Why Investors Are Betting on Real-World Evidence from EHRs to Shape the Future of Healthcare Innovation

07/05/2025

Professor Harnett

In the world of healthcare innovation, few assets are as undervalued - or as powerful - as the data collected during everyday patient care. For the past two decades, Electronic Health Records (EHRs) were primarily viewed as clinical tools or billing systems.

Today, investors see something more: a vast, underutilized trove of Real-World Evidence (RWE) with the potential to revolutionize everything from drug development to care delivery to portfolio strategy.

As venture capital and private equity firms deepen their presence in healthcare and life sciences, many are turning their attention to how RWE from EHRs can fuel predictive models, generate research hypotheses, and analyze clinical outcomes - not just to improve health, but to uncover powerful business opportunities.

Real-World Evidence: A Market-Moving Asset

Real-World Evidence refers to health-related insights derived from data sources outside of traditional clinical trials. That is, what actually happened to patients over the course of time based on queries about their phenotypes, that is, observable characteristics about health and outcomes. All this data is real, not statistically generated.

This includes:

• EHR data from hospital systems and ambulatory practices

• Insurance claims and billing records

• Patient registries

• Wearables and home monitoring devices

• Patient-reported outcomes and social determinants

Among these, EHRs are the crown jewel - providing structured and unstructured data from billions of patient interactions: diagnoses, prescriptions, lab values, imaging, clinician notes, and more. When de-identified and aggregated responsibly, this data becomes a strategic resource with immense commercial value.

Predictive Modeling: From Risk Scoring to Revenue Forecasting

For investors, one of the most exciting applications of EHR-derived RWE is in predictive modeling. These models use historical clinical data to forecast future outcomes such as disease progression, treatment response, and healthcare utilization. Investors see these models as drivers of:

• Risk stratification in population health platforms

• Operational efficiency in provider groups

• Clinical decision support tools

• Personalized medicine platforms including genetic profiling and the use of AI

For example, if a health tech startup can use EHR data to accurately predict hospital readmissions, chronic disease flare-ups, or sepsis onset, it can unlock significant cost savings for providers and payers - translating into enterprise value. These insights also help investors assess a company’s real-world impact, a growing consideration in health tech investing.

In drug development, predictive models trained on RWE can de-risk clinical trials by identifying optimal trial sites, refining inclusion criteria, or simulating control arms - dramatically shortening timelines and costs.

Hypothesis Generation: Spotting the Next Breakthrough

Investors also appreciate how EHR data can support hypothesis generation - the crucial early step of research that identifies novel questions or associations worth pursuing.

Imagine a portfolio company that notices, through EHR analysis, that a commonly prescribed diabetes drug appears to reduce the risk of Alzheimer’s in a certain patient population. That insight could form the basis of a new indication, patent extension, or licensing deal.

EHR-based hypothesis generation can also lead to:

• Biomarker discovery

• Repurposing opportunities

• Identification of underserved populations or unmet needs

These opportunities are particularly attractive to investors seeking asymmetric upside: a modest investment in RWE infrastructure or analytics could yield a high-value therapeutic lead or new market category.

Clinical Outcomes Analysis: The Real-World Proof Investors Need

Traditional clinical trials often struggle to reflect the complexity of real-world care. Investors are increasingly relying on RWE to validate whether a technology, drug, or care model performs outside the clean confines of the trial setting.

Through EHR-based outcomes analysis, investors can:

• Validate the effectiveness of therapeutics, diagnostics, or digital tools across diverse populations

• Measure cost-effectiveness and ROI in payer or provider settings

• Support reimbursement cases by generating evidence for health economics and outcomes research (HEOR)

For example, an investor evaluating a cancer diagnostics firm can analyze outcomes data from multiple institutions to confirm that its test actually changes treatment decisions or improves survival in practice - not just in published papers (see July 11, 2024 blog post on about atrial fibrillation and risk of stroke).

By helping investors de-risk clinical and commercial assumptions, RWE provides not just data, but strategic clarity. Pharmaceutical companies and Contract Research Organizations are primary beneficiaries.

RWE as a Due Diligence Tool

Beyond investing in startups that generate RWE, some firms are now using real-world evidence as part of their diligence process. Especially in biotech and medtech deals, access to large-scale clinical data allows investors to:

• Benchmark a product’s real-world performance against competitors

• Validate patient-reported outcomes or claims

• Understand real-world adoption and utilization patterns

As a result, investors are increasingly partnering with health systems, data aggregators, and analytics platforms to gain proprietary insights.

Some investors even negotiate data-sharing rights into their portfolio companies’ contracts - recognizing that access to clean, relevant EHR data is a source of long-term value.

Why Now? Key Trends Driving Investor Interest

Several macro trends are accelerating investor interest in EHR-derived real-world evidence:

1. Policy tailwinds: The 21st Century Cures Act and the FDA’s evolving stance on RWE create new pathways for regulatory acceptance, labeling expansion, and approval of digital therapeutics.

2. Data interoperability: HL7 FHIR APIs and common data models like OMOP are breaking down silos and making EHR data more usable across institutions.

3. AI and NLP maturity: Advanced tools now enable scalable analysis of imaging, genomics and unstructured notes - long considered inaccessible data.

4. Value-based care: As providers and payers shift toward outcomes-based models, RWE becomes critical for measuring success.

5. Patient-centric innovation: RWE supports diversity, equity, and inclusion in research by better representing real-world populations.

Risks and Responsibilities

Of course, EHR-based RWE comes with challenges: data fragmentation, inconsistent coding, privacy concerns, and potential bias. Sophisticated investors understand these limitations and increasingly look for companies with:

• Strong data governance and de-identification protocols

• Clinically validated models and endpoints

• Transparent methodologies and peer-reviewed evidence

Responsible RWE use isn't just ethical - it's a strategic differentiator.

Conclusion: The New Gold Standard

Real-World Evidence is fast becoming the new gold standard in healthcare investing. For those who know how to collect, analyze, and apply it, EHR-derived data opens doors to smarter bets, faster validation, and stronger returns.

Whether you're backing a predictive analytics firm, a digital health platform, or a next-gen biotech, one thing is clear: the future of health innovation, and health investing, will be built on the real-world stories embedded in EHRs.