Patient Empowerment: Entrusting Data Ownership to Patients for RWE/RWD Access
Empowering patients in data-driven healthcare fuels personalized healthcare research built on advanced AI capabilities and enhances their role in driving clinical advancements.
- Collecting and analyzing patient data is crucial for advancing the healthcare we could all receive in the future
- It is vital that the right safeguards are put in place to protect individuals’ privacy and to ensure they understand how and by whom their data will be used
- Patients should receive tangible health rewards in exchange for sharing their data
When it comes to harvesting the rewards of real world data, it’s time to involve and empower patients
Over the last decade, there has been a growing recognition that harvesting real world data and evidence (RWD and RWE) will be instrumental in delivering better outcomes for patients, healthcare practitioners, policymakers, and other decision makers within our healthcare systems. But confusion over who owns the data and concerns about how to ensure critical and highly personal insights can be shared securely have so far stymied efforts to fully leverage RWD and RWE across the healthcare continuum.
Although patients are the primary source of RWD, they have yet to be integrated into the data value chain, with many decisions about what and how patient data should be used being made without proper consultation with patients themselves.
If we are to take David McCandless’ perspective on data being the soil in which we can plant seeds, then it’s time to view patients as being the gardeners who tend to this soil and ensure it is rich enough to grow the kinds of fruits that will benefit us all as we each go through our healthcare journeys.
In this article, I set out why it is so important that we access patient data and the steps we can take to ensure patients are integrated into the data value chain as equal partners.
Insights from patient data will result in better outcomes for all
The ability to collect, access, and evaluate patient data is vital for medical research, and drug discovery as well as for the prediction, prevention, and management of disease.
Advancing medical research
Opening up patient data to researchers and scientists enables them to get a much better picture of what is happening at a population level as well as how the health of groups of individuals can be affected by different factors. Through the analysis of broader datasets, scientists are able to understand emerging trends, uncover insights into disease patterns, and gain more evidence regarding potential outcomes of different types of treatment in the real world setting – evidence that is generally not collected in randomized control trials.
This information can all be used to aid and speed up the discovery and development of new medicines as it allows researchers to more quickly identify potential drug targets, understand the effectiveness and safety of medications, and predict how patients are likely to respond to specific treatments. By analyzing diverse patient datasets, pharmaceutical companies can also develop medicines that can be targeted to specific patient groups and profiles. Moreover, it offers healthcare companies a chance to enhance the patient recruitment process for clinical trials, leading to reduced study costs and an increased likelihood of successful clinical study outcomes.
Ensuring greater representation in clinical trials and databases
Collecting patient data is also crucial for ensuring research efforts focus on the needs of everyone. The industry continues to face significant challenges in terms of data diversification. There remains, for example, an over-representation of European data in the genomics database with data from Europeans accounting for 78-88% of the data held (1). This disparity is contributing to inequalities in genomic-led drug development. Moreover, even though the Asian population represents around 60% of the global population, only 11% of global trial participants are Asian; 76% are white (2).
Predicting, preventing, and managing disease
Patient data also plays a crucial role in the prediction, prevention, and management of disease. When combined with advanced analytics and machine learning algorithms, patient data enables the creation of predictive models. These models can identify early warning signs, predict disease progression, and estimate patient outcomes. Such predictive analytics can support proactive and personalized interventions and enhance patient care and outcomes.
Policymakers also rely on patient data to make informed decisions regarding public health initiatives, resource allocation, and policy development. By analyzing population-level patient data, policymakers can identify healthcare disparities, track disease outbreaks, and implement targeted interventions to improve health outcomes. Patient data serves as a foundation for evidence-based policymaking, fostering better healthcare systems and public health strategies.
Creating the right conditions: How to achieve safe access to data
In order to maximize the potential insights that can be garnered through patient data, it is paramount that the right safeguards are put in place to protect individuals’ privacy and to ensure they understand how and by whom their data will be used. It is very encouraging to see data governance frameworks being established to maintain trust and facilitate responsible data usage.
Transparent communication and informed consent processes are fundamental elements of good practice. It is absolutely imperative that healthcare providers openly discuss the potential use of data with patients and that their preferences are respected at all times. Taking these steps will help to foster a positive environment for data sharing in clinical research and beyond.
Putting the right precautions in place
Prior to sharing RWD, it is crucial to anonymize and de-identify the data to remove any personally identifiable information (PII) that could identify individuals. This process should be performed rigorously to ensure that data cannot be re-identified. Proper anonymization techniques, such as data aggregation, masking, and encryption and homomorphic encryption, should be employed to safeguard patient privacy.
Patients’ informed consent should be obtained before collecting their RWD for research purposes. Patients should be provided with clear and comprehensive information about how their data will be used, the potential risks and benefits, and any data-sharing practices. Patients should have the autonomy to decide whether they want to share their data and should have the right to withdraw their consent at any time.
Robust data governance frameworks must ensure secure storage, transmission, and access control of RWD. Adequate measures should be implemented to protect against unauthorized access, data breaches, and potential misuse. Data-sharing agreements and protocols should be in place to govern the responsible and ethical use of RWD by researchers and other stakeholders.
