Transforming Patient Record Management
NeuroVisen builds a vendor-neutral, longitudinal patient record that follows every person across every system, every provider, and every border, so care never has to start from zero.
Fragmented data. Fragmented care.
Every additional system a patient touches adds another gap in the story a clinician is trying to read. Acute, primary, community, and mental health records sit in incompatible systems that were never designed to talk to each other.
Siloed systems
Acute, primary, community, and mental health records sit in siloed EPRs, each holding a fragment of the same person's history.
An incomplete view
Clinicians still lack a single, reconciled view of medications, allergies, problems, investigations, and recent events.
Strain across the system
Integrated Care Systems struggle to manage elective recovery, population health, and flow across every connected provider.
No continuity across borders
Travellers, migrants, and patients receiving remote care lose their entire history the moment they cross into a new system.
The compounding impact
One record. Every border.
A universal layer of trusted patient information, available in any system, at any point of care.
Single Patient Record
The Single Patient Record brings together every NHS interaction, medications, allergies, problems, investigations, and recent events, into one reconciled view that follows the patient across acute, primary, community, and mental health settings.
International Patient Record
The International Patient Record extends that same longitudinal history across borders, so a traveller, migrant, or patient in remote care no longer starts from zero the moment they enter a new health system.
From fragmented exhaust to a living record
Five layers turn scattered clinical data into one canonical, auditable patient story.
Multi-source data ingestion
HL7 v2, FHIR, CCD / C-CDA, and DICOM feeds connect directly into existing EHRs, labs, and imaging systems, without replacing any of them.
Master Patient Index & probabilistic matching
Every record is matched back to the right patient, even across systems that were never designed to agree on identity.
SNOMED, LOINC & RxNorm normalization
Diagnoses, results, and medications are translated into shared clinical languages, so nothing is lost in translation between systems.
Longitudinal data layer & API gateway
One continuous, auditable record per patient, served through HL7 FHIR APIs to any authorized system that needs it.
Optional LLM & RAG insights
Clean, coded, and consented data becomes the foundation for AI-generated summaries and clinical decision support, entirely optional and always traceable.
This platform monetizes the delta.
The ingestion platform is a data refinery that turns fragmented clinical exhaust into a proprietary, normalized, longitudinal clinical data asset, and the intelligence layers built on top of it.
Raw healthcare data
On its own, healthcare data is fragmented, inconsistent, locked inside individual vendor systems, and largely unusable for real analysis.
Normalized longitudinal data
Once ingested, matched, and coded, that same data becomes rare, extremely valuable, reusable across every product built on top of it, and defensible once established.
Six markets. One canonical record.
The same normalized data asset is licensed, subscribed to, and built on by six very different kinds of customers.
What it sells
A Single Patient Record platform as a core subscription, with optional modules for care coordination, longitudinal views, and clinical alerts.
How money is made
Annual enterprise licensing or per-member-per-month pricing, secured through multi-year contracts running three to seven years.
Why they pay
It eliminates duplicate testing, cuts the time clinicians spend hunting for data across systems, and improves patient throughput.
Key enabler
Canonical ingestion means data from every connected system appears as one continuous patient story.
What it sells
Population health analytics, screening gap identification, and outbreak and surveillance dashboards.
How money is made
Program-based funding paired with multi-year public sector contracts.
Why they pay
Reporting is often mandatory, prevention costs far less than treatment, and regional visibility improves in real time.
Key enabler
Temporal and terminology normalization make population-level analytics accurate instead of approximate.
What it sells
Predictive risk models, early warning systems for conditions like sepsis and deterioration, and AI-generated clinical summaries.
How money is made
Per-module licensing alongside usage-based pricing tied to AI calls and patients analyzed.
Why they pay
Better outcomes, lower malpractice exposure, and intelligence a clinician can act on immediately.
Key enabler
None of this works without data that is canonical, typed, coded, and temporally aligned underneath it.
What it sells
De-identified longitudinal datasets, cohort discovery services, and trial feasibility and recruitment support.
How money is made
Data licensing agreements and per-study fees.
Why they pay
Faster trials, stronger real-world evidence, and lower patient recruitment costs.
Key enabler
Canonical patient timelines make phenotype creation possible at scale.
What it sells
Utilization analytics, risk adjustment insights, and fraud detection.
How money is made
Subscription pricing combined with shared savings and outcome-based arrangements.
Why they pay
Reduced claims leakage and materially better cost forecasting.
Key enabler
Cross-source data surfaces patterns that stay invisible inside claims-only systems.
What it sells
Normalized clinical APIs, event streams, and developer access, plus a national patient record backbone that governments can white-label.
How money is made
Tiered, usage-based API billing for partners, and large-scale procurement with long-term operational agreements for national programs.
Why they pay
Partners skip building HL7 and FHIR ingestion from scratch and reach market faster. Governments meet interoperability mandates with a vendor-neutral foundation.
Key enabler
One canonical API replaces dozens of point-to-point integrations, backed by standards-first ingestion, compliance, and auditability.
Every customer makes the platform smarter for the next one.
Each new connection strengthens the dataset, improves the models built on it, and raises the value of the platform for everyone already on it.
Tap a stage
Tap or hover any stage to see how it feeds the next one.
Bring one record to every point of care.
For partnership, pilot, and platform inquiries, reach out below or connect with us on LinkedIn.
Headquarters
Mississauga, Ontario, Canada