Practices & health systems
Radiology groups modernizing the data analytics workflow.
Data Analytics for Radiology
Data Analytics for Radiology
We build data analytics for radiology — pairing the engineering of a purpose-built data analytics with the real workflows, codes, and devices of radiology care, all handled to HIPAA standards.
HIPAA-ReadyFHIR R4InteroperablePHI-Safe
Trusted by global innovators
What data analytics for radiology involves
Radiology care has specific needs — Radiology software is an interoperability problem: DICOM imaging, RIS worklists, structured reporting, and increasingly AI triage — all of which have to move reliably without dropping images or context. A data analytics built for it has to serve those needs directly rather than repurpose a generic product.
Building data analytics for radiology means solving turning the specialty's clinical and operational data into decisions, not just dashboards, tuned to the codes and workflows that matter here (DICOM / DICOMweb imaging interop, HL7 v2 ORM/ORU orders & results, FHIR R4 ImagingStudy & DiagnosticReport), with PHI handled to HIPAA standards from the first commit.
What we build into Radiology Data Analytics
The data analytics engineering, tuned to radiology.
Specialty data warehouse
Specialty data warehouse, built for the radiology use case.
Quality and outcome dashboards
Quality and outcome dashboards, tuned to radiology workflows.
Population and operational analytics
Population and operational analytics for a connected, useful data analytics.
Radiology codes & workflow
Built around the codes and workflow that matter in radiology: DICOM / DICOMweb imaging interop, HL7 v2 ORM/ORU orders & results, FHIR R4 ImagingStudy & DiagnosticReport.
Privacy-first by design
PHI protected with encryption, access controls, and audit logging under a BAA.
Built to integrate
We engineer for turning the specialty's clinical and operational data into decisions, not just dashboards, connected to the systems radiology care already uses.
Where it fits
Who builds data analytics for radiology
Teams bringing better radiology products and workflows to market.
Digital health startups
Radiology-focused data analytics products.
MedTech & device makers
Radiology data analytics tied to devices and data.
Payers & programs
Radiology data analytics as a benefit or program.
Built for radiology, engineered to last
Data Analytics for radiology earns its place by fitting the workflow, not the other way round.
Interop-first
Imaging that moves without dropping context
Interoperable
FHIR R4, HL7 v2, and SMART on FHIR by default
MVP-ready
Core data analytics workflow for radiology, shipped then scaled
Compliance-First Healthcare App Development Services Backed by Global Standards
15-Minute Scoping Call01
HIPAA
Health Insurance Portability and Accountability Act
Protect PHI with privacy-first architecture, encrypted storage and transmission, strict access controls, and traceable audit logs.
02
GDPR
General Data Protection Regulation
Implement lawful consent flows, data minimization, retention controls, and secure processing for sensitive health data.
03
FHIR
Fast Healthcare Interoperability Resources
Enable standardized health data exchange across apps, care teams, and systems through robust FHIR-ready APIs.
04
HL7
Health Level Seven International
Support enterprise-grade interoperability with HL7-based integrations for records, events, and clinical messaging workflows.
05
HITRUST
Health Information Trust Alliance
Align security programs to healthcare-specific control and risk management practices trusted by providers and ecosystem partners.
06
HITECH
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.
07
SaMD
FDA Software as a Medical Device
Plan software quality, traceability, and documentation pathways for products that may require SaMD review and submission.
08
MDR (EU)
Medical Device Regulation (European Union)
Prepare EU market-ready processes for risk classification, evidence tracking, and lifecycle governance under MDR expectations.
09
SAMHSA
Substance Abuse and Mental Health Services Administration
Apply confidentiality controls and consent-aware sharing models for behavioral and mental health data experiences.
Why radiology needs a purpose-built data analytics
Radiology codes, standards & devices
DICOMHL7FHIR
Our Process
How we build data analytics for radiology
We prove the core workflow with real users before scaling — clinical fit and adoption decide the outcome.
1.
Discovery & Clinical Design
We map the radiology workflow and the core data analytics job to be done.
Workflow-shaped
2.
Core Build
We build the data analytics substance with interoperability and PHI handling engineered in.
Compliant
3.
Integrations
EHR, device, and standards integration so it connects to the systems already in use.
Connected
4.
Launch & Iterate
A measured launch tracking adoption and outcomes, then iteration.
Adoption-tuned
Frequently Asked Questions
It is built around radiology — Radiology software is an interoperability problem: DICOM imaging, RIS worklists, structured reporting, and increasingly AI triage — all of which have to move reliably without dropping images or context — and its codes and workflows (DICOM / DICOMweb imaging interop, HL7 v2 ORM/ORU orders & results, FHIR R4 ImagingStudy & DiagnosticReport), rather than a one-size-fits-all product. That fit is where the clinical value and the engineering live.
Ready to build data analytics for radiology?
Tell us your radiology workflow and goals. We'll return a plan for data analytics that's clinically credible, interoperable, and built to ship.
contact@agnotic.com
Partnerships
contact@agnotic.com