Determining what data needs to be shared
Only relevant and necessary data should be shared for research purposes. The amount of data shared should be minimized to reduce the risk of privacy breaches and limit the potential harm that could result from data exposure. Unnecessary variables or sensitive information should be excluded to maintain patient privacy while still providing valuable insights for research.
Clear guidelines should be established regarding the permissible uses of RWD and the intended research purposes. Data-sharing practices should be transparent, and the data should only be used for the agreed-upon research objectives. Secondary uses or data re-identification should be strictly prohibited without further informed consent.
Research involving RWD should undergo rigorous ethical review and oversight by relevant institutional review boards (IRBs) or ethics committees. These bodies assess the study design, data handling procedures, and privacy safeguards to ensure that research activities adhere to ethical principles and legal requirements.
The risks of sharing data remain even though ethical anomaly is addressed  hence ongoing monitoring and auditing of data-sharing processes are essential to detect and address any potential privacy or security vulnerabilities. Regular assessments should be conducted to ensure compliance with ethical guidelines and data protection regulations.
Regulation and governance models
Establishing effective data governance models, including data access controls, consent management, and data sharing agreements, is essential to balance data protection and research access. Careful planning and implementation is needed to develop a data governance platform for sharing patient-generated health data (PGHD) anonymously to enhance clinical research. A few steps are highlighted below that can be used:
Define Clear Data Governance Policies: Develop comprehensive data governance policies that outline the principles, objectives, and guidelines for sharing PGHD. The establishment of a multidisciplinary committee comprising representatives from healthcare providers, researchers, data privacy experts, legal professionals, and patient advocates will oversee governance processes and ensure compliance.
Data Anonymization Techniques: Implement robust anonymization techniques to de-identify patient-generated health data effectively and minimize the risk of re-identification.
Consent Management: Develop a consent management framework that allows patients to provide informed consent for sharing their PGHD for research purposes and ensures clear communication channels as well as the ability to revoke consent at any time
Secure Data Infrastructure: Establish secure data infrastructure, to protect the confidentiality and integrity of shared PGHD. Implement secure data storage and transmission mechanisms to prevent unauthorized access.
Data Quality Assurance: Implement measures to ensure the accuracy, completeness, and reliability of shared PGHD to maintain data integrity and enhance the reliability of clinical research findings.
Compliance with Regulations: Adhere to relevant data protection and privacy regulations, such as GDPR, HIPAA, or country-specific laws.
Patient Engagement and Education: Involve and educate patients on the data governance process and foster trust and transparency by providing clear information and addressing patient concerns regarding data security and privacy.
Collaboration with Research Institutions: Collaborate with research institutions and establish data-sharing agreements to leverage shared expertise and resources for efficient and ethical data sharing.
Ongoing Monitoring and Evaluation: Continuously monitor and review data governance policies, and evaluate their effectiveness, based on emerging technologies, regulatory changes, and evolving best practices.
Making sure patients are part of the data value chain
Given the number of ways in which accessing patient data can advance the delivery of healthcare for us all, patients themselves should also be able to directly benefit from the individual contributions they are making. Only by establishing an inclusive approach that fully integrates patients into the process, will we be able to achieve meaningful partnerships with our most important source of health data – our patients.
Health rewards in exchange for data
Offering tangible health rewards to patients in exchange for their health data can incentivize data sharing and foster patient engagement. Here are some examples of the kinds of rewards that can be considered:
Health Discounts or Rebates: Patients could receive discounts or rebates on healthcare services, medications, or health insurance premiums based on the extent of their data sharing. This could help reduce out-of-pocket costs and incentivize patients to actively participate in data-sharing programs.
Wellness Products or Services: Patients could receive tangible rewards such as fitness trackers, smart scales, or subscriptions to wellness apps or programs. These rewards can support patients in monitoring their health, promoting physical activity, and managing chronic conditions.
Donations to Charity: Patients could have the option to donate a portion of their health data or the rewards they receive to selected charities or research organizations. This allows patients to contribute to the greater good and support healthcare initiatives.
Priority Access or Enhanced Services: Patients who actively share their health data could receive priority access to appointments, shorter wait times, or enhanced services, such as personalized care plans, dedicated healthcare professionals, or exclusive health education resources.
Many of these rewards would have the additional benefit of serving as powerful motivators for patients, encouraging them to prioritize their health and adopt healthier lifestyles.
Tending to the soil
It is becoming increasingly evident just how important gathering the right data will be when it comes to advancing our quest for better healthcare. And as we reflect on the words of David McCandless, if we want fruitful harvests, then we need the right soil. And if we want the right soil, we need motivated gardeners to ensure it remains full of the right nutrients. This means we need engaged patients, who are confident and committed to sharing their data so that we may all reap the rewards of this harvest.
Diversity in Genomic Research https://www.genome.gov/about-genomics/fact-sheets/Diversity-in-Genomic-Research
Nature reviews Disease Primers
Chiruvella V, Guddati A, Ethical Issues in Patient Data Ownership, Interact J Med Res 2021;10(2):e22269, URL: https://www.i-jmr.org/2021/2/e22269, DOI: 10.2196/22269