Patient-Owned Health Data Is Reshaping Clinical Research, From Recruitment to Longitudinal Evidence

Introduction

Patients increasingly access and manage their health information through consumer health, pharmacy, and care navigation platforms. At the same time, interoperability initiatives are making that data easier to move between the organizations involved in their care.

Healthcare organizations, consumer health platforms, and biopharma companies are also investing more in direct-to-patient engagement. This creates new opportunities to support patients beyond traditional care settings.

As patients gain access to and control over their own data, a new model is emerging. The patient, rather than the hospital, provider, or protocol, becomes the most persistent source of healthcare and research insight.

For biopharma, patient-owned health data fundamentally changes the research model. Studies open and close, healthcare happens across a growing number of clinical, pharmacy, digital, and consumer touchpoints, and the patient is the constant.
When patients control their longitudinal health data, they stop being participants waiting to be recruited into the next study. Instead, they become a durable, sponsor-independent entry point into research. One relationship can support patient insights, observational research, clinical trial recruitment, and evidence generation.

Key takeaways

• Patients increasingly manage their health through consumer health, pharmacy, and digital platforms, and biopharma is investing in direct-to-patient engagement to meet them there.
• Clinical research runs on episodic, protocol-bound relationships, so the same individuals are repeatedly identified, screened, and re-consented for each new study, at a real cost to research participants and their caregivers.
• Engaging patients on the platforms where they already manage their data, before screening, generates insights that can help reduce screen failures and sponsor costs once a protocol opens.
• A patient-centered research infrastructure built on consented data, verified identity, and ongoing engagement can help sustain patient support, observational research, recruitment, and evidence generation from a single relationship.
• A research-ready cohort in a “virtual patient waiting room” functions as a living community rather than a static list, so every survey, patient-reported outcome, and research program strengthens the foundation for the next one.

Read the b.well and myTomorrows partnership announcement here.

The problem: clinical research runs on episodic relationships

Clinical research has largely operated through protocol-bound relationships. A trial opens, recruitment begins, participants enroll, data is collected, and the relationship ends when the study ends.

However, sponsor evidence needs rarely end there. Many biopharma organizations require insights, observational research, clinical development support, real-world evidence, and long-term outcomes data, often for the same patient population and sometimes across multiple programs. Yet these activities are typically managed as separate initiatives. The result is a fragmented model in which similar patients are repeatedly identified, screened, and engaged for different objectives.

The burden extends beyond operational inefficiency. Every re-registration, re-consent, and repeat medical records request adds to the burden on patients and their often unpaid caregivers, frequently while they go through demanding treatment protocols. As clinical research becomes more decentralized and evidence needs extend across the product lifecycle, continually rebuilding patient relationships becomes increasingly difficult for both biopharma and patients.

Why has early patient identification become a strategic priority?

Biopharma needs new ways to find, engage, and support patients throughout their healthcare journey, not just when a trial opens. As patient engagement increasingly extends beyond traditional care settings and into digital health, support and research ecosystems, organizations are under growing pressure to build more direct and continuous relationships with the populations they serve. The pressure comes from two directions.

In competitive, fast-moving therapeutic areas such as obesity, cardiometabolic disease, and chronic conditions, the challenge is scale. Sponsors must identify the right patients at the right moment in care. They also have to understand how treatments perform over time and generate evidence across large, diverse populations.

Rare disease and precision medicine programs face the opposite problem. They need to locate highly specific populations defined by biomarkers, disease stage, genotype, or treatment history.

Both scenarios point to the same underlying need: to find and engage patients earlier. By the time a patient enters the traditional site recruitment funnel, biopharma has often already absorbed unnecessary cost and friction.

At that point, some prove ineligible, fail screening, or require extensive medical record collection and verification. Access to patient-consented data lets more stakeholders assess key signals for care and research opportunities earlier. At this stage, intervention can stop costs, delays, and operational complexity from compounding.

The value extends beyond recruitment. Engaging patients at key moments lets all stakeholders generate patient insights, understand treatment patterns, and collect longitudinal evidence before a protocol opens. Patients, in turn, receive more personalized support content that may ease their journey and help them stay on treatment.

How interoperability creates a more complete patient picture

Until recently, healthcare data remained largely fragmented across providers, health systems, health plans, pharmacies, and labs, making it difficult to construct a complete view of a patient’s healthcare journey. Advances in interoperability are now making this more achievable enabling patients to bring information from across healthcare settings and gain visibility into their care. With greater access and agency over their health information, patients can also choose to explore treatment and research opportunities when and where they are most relevant to their journey.

This shift is important as healthcare and research increasingly depend on a full patient journey picture rather than isolated clinical encounters. The industry is looking beyond available traditional datasets to better understand how patients move through the phases of diagnosis, treatment decisions, care transition, outcomes, and their daily life with a condition. Increasingly, these experiences occur across clinical, pharmacy, digital health, and consumer health environments rather than any single healthcare institution. A richer understanding of these experiences can help improve patient support, treatment decision-making, and evidence generation across the continuum. Patient-reported experiences, including symptoms, treatment burden, quality of life, and other real-world factors, provide context that is often difficult to capture through available traditional research datasets.

