Patient-generated health data: The key to the future of medicine

• The medical sector has vast clinical and patient-generated health data, but struggles to integrate and utilize it effectively due to outdated systems
• Patient data faces challenges like interoperability issues, fragmentation, and security concerns
• The future of healthcare involves empowering patients with data control, merging it with physicians’ insights, and enabling patient-researcher data sharing for advancements

In today’s high-speed world of medicine, clinicians and researchers are amassing vast amounts of data, and patients are In today’s high-speed world of medicine, clinicians and researchers are amassing vast amounts of data, and patients are becoming pivotal sources of information. When synergized with clinical data, this patient-generated health data forms a powerful catalyst that unlocks medicine’s full potential. In the relentless pursuit to push the boundaries of healthcare, these mountains of daily accumulated data—far beyond mere numbers and charts—embody the keys to groundbreaking next-generation healthcare breakthroughs.

Within just one year, a single hospital surpasses the entire data holdings of the United States Library of Congress by generating approximately 137 terabytes of data daily.¹  If leveraged effectively, this staggering volume of data stands to revolutionize healthcare decision-making in real-time, setting the stage for unmatched patient outcomes.

Despite the vast potential of data driven medicine, patient data processing lags due to the healthcare sector’s reliance on outdated data systems. The future of medicine crucially depends on bridging this extensive data divide. By integrating and leveraging both clinical data collected by healthcare providers and the rich, dynamic data streams generated by patients, we can significantly enhance the efficacy and efficiency of clinical trials and clinical trial data management. This integration allows for more personalized treatment approaches, quicker identification of patient needs, and more robust data-driven decisions. Harnessing this comprehensive data accelerates the development of new treatments and improves patient outcomes by ensuring that interventions are tailored to individual health profiles.

The capacity of patient data to revolutionize healthcare is unquestioned—offering a beacon for medical advancement and patient-centric care; yet, the current healthcare data systems are shackled by constraints that severely hamper this potential.^2,3 The impediments stem from a labyrinth of system challenges, each entwining to create a complex tapestry that resists easy data sharing and use of solutions. The most pressing challenges facing the healthcare space when it comes to data include:

• Data interoperability: The confidentiality of health information, as mandated by regulations like the Health Insurance Portability and Accountability Act of 1996 (HIPAA) and General Data Protection Regulation (GDPR), rightfully safeguards patient privacy but paradoxically hinders the fluid exchange of data. Without interoperability, it impedes effective analysis and delivery of real-time insights to those making critical decisions, such as vaccine-related adverse events. Additionally, many healthcare providers employ customized electronic health record systems that make it difficult to convert data into a standardized format enabling us to to share with other healthcare professionals.^4,5
• Delayed data exchange: In traditional healthcare settings, the exchange of patient data is often a slow, laborious process slowing down the gears of a system that often requires rapid information transmission. In scenarios where immediate treatment is essential, this sluggish pace can stifle response times and endanger patient outcomes​.⁵
• Fragmented data: Fragmented data is a phenomenon where health information is repeatedly entered, stored, and processed in multiple versions across a spectrum of healthcare entities, including public health organizations, providers, pharmacies, patients, and insurance bodies. The resultant data redundancy fosters inconsistencies, potentially leading to misinterpretation and clinical errors.⁵ The inconsistencies inevitably emerge when multiple versions of the same data exist independently within different healthcare entities.

To elaborate, each entity that re-enters, stores, or processes patient data—whether a hospital, clinic, pharmacy, insurance company, or the patients themselves—may have its systems and procedures. These systems may not be perfectly synchronized or updated simultaneously. This fragmentation means healthcare providers may need more complete or updated information when making decisions. This can lead to misinterpretation of a patient’s health status, which can result in clinical errors, such as incorrect medication dosages, duplicate testing, or inappropriate treatments.

• Security concerns: The rise in cyber threats and data breaches necessitates robust IT security infrastructures and governance frameworks to shield patient data from unauthorized access, thus averting reputational damage and financial losses. Implementing multi-factor authentication, data encryption, and rigorous employee training is vital to reinforce the defenses against such threats​.⁶
• Patient-generated data: Patient-generated data increasingly contributes to healthcare. It brings opportunities for personalized care but also challenges. Capturing, formatting, and integrating this data into a central system is crucial. However, patient-generated data comes from a vast array of sources, and as a result creates additional silos, each with its format, standards, and protocols. Therefore, a robust framework is needed to make data understandable and actionable. Additionally, the International Consortium for Health Outcomes Measurement (ICHOM) stipulates that patient-reported data must be systematically organized, adhere to global standards, undergo validation, and be collected consistently over time.⁷

The repercussions of these data management challenges ripple beyond healthcare professionals to the patients themselves. Hindered access to their health information complicates their ability to gain a holistic understanding of their health status and make enlightened decisions regarding their care. Furthermore, when patients are disinclined or unequipped to manage their health records, their agency in health decision-making is curtailed, ultimately leading to diminished patient empowerment and involvement in their care​.⁸

The absence of accessible, high-quality clinical and patient-generated data pivots healthcare providers to prioritize immediate care delivery over fostering patient autonomy, inadvertently sidelining the ethos of patient-centered care in the quest to unlock its transformative power.

The healthcare industry is not the first to experience the challenges caused by tremendous amounts of data. Take the financial industry for example. When faced with a crisis in 2008, the Banking, Financial Services, and Insurance (BFSI) industry began to focus on informatization and data integration, increasing the industry’s capacity to manage large volumes of data effectively and leverage it for value creation and innovation.⁹

Despite the financial sector’s notable achievements in securing integrated data systems, the healthcare sector’s path to equivalent security is fraught with obstacles. Each data collection point adds complexity to the formidable task of safeguarding information, necessitating a more nuanced and robust approach to data integration and cybersecurity in healthcare.

