Health Care Doesn't Have a Data Problem. It Has an Activation Problem.

Every day, health systems generate massive volumes of clinical data. Researchers produce new evidence at an unprecedented pace. Pharmaceutical companies continue to invest heavily in real-world evidence programs designed to better understand how therapies perform outside the controlled environment of clinical trials. In fact, health care now generates roughly 30% of the world's data volume, with the amount of health data expected to continue growing at a rate of more than 35% annually.^1,2

Yet despite this explosion of data, evidence, and technology, health care outcomes have not improved at the same pace. The industry’s challenge is no longer generating knowledge. It is activating knowledge at the point of care in service of better patient outcomes.

This disconnect should concern every health care stakeholder, especially life sciences organizations working to ensure that information reaches the clinicians and patients who need it most – and in ways that can meaningfully shape care decisions.

What Is the Evidence Gap?

The health care industry has spent the last decade building increasingly sophisticated capabilities around real-world data and real-world evidence.

This progress matters. Real-world evidence helps researchers better understand treatment effectiveness, identify unmet needs, support regulatory submissions, and inform clinical decision-making. It also helps bridge gaps left by traditional clinical trials, which often involve highly controlled patient populations that do not fully reflect the realities of everyday care.

Clinical trial participants tend to be more engaged, more adherent, and often healthier than many patients encountered in routine practice. They are more likely to complete follow-up visits, take medications as prescribed, and meet strict study criteria.

Real-world patients are different.

They miss appointments. They face transportation challenges. They struggle with medication affordability. They manage multiple chronic conditions simultaneously. Social and economic factors often influence treatment outcomes as much as clinical factors.

Understanding these realities is precisely why real-world evidence has become so valuable. It provides insight into how therapies perform in the environments where care actually occurs.

But even as health care has improved its ability to generate evidence, a critical question remains: How often does that evidence change what happens during a patient encounter?

Too often, valuable insights remain disconnected from clinical workflows. For life sciences organizations, this has important implications. The value of real-world evidence is no longer limited to publications, regulatory submissions, or retrospective analysis. Increasingly, its value will be measured by whether it helps identify patients sooner, supports more informed treatment decisions, and improves outcomes in routine clinical practice.

Why More Information Doesn't Equal Better Decisions

One of the greatest misconceptions in health care is that providing clinicians with more information automatically leads to better care.

In reality, health care is experiencing the opposite problem. Physicians today face a constant stream of alerts, guidelines, research publications, quality measures, and patient information. The volume of knowledge being generated is growing faster than any individual clinician can reasonably absorb.

Research has shown that physicians can receive dozens, and in some settings hundreds, of electronic health record alerts per day, contributing to widespread alert fatigue and clinician burnout.³ When every notification is urgent, it becomes increasingly difficult to identify the insights that truly matter.

This creates an unintended paradox. As health care becomes more data-rich, it also becomes increasingly insight poor – meaning it’s difficult for providers to identify the information that matters most for the patient sitting in front of them.

The answer is not to generate even more reports, dashboards, or evidence repositories. The answer is to make knowledge actionable. That means delivering the right insight at the right moment within the clinical workflow.

Imagine a patient who has visited multiple specialists over several years. One physician sees gastrointestinal symptoms. Another treats recurring orthopedic issues. A third manages ophthalmologic concerns. Individually, each provider sees only a fragment of the patient's story.

Collectively, however, those seemingly unrelated symptoms may point to an underlying rare disease or connective tissue disorder.

The opportunity is not simply identifying those patterns retrospectively. The opportunity is surfacing those insights during care, when providers and patients can act on them together.

From Evidence Generation to Evidence Activation

The next frontier for health care is activating the data we already have. Think of it this way: Evidence generation tells us what works. Evidence activation helps ensure that knowledge changes what happens next. This is where the conversation around real-world evidence needs to evolve.

Historically, life sciences organizations have focused heavily on evidence generation — creating the data necessary to demonstrate value, support regulatory requirements, and inform future research. Those efforts remain essential. But the industry should increasingly ask a different question: How do we turn evidence into action?

The most promising applications of real-world data may not be retrospective analyses or publications. They may be the tools that help providers identify patients earlier, recognize care gaps sooner, and make more informed treatment decisions in real time.

Rare disease identification offers a compelling example.

Many patients with rare diseases spend years navigating a diagnostic odyssey before receiving an accurate answer.⁴ In many cases, the relevant signals already exist within data points across the health care system. They are simply fragmented across providers, care settings, and data sources.

By connecting those signals and applying advanced analytics, health care organizations can identify patterns that would otherwise remain invisible.

The same principle applies to clinical trial recruitment, precision medicine initiatives, and population health management. The value comes not from possessing more data, but from using data to create timely interventions.

Over the next decade, health care organizations will increasingly compete not on how much data they possess, but on how effectively they turn that data into action. The winners will be those that can move insights from analysis into action faster than their peers.

The Future Is a Connected Health Care Ecosystem

Improving outcomes requires recognizing that no single stakeholder can solve this challenge alone. Providers, payers, life sciences organizations, researchers, and technology companies each hold part of the solution.

Life sciences organizations contribute to therapeutic innovation and scientific discovery. Providers deliver care and engage patients. Payers help drive population-level management strategies. Technology platforms increasingly serve as the connective tissue that enables information to move across the ecosystem and facilitate activation.

The greatest impact can only be achieved by organizations collaborating to bridge these traditionally separate worlds.

The industry has made extraordinary progress in generating data, evidence, and insight. Those investments have created tremendous value. But health care does not need another decade focused solely on collecting more information. It needs a decade focused on activating the information we already have.

The next chapter will be defined by our ability to ensure that knowledge reaches the point of care, where providers and patients can act on it together. When the right insight reaches the right clinician at the right moment, data stops being an asset and becomes an outcome.

Ultimately, success will not be measured by the volume of information health care produces. It will be measured by the number of lives improved because that information was put to use.

Sandy Leonard is general manager of life sciences at Arcadia.

References

1. World Economic Forum, "How data-driven digital healthcare tools cut costs and boost outcomes," weforum.org, updated 2024. https://www.weforum.org/impact/how-digital-healthcare-tools-cut-costs-boost-outcomes/
2. Roots Analysis, "Big Data in Healthcare Market Growth, till 2035," press release, published January 2024. https://www.rootsanalysis.com/press-releases/big-data-in-healthcare-market.html
3. Budd J. "Burnout Related to Electronic Health Record Use in Primary Care." Journal of Primary Care & Community Health. 2023 Jan-Dec;14:21501319231166921. doi: 10.1177/21501319231166921. PMID: 37073905; PMCID: PMC10134123. https://pmc.ncbi.nlm.nih.gov/articles/PMC10134123/
4. Faye F, Crocione C, Anido de Peña R, et al. "Time to diagnosis and determinants of diagnostic delays of people living with a rare disease: results of a Rare Barometer retrospective patient survey." European Journal of Human Genetics. 2024;32:1116-1126. Published 16 May 2024. doi: 10.1038/s41431-024-01604-z. https://www.nature.com/articles/s41431-024-01604-z