stuart.mccully, Author at rwr-regs

Italy – CCNCE – Ethical and Regulatory Issues in the Processing of Patient Data in Observational Research
Italy – CCNCE – Ethical and Regulatory Issues in the Processing of Patient Data in Observational Research

2023, RWE 201

Italy – CCNCE – Ethical and Regulatory Issues in the Processing of Patient Data in Observational Research

RWE 201 – Italy – CCNCE – Ethical and Regulatory Issues in the Processing of Patient Data in Observational Research

CCNCE Reflection Paper (Apr 2023): https://www.aifa.gov.it/documents/20142/1808580/Criticita_etiche_ricerca_osservazionale_06.04.2023.pdf

The Italian National Coordination Center of Territorial Ethics Committees (CCNCE) has released a comprehensive document discussing the ethical and regulatory challenges surrounding personal health data processing in observational research.

Key Points:

[1] Importance of Observational Research: Observational studies are foundational in the medical research domain. In a 2019 survey by CCNCE, 50% (7,400) of approximately 14,800 studies reviewed by Ethics Committees were observational. Retrospective studies made up more than half of these, leading to around 4,500 such studies annually in Italy. Observational research strengths lie in the vast health data registers and long observation periods. The COVID-19 pandemic accentuated the significance of timely analyzing pre-collected data.

[2] Regulation and Ethical Evaluation: Current clinical trial legislation inadequately covers observational research. Bureaucratic hurdles in observational studies can lead to increased costs and operational challenges. Two major ethical issues arise:

Data processing from/by patients.
Additional procedures outlined in the research Protocol.

The latter was discussed in a 2022 CCNCE publication.

[3] GDPR and Data Processing: GDPR (Regulation EU/2016/679) addresses the use of registers in research. CCNCE also scrutinizes the legal bases provided by GDPR and its relevance in personal data processing during observational studies.

[4] Proposals for Enhanced Data Processing:

New Regulation: Suggestions from public institutions emphasize data collection quality. The “Reform Scheme of Health Information Systems” (January 2022) suggests clearer data collection intentions, legal architecture, and transitioning from pre to post data processing control.
Shared Data Governance: Recognizing data as a shared resource, a “data access committee” (DAC) is recommended to control data access. The European Data Governance Act also backs such data sharing facilitation.
Accountability Rethink: The Superior Council of Health suggests transitioning from pre-processing authorization to post-processing checks. This involves sharing general research details and establishing a notification system for easier post-process checks.
Revamping Consent: New forms of consent like “Broad Consent” and “Dynamic Consent” are explored. The latter allows participants to dynamically decide on their data usage over time.

Conclusion: To address personal health data’s ethical and regulatory issues in observational research, CCNCE proposes:

Uniform pseudonymization rules.
Moving beyond traditional consent methods.
Promoting researcher accountability, consulting the Guarantor for potential processing risks, and encouraging post-process control for data processing exclusively for research purposes.

Italy – CCNCE – Ethical and Regulatory Issues in the Processing of Patient Data in Observational Researchstuart.mccully2023-10-14T08:50:52+00:00

Germany – AKEK – Secondary Use of Patient Data for Research Purposes
Germany – AKEK – Secondary Use of Patient Data for Research Purposes

2023, RWE 201

Germany – AKEK – Secondary Use of Patient Data for Research Purposes

RWE 201 – Germany – AKEK – Secondary Use of Patient Data for Research Purposes

AKEK Statement (Aug 2023): https://www.akek.de/wp-content/uploads/Stellungnahme-EHDS_V7.1.pdf

The Working Group of Medical Ethics Commissions in Germany (AKEK) has emphasized the importance of secondary patient data use for research in public health. Its relevance was magnified during the COVID-19 pandemic, showing the need for efficient data collection and evaluation. Germany requires a robust regulatory framework promoting both data privacy and research.

During the pandemic, the lack of standardization in country-specific regulations made data handling challenging. The upcoming European Health Data Space Regulation (EHDS-R) and the proposed German Health Data Use Act (Gesundheitsdatennutzungsgesetz – GDNG) aim to harmonize regulations, facilitating responsible health data access at multiple governance levels.