Despite the existence of defined standards for seamless data exchange, healthcare providers need help to share data as nimbly as financial services do. Common Data Models (CDMs) are being utilized more widely in the healthcare sector to overcome the need for more consistency in health data. Standardizing health data can streamline data management, improve data quality, consistency, and reproducibility, and enable robust linkage to other data.¹⁰ Transport standards such as  Health Level Seven (HL7)  and Fast Healthcare Interoperability Resources (FHIR) facilitate data exchange between different health systems by defining the formats, document architecture, data elements, and messaging patterns to be used.^11,12

Real-world evidence (RWE) derived from patient data in clinical trials has the potential to revolutionize healthcare by providing insights into the effectiveness and safety of treatments in real-world settings.¹³ By incorporating patient-generated health data into clinical trials and translating these findings into real-world practice, healthcare systems can benefit from more personalized and effective treatments, improved patient outcomes, and enhanced healthcare delivery.

The first step is to embed clinical trials within the usual care setting to improve data quality. Rather than conducting clinical trials at an academic center, running them at an appropriately configured community-based clinic may provide results that better reflect the real-world performance of medical products in the populations that will use them. Thus, embedded trials can help bridge the gap between research and clinical care, producing more accurate and reliable data representative of the patient population. Embedded clinical trials can also expand representative and generalizable evidence by enabling the inclusion of diverse patient populations and real-world data (RWD) in the context of regulatory decision-making.

Additionally, embedded clinical trials are poised to unlock greater benefits for both the trial sponsor and the patients. Integrating trial elements into clinical practice can reduce the duplication of trial and care activities, leading to increased efficiency, cost savings, and reduced burden on patients participating in trials.¹⁴ High-quality evidence generated by embedded clinical trials can lead to economic and healthcare system efficiencies, as demonstrated by a net health system benefit of AUD 1.6 billion and a benefit-to-cost ratio between 6:1 and 51:1 in a review of 24 late-phase clinical trials.¹⁵

Patients benefit from embedded clinical trials as well. Integrating trials into clinical practice can promote translating knowledge into improved patient care, as high-quality evidence can guide clinical decision-making and encourage consistency in clinical practice.¹⁶ This integration allows for the seamless incorporation of research findings into patient care, leading to more informed treatment decisions, enhanced patient outcomes, and a more evidence-based approach to healthcare delivery.

This higher-quality data becomes immensely valuable to decision-makers in real-world settings.¹⁷ Solving interoperability challenges will encourage data sharing among researchers, funders, and journals to facilitate evidence aggregation across multiple RCTs, thus providing decision-makers with a broader research landscape to inform their decisions.¹⁸

Despite the improvements that real-world evidence and embedded trials can lend to our understanding of medical questions, researchers must still carefully weigh ethical concerns against the benefits of clinical trials in general. In clinical trials, it’s crucial to balance the need for new medical knowledge with the rights and safety of participants. Trials should focus on meaningful questions when genuine uncertainty about the best treatment exists.

By regularly updating reviews of current evidence, researchers can better understand where true uncertainties lie. Even with evolving evidence, some uncertainty is inevitable. Yet, the research community must focus on areas where more information is most needed and beneficial to patients, making the best use of limited time, resources, and patient participation. By implementing these strategies, healthcare providers can leverage high-quality evidence from clinical trials to make more informed decisions in real-world healthcare settings.

Integrating patient-generated health data is a cornerstone in the evolution of healthcare, a shift towards a more collaborative and outcome-focused model of care. This dynamic approach centers not just on clinical data but also on the wealth of information provided by patients themselves, offering a 360-degree view of individual health journeys. Elevating patient outcomes subsequently enhances the value proposition of the healthcare system, thereby contributing to more equitable and sustainable long-term access.¹⁹ Empowering patients by utilizing real-life data can lead to a deeper understanding of their health conditions and encourage active engagement in their care.

Moreover, leveraging this comprehensive data repository supports the transition to value-based care, where providers are rewarded for the quality of care rather than the quantity of services delivered. A value-based care model could reduce healthcare costs by as much as 30%.²⁰ By harnessing the full spectrum of patient data, clinicians can make informed decisions that focus on outcomes, ultimately driving down costs and enhancing patient satisfaction.

Value-based care, bolstered by patient-generated health data, promises economic efficiency and a more profound and personal interaction between patients and their care teams. This paradigm shift could see healthcare providers spending more meaningful time with patients, fostering a system that thrives on the success of patient outcomes.

As we stand at the threshold of a new era in healthcare, the transformative potential of patient data beckons us forward. It is time to redefine the patient’s role from passive recipient to active collaborator in their healthcare journey. Imagine a future where patients are stakeholders and co-authors of their medical narratives. They hold the pen that writes their health story and completely own their end-to-end medical data.

True empowerment comes from partnership. By giving patients command of their data, we entrust them with the keys to unlock a healthcare system that sees them as equals. This vision propels us toward an infrastructure meticulously designed to bolster physicians with comprehensive medical histories and patient-generated health data in digital form, sharpening the precision of their treatment strategies.

It’s more than a call to action; it’s an invitation to revolutionize healthcare together. By uniting patients, providers, and researchers on a shared digital platform, we are advancing research and crafting a legacy of collaborative health innovation. Together, let’s unlock the future of medicine, bridging the gap with patient data and, in doing so, bridging our efforts to the most fundamental aspect of healthcare: the improved well-being of every patient we serve.