Cancer care rarely follows a simple, linear path.
A patient’s diagnosis and treatment journey can weave through primary care practices, community specialists, academic medical centers, diagnostic facilities, and specialized oncology networks. Along the way, their disease evolves at the molecular level long before that progression is captured by a billing code generated from those medical encounters. Critical treatment decisions frequently hinge on nuance: biomarkers, pathology findings, functional status, prior responses, toxicities, or observations documented strictly within a clinician’s narrative notes.
For real-world evidence (RWE) researchers, this complexity creates a fundamental challenge: How do we reconstruct the patient journey with enough depth, continuity, and timeliness to answer increasingly sophisticated oncology questions?
As OMNY Health continues to deepen its data capabilities across solid tumors and hematologic malignancies, a clear, consistent theme guides our platform: The next generation of oncology RWE requires more than patient volumes, it requires connected, continuous clinical context.
Indication Insights
Below are some examples of how OMNY Health’s connected data ecosystem directly addresses data gaps across different types of malignancies.
In metastatic breast cancer (mBC), structured fields and ICD codes capture only part of the story.
Critical disease shifts often surface first within pathology reports and unstructured clinical narratives. Understanding nuances like endocrine resistance or evolving HER2 expression (including HER2-low and ultra-low status) requires visibility beyond prescription fill dates.
By converting unstructured clinical documentation into research-ready variables, researchers can move beyond simply identifying treatment events by gaining the context needed to evaluate disease progression, treatment sequencing, and long-term outcomes.
Few therapeutic areas highlight the necessity of molecular context like lung cancer.
As biomarkers like EGFR, ALK, KRAS, and BRAF shape frontline and subsequent care, evaluating precision medicine in the real world requires connecting molecular findings directly to treatment decisions and outcomes.
Connecting deep EHR-derived clinical details with longitudinal claims and mortality data allows researchers to see not just which treatment regimens patients received, but how specific molecular profiles directed the course of care in the real world.
Colorectal cancer (CRC) clearly demonstrates the limitations of relying solely on broad diagnosis codes. Two patients presenting with the exact same stage can experience dramatically different clinical pathways based on:
- Left- versus right-sided tumor location
- MSI / mismatch repair (MMR) status
- Longitudinal carcinoembryonic antigen and pathology findings
- Surgical interventions and history
Connecting these granular clinical variables with healthcare utilization, cost, and survival data enables researchers to bridge clinical and economic outcomes from evaluating later-line adherence to mapping risk-adjusted real-world survival.
For rapidly progressing diseases such as pancreatic ductal adenocarcinoma (PDAC), data completeness is only half the battle. Time matters.
A patient’s functional status and disease burden can shift within weeks. Data sources burdened by latency and lack of clinical notes risk missing crucial inflection points entirely.
OMNY Health’s pancreatic cancer dataset currently includes more than 100,000 patient lives, integrating unstructured EHR notes, claims, and mortality data with less than a 30-day lag from time of treatment to data availability. This reduced data lag helps researchers track rapid CA 19-9 trends, ECOG performance score shifts, pain management strategies, and frontline regimen performance in near real-time which is vital for building robust external control arms (ECAs) and burden-of-disease studies.
Hematologic Malignancies
The rise of CAR-T, bispecific antibodies, and targeted cell therapies has transformed care in multiple myeloma and lymphoma while making real-world tracking significantly more complex.
- Multiple Myeloma: Knowing drug histories alone doesn’t reveal when a patient became double- or triple-class refractory, or whether discontinuation was driven by toxicity or progression. Integrating clinical notes, cytogenetics, and bone marrow findings with longitudinal claims clarifies post-BCMA outcomes and line-of-therapy definitions.
- Lymphoma: Across a cohort of more than 230,000 unique patient lives, combining unstructured narratives, pathology, and claims allows researchers to investigate complex staging, cytogenetic drivers, and post-progression pathways as advanced therapies move into earlier lines of care.
- Leukemia: Spanning over 172,000 patient journeys, billing codes fail to capture critical progression milestones like blast counts crossing 20% or emerging cytogenetic risk profiles during the MDS to AML disease spectrum. Unifying structured EHR data, claims, and unstructured clinical notes enables precise tracking of disease transformation timing, molecular risk, and real-world outcomes across care settings.
Prostate cancer care is notorious for cross-specialty fragmentation. A patient’s care team often spans community urology practices, multispecialty clinics, and tertiary oncology centers. When these records remain isolated, critical transitions vanish.
By linking data across urology and oncology environments, researchers can track the transition from non-metastatic to metastatic castration-resistant prostate cancer (mCRPC), calculate PSA kinetics, monitor Gleason scores, and evaluate long-term outcomes across distinct care settings.
Connecting Clinical Depth with Comprehensive Longitudinal Resource Utilization
Deep clinical context reaches its full potential when paired with comprehensive healthcare utilization data captured in administrative insurance claims/billing data.
OMNY’s deep EHR clinical data, including structured metrics and billions of unstructured clinical notes, is available linked directly with longitudinal claims for overlapping patients.
For Health Economics and Outcomes Research (HEOR) and RWE teams, this linkage unlocks the ability to study broader healthcare resource utilization (HCRU), and economic burden within the exact same patient population.
From Bigger Data to Deeper Evidence
Across solid tumors and hematologic malignancies, specific research questions vary, but the underlying data imperative remains the same: Researchers need to know more than whether a billing code appeared in a file.
To unlock actionable insights, researchers also must:
- Capture the molecular profiles driving treatment choices
- Identify progression the moment it is documented by a clinician
- Understand the “why” behind treatment plan decisions and pivots
- Bridge patient journeys across care settings and specialty boundaries
- Tie clinical events directly to utilization, cost, and survival
Powered by a provider-led ecosystem representing over 175 million longitudinal patient lives, OMNY Health provides the infrastructure required to answer these questions with confidence. Connect with our team to explore our oncology cohorts and how OMNY data can support your real-world evidence strategy.
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