The pandemic also spurred interest in alternative consent models, like “broad consent” and “dynamic consent”, aiming to balance personal data rights, research freedom, and public health. As obtaining individual consent becomes complex, the German law needs clear rules to reconcile these rights.

Germany’s legislators need to evaluate consent models, considering pandemic-driven challenges. They should provide compensatory measures, such as defining standards for data pseudonymisation and anonymisation. Ensuring transparency in research results and balancing intellectual property rights are also vital.

For effective secondary patient data use in research, a strong governance structure, inclusive of ethics committees, is essential. These committees are pivotal in ensuring data protection and balancing the risks and benefits of research.

AKEK highlights key demands for promoting secondary patient data use:

Nationwide standardisation of legal regulations to reduce bureaucratic hurdles.
A balance between individual data rights, research freedom, and societal welfare.
Risk-adapted methods to reconcile scientific evidence with data privacy.
The involvement of ethics committees in governance for a balanced approach.

In conclusion, secondary patient data use is crucial for medical advancements. Germany needs a comprehensive strategy that balances individual rights with research benefits. The urgency brought by the COVID-19 pandemic necessitates swift legislative action by Germany.

Germany – AKEK – Secondary Use of Patient Data for Research Purposesstuart.mccully2023-10-14T08:46:40+00:00

UK – NHS England – Federated Data Platform – Lessons Learned from the General Practice Data for Planning and Research Initiative
UK – NHS England – Federated Data Platform – Lessons Learned from the General Practice Data for Planning and Research Initiative

2023, RWE 201

UK – NHS England – Federated Data Platform – Lessons Learned from the General Practice Data for Planning and Research Initiative

RWE 201 – UK – NHS England – Federated Data Platform – Lessons Learned from the General Practice Data for Planning and Research Initiative

NHS England – Federated Data Platform: https://www.gov.uk/government/news/the-nhs-federated-data-platform-the-importance-of-building-bridges-with-the-public

The National Health Service (NHS) in England is in the process of procuring a Federated Data Platform (FDP), aiming to streamline IT systems and improve healthcare delivery. However, the initiative has come under scrutiny, particularly around ethics, privacy, and commercial involvement. The National Data Guardian’s role is to offer advice and ensure that the NHS maintains public trust, especially concerning data management.

Public concerns mainly revolve around commercial interest in NHS data. Research indicates that the public is generally open to commercial involvement if conditions such as transparent communication, public benefit, and adequate safeguards against misuse are met. Previous initiatives like the General Practice Data for Planning and Research (GPDPR) serve as cautionary tales. Lack of communication led to misinformation and resulted in a significant number of people opting out of data-sharing, negatively affecting health research and planning.

To avoid repeating past mistakes, the National Data Guardian advocates for meaningful and open dialogue between NHS England and the public. They outline three key focus areas:

Value to Patients and the NHS: Clearly communicate the FDP’s purpose and benefits. Answer critical questions like the scope of the program, public choice in data sharing, and how it solves real-time problems in healthcare delivery.
Integrity of Decision-making: Given the sizable contract and existing relationships with potential suppliers, the NHS must demonstrate a transparent, fair procurement process. Information should be provided about who makes decisions, how they are made, and how safeguards are in place to ensure fair competition.
Relationship with the Supplier: The public needs assurance that NHS maintains control over the data and the system. This includes clarifying what data the supplier can access and the safeguards against misuse. Concerns about vendor lock-in and the ability for the NHS to terminate partnerships without compromising patient care or incurring significant costs should also be addressed.

In summary, the key to the FDP’s success lies in transparent, meaningful engagement with the public and healthcare professionals. Filling the existing knowledge gap with accurate information can quell mistrust and speculation, thereby earning public trust for a smoother implementation. Open communication, even when there are no complete answers, can prevent suspicion and ensure ongoing public support for the FDP initiative.

