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Findings
Collaborative Communities are sustained, multi-stakeholder forums (including patients, industry, academia, and the FDA) dedicated to solving shared challenges in the medical device ecosystem. These communities are not intended to replace formal regulatory mechanisms. They are equipped to perform activities such as:
Developing best practices and strategies.
Generating and evaluating evidence to support novel approaches.
Clarifying ill-defined challenges and generating consensus on definitions.
Addressing issues related to product quality and safety.

Recommendations
The FDA/CDRH does not establish or fund these communities. Instead, the FDA recommends that interested stakeholders convene and lead these groups. The FDA reviews opportunities on a case-by-case basis for participation, considering:
The community's potential public health impact.
Alignment with the CDRH mission, priorities, and resources.
The existence of a formal governance structure, a convener, a plan to measure success, and a mechanism for sustained engagement.

Regulatory Considerations
The FDA's participation in these communities is a strategic priority for advancing regulatory science and fostering responsible medical device innovation. Examples of digital health-related collaborations include those focused on AI/ML, Digital Biomarkers, Digital Health Technologies (DHTs), and Real-World Data (RWD). The outcomes developed by these groups can inform and accelerate the development of science-based solutions to policy and scientific challenges.

Findings
Traditional, site-based clinical trials often create significant burdens for participants, which can hinder recruitment, retention, and the enrollment of diverse populations.
A lack of early and sustained patient engagement in trial design can lead to research protocols that are misaligned with patient needs and endpoints that are not meaningful to them.
The underrepresentation of diverse racial, ethnic, and other demographic groups in clinical trials limits the generalizability of study results and can perpetuate health disparities.
Emerging digital health technologies (DHTs) and real-world data (RWD) present significant opportunities to make clinical trials more efficient, patient-centric, and inclusive, but their adoption has been inconsistent.

Recommendations
Sponsors and research teams should engage patients and patient advocacy groups as active partners throughout the entire clinical trial lifecycle, from design to dissemination.
Decentralized clinical trial (DCT) elements should be incorporated to reduce patient burden, improve access for diverse populations, and enhance the quality of data collection.
Trial sponsors must develop and implement proactive strategies to enhance the diversity and inclusion of trial participants to ensure results are applicable to all patient populations.
Novel endpoints derived from DHTs should be developed and validated to capture more objective, real-world measures of how patients feel, function, and survive.
Multi-stakeholder collaboration between industry, academia, patient groups, and regulators is essential to address systemic challenges and improve the clinical trial enterprise.

Regulatory Considerations
Early and frequent communication with regulators, such as the FDA, is critical when implementing novel approaches like DCTs or developing new digital endpoints for pivotal trials.
Regulatory frameworks must support the use of innovative technologies and trial models while ensuring data integrity, reliability, and patient safety.
The use of a single Institutional Review Board (IRB) for multi-site trials is a key regulatory-supported mechanism for streamlining ethics review and increasing trial efficiency.
When using DHTs and decentralized methods, robust plans for data quality, privacy, and security are necessary to meet regulatory standards for trial data submission.

Findings
Misclassification of wakefulness during sleep periods and issues with tracking outside main sleep bouts.
Bias in performance evaluation studies due to limited representation of diverse populations.
Hidden complexities in consumer-grade devices related to data access, fees, privacy, and security.

Recommendations
Carefully interpret study results based on wearable sleep-tracking technology data.
Address biases in study populations by including diverse cohorts.
Ensure proper preprocessing of data from consumer-grade devices.
Avoid inserting personally identifiable information in device settings.
Evaluate issues related to specific populations like minors.

Regulatory Considerations
Complexity of privacy laws across different countries.
Need for strategies to protect personal information in device settings.
Consideration of specific population issues, such as minors, in regulatory frameworks.

Findings
There is a need for comprehensive validation and verification processes for DHTs.
Ensuring data security and privacy is a significant concern.
Usability issues for diverse populations need to be addressed.
There is a lack of clarity on whether certain DHTs meet the definition of a device under the FD&C Act.
The guidance does not establish legally enforceable responsibilities.

Recommendations
Ensure DHTs are fit-for-purpose for clinical investigations.
Implement robust data security measures to protect participant information.
Conduct usability evaluations to ensure DHTs can be used by intended populations.
Engage with FDA early to discuss the use of DHTs in clinical investigations.
Develop a risk management plan to address potential issues with DHT use.

Regulatory Considerations
Verification and validation should be addressed regardless of device classification.
Sponsors should ensure compliance with data protection and privacy regulations.
FDA evaluates DHT data based on endpoints, medical products, and patient populations. Sponsors can engage with FDA’s Q-Submission Program for feedback on DHT usage in clinical trials.
Sponsors should understand the legal implications of using DHTs in clinical investigations.
The guidance provides recommendations but does not establish legally enforceable responsibilities.