The new lifecycle that’s possible is illustrated below:

By bringing information from across the healthcare ecosystem, patients can actively contribute insights that extend beyond clinical encounters. This creates new opportunities for more personalized support, better understanding of treatment journeys, improved awareness of relevant treatment and research options, and richer evidence generation across the product lifecycle.

Scale makes this practical. Through connections across clinical, claims, pharmacy, and consumer health sources, patients can build a more complete view of their health than any individual healthcare organization can typically provide. For biopharma, this creates the opportunity to understand patient populations more holistically, generate real-world and patient-experience insights more efficiently, and engage patients in ways that are more relevant, timely, and meaningful.

Patient-owned health data as reusable care and research infrastructure

Patient-consented longitudinal data creates an alternative to the episodic model: a patient-centered research infrastructure that carries from one study to the next. Instead of standing up a new vendor stack for each protocol, biopharma can build on five core elements:

• Verified patient identity, reducing duplicate outreach and supporting trusted patient relationships.
• Patient-controlled consent that is configurable, revocable, and tied to approved uses, ensuring clarity around how data may be used.
• A FHIR-native longitudinal record that is continuously updated as patients move through diagnosis, treatment, and routine care.
• An engagement layer for patient-reported outcomes, symptom and medication tracking, and ongoing communication through channels patients already use.
• A research readiness layer where eligibility, preferences, geography, biomarkers, and treatment history are kept up to date.

Matching, navigation, and study execution sit on top of this infrastructure. Rather than rebuilding patient identification, engagement, and data collection efforts for every new protocol, biopharma can build upon a foundation of consented patients whose records, preferences, and eligibility signals remain current over time. A new research initiative can begin by understanding which patients may already be appropriate for a specific care need or research question. The focus shifts from patient acquisition to patient understanding.

As care and research needs evolve, the same foundation can support increasingly advanced use cases. Insights generated through surveys or observational studies can deepen understanding of patient populations, inform evidence-generation strategies, and improve how organizations support patients throughout their treatment and ongoing care. Verified and continuously updated records help stakeholders make more informed decisions while reducing operational complexity and duplication.

The value extends beyond any individual study. Every patient interaction, patient-reported outcome, research activity, and care milestone contributes to a growing understanding of patient needs and experiences. Rather than creating value for a single protocol, each engagement strengthens the infrastructure for future patient support and research understanding.

As patient-mediated interoperability continues to mature, the opportunity extends beyond any single research objective. The same patient-centered foundation can support treatment navigation, patient support, evidence generation, clinical development, and patient experience research from a common infrastructure. This reduces duplication for organizations while creating more continuous and meaningful experiences for patients throughout the continuum of care.

The research-ready cohort

A research-ready cohort works more like a living community than a static list. Patients who have consented and opted into research continue to use their records and receive support content relevant to their condition. They log outcomes and medications, and take part in surveys, observational studies, and other low-burden research activities. Often, there is no active trial available or relevant to their situation. Yet their care journey, preferences, and experiences still contribute to a richer understanding of patient needs and outcomes over time.

When a new research opportunity emerges, from a patient insights initiative to a clinical trial, researchers can engage a population they already understand. A screen failure, trial closure, or temporary ineligibility does not end the relationship. Patients remain part of the ecosystem, ready for the next opportunity that fits.

Over time, the greatest value may come from network effects, helping patients, providers, researchers, and biopharma learn faster and act more effectively together.

Protecting patient capital

The organizations that succeed will be the ones that stop rebuilding patient relationships. Each time a patient is asked to start again, the cost falls on people already in treatment or the caregivers supporting them. Research participation should feel like part of managing your health in an app you already use, not another system to sign up for.

That is the thinking behind the b.well and myTomorrows partnership. b.well unifies fragmented healthcare, pharmacy, and consumer health data into comprehensive longitudinal records that patients control and can choose to share. myTomorrows brings AI-powered clinical trial pre-screening, matching and patient navigation capabilities, along with a decade of experience connecting patients and physicians to treatment and research opportunities beyond the standard of care.

Together, the two create a continuum that begins with patient-owned, longitudinal health data and extends through patient support, patient insights, observational research, evidence generation, and trial participation. This can help biopharma and sites identify and screen eligible patients more efficiently, reach broader and more diverse populations, and reduce the duplicative data gathering that has historically fallen on patients and caregivers.

As healthcare, consumer health, research, and patient experience data become more connected, the greatest opportunity may lie in building trusted patient ecosystems, where every interaction contributes to stronger evidence, deeper patient understanding, and ultimately better care.

Read the b.well and myTomorrows partnership announcement to find out how we’re working together to connect patients with research opportunities through patient-owned health data.