UK – NHS England – Federated Data Platform – Lessons Learned from the General Practice Data for Planning and Research Initiativestuart.mccully2023-10-14T08:39:42+00:00

UK – NICE – RWE Framework
UK – NICE – RWE Framework

2023, RWE 201

UK – NICE – RWE Framework

RWE 201 – UK – NICE – RWE Framework

NICE RWE Framework: https://www.nice.org.uk/corporate/ecd9/chapter/overview

Real-world data (RWD) encompasses various types of information on patient health, care delivery, and experiences collected outside traditional clinical trials. This data is crucial in forming National Institute for Health and Care Excellence (NICE) guidance.

NICE utilises RWD to:

Characterise health conditions, care pathways, and patient outcomes.
Design and validate economic models related to healthcare.
Evaluate digital health technologies.
Address health inequalities.
Assess the safety of medical technologies.
Examine the effects of interventions on care delivery.

While Randomised Controlled Trials (RCTs) are preferred for studying interventions, they may not always be available or applicable to real-world NHS settings for various reasons, including ethical constraints, technical challenges, or lack of funding. Sometimes, RCTs may also have limitations such as irrelevant comparators, exclusion of important population groups, or poor quality, making them insufficient for NHS decision-making.

NICE often resorts to non-randomised studies, particularly for medical devices, public health interventions, and assessments of medicines. Observational cohort studies and single-arm trials with real-world external control are commonly used non-randomised methods.

NICE aims to use RWD more consistently to fill evidence gaps and expedite patient access to innovations. For RWD to be trusted, it needs to be gathered and analysed transparently, utilising fit-for-purpose data while mitigating biases.

NICE has developed a real-world evidence framework to guide the generation of high-quality evidence. This framework is targeted primarily at those creating evidence to inform NICE guidance but is also relevant for patients, data collectors, and evidence reviewers. Core principles for generating trusted real-world evidence include ensuring data quality, transparency, and the use of analytical methods that minimise bias.

The framework consists of several sections:

Introduction: Outlines the role and potential of RWD.
Study Conduct: Describes expectations for planning and reporting RWD studies.
Assessing Data Suitability: Provides guidelines for assessing the quality and relevance of RWD.
Methods for Real-world Studies: Offers specific recommendations for conducting non-randomised studies.

Companies are encouraged to seek early advice from NICE on integrating RWD into their evidence-generation plans.

In summary, RWD has become an essential tool for improving healthcare outcomes and policy, fulfilling NICE’s strategic ambitions to drive innovation and resolve gaps in knowledge through robust, transparent, and high-quality evidence.

UK – NICE – RWE Frameworkstuart.mccully2023-10-14T08:35:21+00:00

UK – MHRA – Randomised Controlled Trials Using Real World Data
UK – MHRA – Randomised Controlled Trials Using Real World Data

2023, RWE 201

UK – MHRA – Randomised Controlled Trials Using Real World Data

RWE 201 – UK – MHRA – Randomised Controlled Trials Using Real World Data

MHRA RWD Guidance: https://www.gov.uk/government/publications/mhra-guidance-on-the-use-of-real-world-data-in-clinical-studies-to-support-regulatory-decisions/mhra-guideline-on-randomised-controlled-trials-using-real-world-data-to-support-regulatory-decisions

The MHRA guideline focuses on sponsors planning to conduct randomised, controlled clinical trials (RCTs) primarily using Real-World Data (RWD) for regulatory decisions concerning medicinal products.

Scope

The guideline covers:

Clinical trial authorisation in the UK.
Trial design, including endpoint selection and safety requirements.

It excludes discussions on observational studies, and clinical trials using RWD as a control arm.

Definition and Types of RWD Trials

RWD is health data obtained outside clinical studies and can include electronic healthcare records, disease registries, and patient-reported outcomes. In a simple RWD-based RCT, patients are randomized to receive standard clinical care alone or an added intervention. Data quality and study design need to be as rigorous as traditional RCTs for the results to be valid for regulatory decisions.

Protocol Requirements

The protocol should pre-specify objectives, data collection methods, and primary and secondary endpoints. Consent is required before enrolment, and in most real-world settings, patients are not blinded to treatment allocation.

Regulatory Acceptability

From a regulatory standpoint, the source of the data (RWD, hybrid, or traditional) is irrelevant as long as the trial answers the necessary regulatory questions. The need for blinding should be considered, especially if the primary endpoints are not sufficiently objective.

