As the data is generated, all relevant RWD undergoes a candidacy assessment to determine its potential for secondary usage. This includes projects where the data is collected retrospectively as well as prospectively for ongoing RWD generation by healthcare providers and institutions.

Accessing this data is a challenge. Healthcare provider IT systems are designed to enable data access during the delivery of primary care, with diagnostic devices and software tools following this approach. A lack of governance, technical knowledge, and software tools also reduces their capacity to leverage RWD sources in real-time outside of primary care.

This has a knock-on effect for medical AI developers and pharmaceutical manufacturers, who need RWD to derive RWE but lack the necessary data sources. It is not only data access, but access to institutions who house and distribute RWD in the first place that causes problems.

Even when RWD is readily available, strong governance mechanisms must be in place. Under provisioning data is always preferable to overprovisioning, as additional access can be granted easily, but exposed data is much harder to recover. There are also regional and international regulatory compliance requirements that mandate strong RWD governance.

Extending Access to Real-World Data for AI and BioPharma

GE Healthcare Edison™ Digital Pharma Solutions is extending access to Real-World Data cohorts for medical AI developers and pharmaceutical companies. RWD is the main deliverable, where customers can then derive meaningful RWE to support product and service development.

Edison™ Digital Pharma Solutions’ core values include:

Comprehensive end-to-end data governance throughout the RWD acquisition process for customers and data partners
Management of legal, privacy, and security compliance protocols
Delivering reliable data access services aligned with customer specifications through a cost-effective distribution model

Edison™ Digital Pharma Solutions delivers on these values using a combination of software tools, industry resources, and a highly qualified workforce.

Our Real-World Data Framework

These RWD services rely on a strong legal and privacy framework for RWD that includes the pre-assessment of existing data management processes. A set of project milestones are established to gauge progress and ensure the timely implementation of RWD access. This governs the end-to-end relationship between GE Healthcare and its partners, with strong compliance controls and adherence to GE Healthcare’s Spirit and the Letter policy[18].

Data sourcing and privacy-related controls ensure that the legal frameworks in each country or region are strictly adhered to, including General Data Protection Regulation (GDPR), Privacy Impact Assessments (PIA), and Records of Processing Activities (ROPA). Additional processes include continuous auditing and internal toolkits that incorporate security-by-design (SBD).

Our Program Interactions, Tools, and Resources

The RWD program is closely connected to supplementary activities performed by the Edison™ Digital Pharma Solutions team:

Assessment – The assessment process is a key feature throughout the RWD program that identifies current care pathways and data capabilities. Throughout the assessment, Edison™ Data Partners can gain a better understanding of how institutions manage different care pathways in diverse clinical and technical conditions. Similarly, Data Partners can gain greater clarity on projected operational improvements by learning about the volume of data production, analytics, and data structure gap analysis in detailed reports.
Clinical Library – The Clinical Library is a resource that defines a set of potential use cases for RWD in the context of medical AI development.
SOW Advisory Services – Scope of Work (SOW) advisory services identify partner requirements by providing clinical and technical guidance to establish a scope of work for the project.
Real-World Data Services – Finally, Real-World Data Services consist of data preparation services and data pipeline tools to enable seamless access to Real-World patient cohort data. This includes de-identification, enrichment for less-than-optimal data sources, and packetization for analog-to-digital RWD conversion.

Destination Data with Edison™

Real-World Data and Real-World Evidence go hand-in-hand. The potential for these data sources and insights extends across the entire healthcare continuum, enabling better patient care, advancement in medical AI applications, and expedited research and development for groundbreaking pharmaceuticals.

Step into a world of data clarity by contacting the GE Healthcare Experts at Edison™ Digital Pharma Solutions today.

[1] Chen, Chi-Hsun. 2021. "Using Real-World Data/Evidence In Regulatory Decision Making". Pmda.Go.Jp. Accessed May 24. https://www.pmda.go.jp/files/000226215.pdf

[2] Chen, Chi-Hsun. 2021. "Using Real-World Data/Evidence In Regulatory Decision Making". Pmda.Go.Jp. Accessed May 24. https://www.pmda.go.jp/files/000226215.pdf (Page 5)

[3] "Digital Information Security In Healthcare Act". 2018. Nhp.Gov.In. https://www.nhp.gov.in/NHPfiles/R_4179_1521627488625_0.pdf

[4] "Digital Information Security In Healthcare Act". 2018. Nhp.Gov.In. https://www.nhp.gov.in/NHPfiles/R_4179_1521627488625_0.pdf (Page 5)

[5] Magazanik, Limor. 2019. "Draft Regulation – Review Patient Rights Regulations (Health Data Research Use), 2019". Techpolicy.Org.Il. https://techpolicy.org.il/wp-content/uploads/2020/10/ITPI-Brief-Israel-Draft-Health-Data-Research-Regulations-.pdf (Page 5)

[6] "PIC/S". 2021. Picscheme.Org. Accessed May 24. https://picscheme.org/en/picscheme

[7] "PHARMACEUTICAL INSPECTION CO-OPERATION SCHEME". 2021. Picscheme.Org. Accessed May 24. https://picscheme.org/docview/2146

[8] "Celebrating MHLW's And PMDA's New International Strategic Plans "Toward Further Promotion Of Regulatory Science And Global Capacity Building" | Pharmaceuticals And Medical Devices Agency". 2015. Pmda.Go.Jp. https://www.pmda.go.jp/english/symposia/0080.html

[9] "Health Products International Activities - Canada.Ca". 2021. Canada.Ca. https://www.canada.ca/en/health-canada/services/drugs-health-products/international-activities.html

[10] "SCORE Data Collection Tool - WHO". 2021. Who.Int. https://www.who.int/data/data-collection-tools/score

[11] "EMA Regulatory Science To 2025". 2021. Ema.Europa.Eu. https://www.ema.europa.eu/en/documents/regulatory-procedural-guideline/ema-regulatory-science-2025-strategic-reflection_en.pdf

[12] "FRAMEWORK FOR FDA’S REAL-WORLD EVIDENCE PROGRAM". 2021. Fda.Gov. https://www.fda.gov/media/120060/download

[13] "FDA Announces 4 Grant Awards". 2020. U.S. Food And Drug Administration. https://www.fda.gov/drugs/science-and-research-drugs/fda-announces-4-grant-awards-projects-exploring-use-real-world-data-generate-real-world-evidence

[14] https://www.ehden.eu/

[15] https://www.ohdsi.org/

[16] "OHDSI Pager". 2019. Ohdsi.Org. https://www.ohdsi.org/wp-content/uploads/2019/11/OHDSI_1_Pager_v2.pdf

[17] "Welcome To OMOP – OHDSI". 2021. Ohdsi.Org. Accessed May 25. https://www.ohdsi.org/omop/

[18] "The Spirit & The Letter". 2014. Ge.Com. https://www.ge.com/in/sites/www.ge.com.in/files/TheSpirit&TheLetter.pdf

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