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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 real world patient 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’s perspective on data being the soil in which we can plant seeds, then it’s time to drive patient empowerment and view the 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.
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.
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 and health literacy 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 empowerment and recruitment process for clinical trials, as empowered patients are proactive in seeking out clinical trial opportunities that align with their specific conditions or interests, leading to reduced study costs and an increased likelihood of successful clinical study outcomes. By incorporating patient input, healthcare companies can design more targeted and effective clinical trials, leading to improved treatment outcomes.
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
Patient data also plays a crucial role in the prediction, prevention, and management of disease. Real-time patient data access, 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, health education programs, 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.
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 for patient empowerment that healthcare providers openly discuss the potential use of data with patients and that their preferences are respected at all times, including fostering a sense of healthcare data ownership. Taking these steps will help to foster a positive environment for patient centered care that facilitates data sharing in clinical research and beyond.
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, 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. This will really help drive patient empowerment and help ensure more RWD is collected and shared with the relevant stakeholders.
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.
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.3 Regular assessments should be conducted to ensure compliance with ethical guidelines and data protection regulations.
Regulation and governance models
Establishing effective data frameworks, including data governance models, 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:
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 increase patient empowerment and achieve meaningful partnerships with our most important source of health data – our patients.
Offering tangible health rewards to patients in exchange for their health data can incentivize data sharing and foster digital patient engagement. Here are some examples of the kinds of rewards that can be considered:
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.
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 to drive patient empowerment to ensure we have engaged patients, who are confident and committed to sharing their data so that we may all reap the rewards of this harvest.
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