Examples and Practical Considerations

The guideline suggests that RWD-based trials can be effective when dealing with an established EHR database and objective endpoints like all-cause mortality. Scenarios where the intervention is an existing licensed product with a well-known safety profile are particularly suited for RWD trials. It’s critical not to assume the completeness of potential endpoints in EHRs. Sponsors are advised to conduct a feasibility study to assess the reliability of the data capture methods.

Data Gaps and Hybrid Trials

If the RWD source does not cover all required endpoints, a hybrid trial can supplement RWD with specific additional data. These could be additional clinical assessments, which might even be carried out remotely.

In summary, the MHRA guideline serves as a comprehensive framework for sponsors interested in leveraging RWD for RCTs aimed at supporting regulatory decisions for medicinal products. While RWD-based trials offer advantages in reducing patient and healthcare burdens, they must be designed and executed with rigor comparable to traditional RCTs to be deemed acceptable for regulatory purposes.

UK – MHRA – Randomised Controlled Trials Using Real World Datastuart.mccully2023-10-14T08:31:42+00:00

UK – MHRA – Use of RWD to Support Regulatory Decisions
UK – MHRA – Use of RWD to Support Regulatory Decisions

2023, RWE 201

UK – MHRA – Use of RWD to Support Regulatory Decisions

RWE 201 – UK – MHRA – Use of RWD to Support Regulatory Decisions

MHRA RWD Guidance: https://www.gov.uk/government/publications/mhra-guidance-on-the-use-of-real-world-data-in-clinical-studies-to-support-regulatory-decisions/mhra-guidance-on-the-use-of-real-world-data-in-clinical-studies-to-support-regulatory-decisions

The MHRA (Medicines and Healthcare products Regulatory Agency) has produced a comprehensive series of guidelines addressing the use of Real-World Data (RWD) in clinical research, particularly aiming to guide sponsors who intend to use RWD to support regulatory decisions.

Key Highlights:

[1] Definition and Sources: RWD is defined as data relating to patient health status or healthcare delivery, collected outside the controlled environment of a clinical study. EHR, primary and secondary care records, and disease registries are key sources of RWD. The guidelines also recognize newer sources like wearable devices and specialized websites.

[2] Purpose and Scope: The guidelines are intended to inform the design of studies that leverage RWD for evidence suitable for regulatory decisions, irrespective of geographical location. It outlines requirements for gaining approval for such studies to be conducted in the UK.

[3] Benefits: Using RWD can potentially expedite research and reduce costs. RWD can also make certain previously unfeasible studies viable, resulting in a broader understanding of treatments’ real-world effectiveness.

[4] Data Quality: Ensuring the data source’s quality is crucial; otherwise, the benefits of using RWD become moot. Key considerations include the source data’s accuracy, validity, reliability, and provenance. Pre-study protocols must address questions about data quality, population size, data capture details, data availability, interoperability issues, and more.

[5] Methodological Rigor: Traditional principles of evidence strength, such as randomization and blinding, still apply when using RWD. The guidelines indicate that sponsors should clarify how data quality checks, data extraction, and data handling will be performed and validated.

[6] Digital Health Technologies: Digital platforms, including wearables and sensors, are recognized as valid RWD sources. These technologies must be validated for their intended use.

[7] Ethical and Legal Aspects: The guidelines stress the importance of understanding privacy and security policies associated with database use, including data transfer and storage restrictions.

[8] Inspection: MHRA will continue its risk-based Good Clinical Practice (GCP) inspections. The integrity of the reported data will be a focus during these inspections, which may also involve reviewing the systems and processes used for RWD data management.

[9] Sponsor Responsibilities: Sponsors must clearly outline methods for data selection, extraction, transfer, and handling in the study protocol. Validity of the RWD should be formally documented and approved before study initiation.

Future Outlook:

Overall, the guidelines strive to provide a structured approach for incorporating RWD into clinical research, ensuring data integrity, methodological rigor, and compliance with ethical and legal standards. By doing so, they aim to pave the way for more effective and rapid healthcare solutions.