FHIR ingestion pipelines
Production-grade ingestion from EHR FHIR endpoints with PHI classification and quality validation.
Healthcare Data Analytics
Healthcare analytics platforms — PHI-safe and clinically grounded
We build healthcare analytics platforms with PHI-safe data pipelines, FHIR-native ingestion, clinical dashboards, and an ML layer tuned for regulated environments.
PHI-SafeFHIR SourceHIPAA-ReadyBAA-Covered
Trusted by global innovators
Analytics without shortcuts
Healthcare analytics is rarely just BI. It's PHI handling, terminology resolution, clinical context, and ML governance all at once.
3
Dashboard classes — population, clinical, operational
FHIR
Primary source for new pipelines
100%
BAA coverage on analytics infrastructure
What it is
Healthcare analytics is data engineering plus clinical context
Healthcare analytics turns clinical, claims, and operational data into signals that support clinical, business, and population-level decisions. Done well, it powers risk stratification, population health, clinical quality measures, and operational improvement.
The hard parts aren't the dashboards. They're PHI handling, terminology resolution (SNOMED, LOINC, ICD-10, RxNorm), clinical context preservation, and ML governance — all before you write the first SQL query.
Core capabilities
What we build
A full healthcare analytics stack — ingestion, warehouse, dashboards, ML.
HL7 / claims / operational ingestion
Legacy clinical and administrative data alongside FHIR sources.
Data lake / warehouse
Healthcare-tuned data architecture on Snowflake, BigQuery, Databricks, or native cloud.
Terminology services
SNOMED, LOINC, ICD-10, RxNorm resolution and mapping as first-class infrastructure.
Population health analytics
Cohort definition, risk stratification, and care gap identification at population scale.
Clinical dashboards
Provider-facing dashboards for quality measures, clinical performance, and individual patient views.
Operational dashboards
Capacity, throughput, revenue cycle, and operational KPIs for health system leadership.
ML & predictive models
Risk prediction, readmission modelling, no-show forecasting under BAA-covered infrastructure.
De-identification services
Safe Harbor and Expert Determination de-identification for research and partner access.
Reference architecture
PHI-safe analytics architecture
We design analytics architecture in three layers — ingestion, analytics, and consumption — each with explicit PHI boundaries.
Ingestion layer
- FHIR R4, HL7 v2, claims, and operational systems
- PHI classification on ingestion
- Data quality validation and reconciliation
Analytics layer
- Data lake / warehouse with PHI segregation
- Terminology services for clinical coding
- Derived tables for dashboards and ML
Consumption layer
- Clinical, operational, and population dashboards
- ML models under BAA for risk and prediction
- De-identified views for research and partner access
Where it runs
Healthcare analytics use cases
Population health
Risk stratification, care gap closure, and quality measure tracking at cohort scale.
Clinical quality improvement
Quality measure dashboards, specialist-level performance, and improvement initiatives.
Revenue cycle analytics
Claims analytics, denial tracking, and revenue cycle optimisation.
Capacity & operations
Capacity forecasting, staffing analytics, and operational KPI tracking.
Research & real-world evidence
De-identified data access for research, RWE generation, and partner analytics.
Payer analytics
Risk scoring, utilisation analytics, and care management support for payer orgs.
How we ship
Our healthcare analytics delivery process
Step 01
Use case discovery
Which decisions need to be better informed, by what evidence, for whom?
Step 02
Data source mapping
Clinical, claims, and operational data sources with PHI classification and access plan.
Step 03
Architecture & infrastructure
PHI-safe data lake / warehouse, terminology services, and BAA coverage.
Step 04
Ingestion & modelling
Pipelines, derived tables, and clinical coding alignment.
Step 05
Dashboards & ML
Clinical, operational, and population dashboards plus targeted ML models.
Step 06
Governance & operations
Data governance, access review, and ongoing pipeline health monitoring.
Common failure modes
Where healthcare analytics builds usually fail
Challenge
PHI sprawls across analytics stack
Agnotic approach
PHI classification on ingestion, column-level masking, and BAA coverage across every analytics vendor.
Challenge
Terminology chaos — same concept coded three ways
Agnotic approach
Terminology services as first-class infrastructure, not a reporting afterthought.
Challenge
Dashboards measure what's easy, not what matters
Agnotic approach
Use case discovery anchored on clinical and operational decisions, not data availability.
Challenge
ML models ship without governance or drift monitoring
Agnotic approach
Model registry, drift monitoring, and retraining cadence built into the ML lifecycle.
Standards we build against
Analytics standards
HIPAAGDPRFHIRHITECHHITRUST
Engineered for Healthcare Compliance, Backed by Global Standards
Every Agnotic healthcare build is architected for privacy, interoperability, and regulatory readiness from the first commit — not retrofitted before launch.
Health Insurance Portability and Accountability Act
Protect PHI with privacy-first architecture, encrypted storage and transmission, strict access controls, and traceable audit logs.
General Data Protection Regulation
Implement lawful consent flows, data minimization, retention controls, and secure processing for sensitive reproductive and health data.
Fast Healthcare Interoperability Resources
Enable standardized health data exchange across apps, care teams, and systems through robust FHIR-ready APIs and mappings.
Health Level Seven International
Support enterprise-grade interoperability with HL7-based integrations for records, events, and clinical messaging workflows.
Health Information Trust Alliance
Align security programs to healthcare-specific controls and risk management practices trusted by providers and partners.
Health Information Technology for Economic and Clinical Health Act
Design with breach notification readiness, digital record safeguards, and operational controls that support regulated care programs.
Food and Drug Administration Software as a Medical Device
Plan software quality, traceability, and documentation pathways for products that may require SaMD review and regulatory submission.
Medical Device Regulation (European Union)
Prepare EU market-ready processes for risk classification, evidence tracking, and lifecycle governance under MDR expectations.
Substance Abuse and Mental Health Services Administration (42 CFR Part 2)
Apply confidentiality controls and consent-aware sharing models for behavioral and mental health related data experiences.
We Are Technology-Agnostic
With a diverse technology stack, we deliver solutions using a technology-Agnostic approach to meet your unique needs.
Wireframe & Ideation
User Experience
Real-Time Projects
Voices of Success
We don't just build products; we forge lasting partnerships. See how we've helped industry leaders transform their vision into technical reality.
"I can clearly see how Agnotic has a unique way of handling end-to-end development. They are always active on quick chat and provide support quickly."
Aaron Phelan
Founder, Benchmark
"Agnotic is the best technical team we evaluated. Their engineering excellence made our work dramatically easier and allowed us to stay focused on what matters most for maternal care outcomes. They took full ownership of the technical execution, and we are always happy to continue working together."
Kim Smith
Founder, My Lauren
"Agnotic combines deep technical expertise with strong domain knowledge. They understand the business context, anticipate challenges, and make collaboration smooth and effective."
John Pasmore
Founder, Latimer
Related Solutions
Frequently Asked Questions
Healthcare analytics has to handle PHI under HIPAA, resolve clinical terminology (SNOMED, LOINC, ICD-10, RxNorm), and preserve clinical context across data sources. It also needs to integrate with regulated systems (EHRs, claims, labs). General BI tools often don't carry these primitives — you either build them on top or use healthcare-specific tooling.
Book a healthcare analytics demo
Tell us what decisions you need to inform and what data you have. We'll share an analytics architecture and delivery plan.