Findings
The clinical research ecosystem has longstanding diversity gaps, making targeted DEI strategies essential for equitable healthcare innovation.
Digital tools, including virtual visits, digital outreach campaigns, and AI-driven analytics, can increase access to trials for underrepresented populations.
Real-world data (RWD) and real-world evidence (RWE) help identify diverse participant pools and optimize recruitment strategies.
eConsent and educational resources improve patient engagement and retention by making clinical trials more transparent and accessible.
Trust-building measures, such as community partnerships and patient advocacy collaborations, are critical for long-term success in diversifying clinical trials.

Recommendations
Clinical trial sponsors should integrate digital tools at each stage of trial design to enhance participant diversity and reduce barriers to participation.
AI/ML and real-world data should be leveraged to identify, recruit, and retain diverse patient populations in a data-driven manner.
Digital engagement strategies, including social media outreach and mobile-friendly platforms, should be employed to improve awareness and accessibility.
Transparent communication, including clear eConsent processes and on-demand educational materials, should be prioritized to foster participant trust.
A comprehensive tracking system should be implemented to measure progress on diversity goals, ensuring accountability in clinical trial execution.

Regulatory Considerations
The FDA Diversity Plan requirement should be incorporated into clinical trial planning, with measurable targets for diverse participant inclusion.
Digital tools used for recruitment and engagement must comply with HIPAA, GDPR, and other privacy regulations to protect participant data.
The use of real-world evidence (RWE) in regulatory submissions should be expanded to demonstrate the efficacy of digital recruitment and retention strategies.
Standardized DEI reporting frameworks should be established to ensure regulatory bodies can assess the impact of diversity initiatives in clinical research.
Clinical trials utilizing digital tools should align with decentralized clinical trial (DCT) regulatory guidance to maximize accessibility and equity.

Findings
Traditional RCTs face high costs, long timelines, recruitment challenges, and lack of diversity.
Recruitment efficiency in stroke trials has decreased over the past 25 years.
Digital tools for stroke prevention often lack quality and interactive functionality.
Decentralized RCTs present challenges in data quality and require validation.
Regulatory and compliance requirements vary significantly across regions.

Recommendations
Adopt decentralized RCTs with a patient-centric approach.
Leverage digital technologies to improve trial efficiency and participant experience.
Ensure participant engagement and education in trial design.
Provide high-quality training and support for decentralized procedures.

Regulatory Considerations
Collaborate with regulatory agencies early in trial design.
Compliance with varying international standards is necessary.
Rapid evolution of technology outpaces regulatory changes.
Cross-border data standards and privacy rules must be observed.

Findings
The DTRA Best Practice Evaluation Rubric uses five dimensions to determine if a DCT practice should be considered a "best practice":
Evidence of Success: Requires measurable and demonstrable success using KPIs and tangible outcomes.
Improving Patient Experience: Must address the needs of patients, caregivers, and therapeutic experts, demonstrating improved experience and engagement.
Site Impact: Must consider the implications of adoption and the practical impact on site burden and working practices.
Operational and Technical Feasibility: Ensures operational and technical aspects (including ongoing support, security, integrity, scaling, and reuse) have been fully considered when deploying new technologies.
Regulatory & Ethical Compliance: Requires appropriate consideration of global and local regulations and guidance (e.g., ICH E6/E8, GDPR, HIPAA), including adherence to privacy, consent, and ethical safeguards.

Recommendations
A practice should demonstrate several key factors across the dimensions:
Patient-Centricity: Reduce patient burden by offering the option to reduce physical visits and enable greater patient empowerment and access to information. It should strive to increase the diversity of recruited patients while mitigating bias toward technologically literate patients.
Site Support: Achieve a net reduction in burden for sites, utilizing simple, intuitive technology with minimal, on-demand training. It must provide clarity of fiduciary responsibility and use technology to increase risk-based monitoring without sacrificing data integrity.
Technical Rigor: Have a clear problem statement and a thoroughly defined strategy to mitigate operational and technical risks. It should take a holistic approach and ensure the solution is fit for use for the specific patient population, aligning with data privacy and security standards.

Regulatory Considerations
Practices must ensure compliance with both global and local regulations and Health Authority guidance. Explicit attention must be given to aligning with ICH E6 (Good Clinical Practice) and privacy laws like GDPR and HIPAA. The design must protect stakeholders providing sensitive or personal data with safeguards to ensure ethical safety.

Findings
Sponsors must weigh the study benefits of PTs against potential burdens such as usability challenges, frequent reminders, or the need for connectivity and device maintenance.
Factors such as geography, socioeconomics, cultural practices, and technical literacy must be addressed to ensure PT accessibility across diverse patient populations.
Sponsors need to protect patient privacy by adhering to data protection standards and ensuring informed consent materials clearly communicate how data will be used and stored.
Effective maintenance, training, and 24/7 support systems for patients and sites are critical to ensure smooth operation and minimize disruptions.
Providing value to participants, such as progress feedback or gamification elements, can improve the patient experience and adherence.

Recommendations
Design Patient-Centric Materials: Simplify patient-facing materials, tailoring them to low health and technical literacy levels, and ensure patient input is incorporated during the design phase.
Identify and address geographic, socioeconomic, and cultural barriers to technology adoption to ensure inclusivity.
Offer multi-format training for patients and caregivers, provide troubleshooting guides, and ensure 24/7 multilingual technical support.
Safeguard patient data and inform patients of all potential risks associated with PTs. Develop backup plans for device failures or power outages.
Assess how PTs affect daily living, including comfort, usability, and the time required for setup and routine use, to minimize intrusion.

Regulatory Considerations
Ensure adherence to GDPR, HIPAA, and other relevant data protection laws. Clearly communicate privacy and data use details in consent forms.
Validate PTs for safety and suitability in the target population and ensure compliance with regulatory standards for medical devices.
Ensure that consent forms clearly describe PT functionality, benefits, and limitations in accessible language.
Global Adaptability: Account for regional laws, infrastructure limitations, and language requirements to ensure PT compatibility and regulatory compliance across geographies.

Findings
Patient experience data encompass a range of inputs, including symptom burdens, treatment impacts, patient preferences, and views on unmet medical needs.
These data inform all stages of medical product development, from discovery to post-market use.
Quantitative methods (e.g., surveys) provide numerical insights, while qualitative methods (e.g., interviews) offer in-depth understanding. Mixed methods combine both for a fuller perspective.Social media and verified patient communities present novel data collection opportunities but require consideration of verification and representativeness challenges.
Probability sampling (e.g., stratified random sampling) is emphasized for generalizability, while non-probability methods (e.g., convenience sampling) are useful for exploratory research. Representativeness ensures that patient input reflects the diversity and heterogeneity of the target population.
Data collection should adhere to good clinical practices and regulatory standards.
Research protocols should address missing data, quality assurance, and confidentiality.
Early collaboration with the FDA is recommended to align on study designs and regulatory requirements.

Recommendations
Define clear research objectives and determine specific research questions before selecting data collection methods.
Use probability sampling methods whenever feasible to ensure representativeness of the target population.
Address data quality through rigorous planning, data management, and adherence to FDA-supported standards.
Incorporate diverse perspectives by including underrepresented patient populations, tailoring methods to specific subgroups as needed.
Leverage existing data sources, such as patient registries and literature, to complement primary data collection efforts.

Regulatory Considerations
Data submitted to FDA should include clear documentation of the study protocol, intended use, and data collection methodologies.
Researchers must comply with human subject protection regulations (e.g., 21 CFR Parts 50 and 56) and good clinical practice guidelines.
For data intended to support regulatory submissions, adherence to FDA-supported data standards (e.g., CDISC) is strongly encouraged.
Missing data should be addressed through pre-planned strategies and summarized in the study report.
Patient experience data must meet methodological rigor to ensure their reliability and relevance for regulatory decision-making.

Findings
HFE/UE is essential for identifying and mitigating use-related risks that could compromise device safety or effectiveness.
Preliminary analyses, such as task and fault tree analyses, help identify critical tasks and use-related hazards early in device development.
Human factors validation testing must represent realistic use scenarios, include diverse user populations, and focus on critical tasks with potential for serious harm.
Residual risks that remain after validation testing must be justified in terms of the device's overall benefits and risk management measures.
Effective risk management prioritizes design modifications over labeling or training as the primary method for addressing use-related hazards.

Recommendations
Incorporate HFE/UE into all stages of device development to address use-related hazards through design improvements.
Conduct comprehensive risk analyses to identify and prioritize critical tasks that may lead to serious harm if performed incorrectly.
Design human factors validation testing to reflect real-world conditions and involve representative user populations.
Address use-related risks primarily through design modifications, with labeling and training as secondary measures.
Submit detailed HFE/UE documentation in premarket applications to facilitate FDA review and approval.

Regulatory Considerations
Submit human factors validation testing data as part of premarket applications for devices where use-related errors could result in serious harm.
Risk management processes must align with standards such as ANSI/AAMI/ISO 14971 and IEC 62366, ensuring comprehensive hazard identification and mitigation.
Conduct additional validation testing if modifications to a marketed device impact user interactions or introduce new risks.
For actual-use testing, ensure compliance with Investigational Device Exemption (IDE) requirements where applicable.
Manufacturers should maintain detailed records of HFE/UE processes, which must be available for FDA review upon request.