Turn healthcare data into higher-quality data — across organizations, without moving the records.
Move the question — not the data.
Most platforms hand you a toolbox and expect you to clean, normalize, and enrich your data yourself. HDIM does it for you: we operationalize and enhance data quality in place, then deliver better data to providers (care-gap closure, HEDIS, point-of-care) and researchers (de-identified, k ≥ 11) — for HIEs, ACOs, health plans, and health systems. Your PHI never leaves your boundary.
Live system walkthrough
Review the running clinical experience, care-gap workflows, and role-based views before a buying conversation.
Validation dashboard
Inspect the test, architecture, and control evidence that backs the implementation story.
Evidence room
See packaged buyer-facing evidence for architecture, implementation, and release-grade diligence.
Architecture review
Understand the deployment boundary, event-driven pipeline, and data-control posture without reading source code first.
The problem isn’t more dashboards. It’s data you can trust — without building that yourself.
Quality and research teams already know the pain. The harder part is operationalizing data quality across organizations without forcing another opaque platform decision.
The data-intelligence gap is left to you
Most platforms hand you raw feeds and a toolbox, then expect your team to clean, normalize, and enrich the data before it is usable — an open-ended project you have to staff and own.
Providers can’t trust the answers
When the underlying data quality is uneven, clinicians hesitate to act on care-gap and quality outputs at the point of care — the answers arrive, but not the confidence to use them.
Proof is hard to evaluate
Enterprise reviewers need to see what is live, what is validated, and what controls exist before they commit time or money.
Your data-intelligence partner — not another data tool.
HDIM operationalizes and enhances your data quality in place, then serves better data to providers and researchers — without surrendering deployment control. The product story stays tied to an implementation story you can actually inspect.
- ✓We operationalize and enhance your data quality for you — not a DIY data-cleaning project you staff.
- ✓Serve providers with data they can trust at the point of care: care-gap closure, HEDIS, quality workflows.
- ✓Serve researchers with de-identified data (k ≥ 11) for regional secondary use.
- ✓Keep PHI and operational control within your infrastructure boundary — across organizations.
Evidence buyers can use internally
The first engagement should leave buyers with enough implementation signal to brief executives, technical leaders, and reviewers without hand-waving.
Every major claim on this site has a proof destination.
Buyers should be able to move from headline to proof without needing a custom explanation. These are the first-stop destinations for diligence.
Evidence Room
Buyer-facing proof packages, readiness materials, and curated review paths.
Validation
Architecture decisions, quality controls, and implementation evidence tied together.
Architecture
Deployment boundaries, event-driven flow, and system shape explained for evaluators.
The buyer story is anchored to real screenshots, role-based views, and validation artifacts rather than abstract marketing diagrams alone.
Start with a pilot. Expand after proof.
Buyers do not need to commit to the largest deployment path first. The site now reflects a staged motion: validate fit, confirm proof, then scale to the operating model you need.
Starter
Single-node Docker deployment for proof of concept
Professional
Clustered deployment with high availability
Enterprise
Kubernetes deployment for maximum scale
Hybrid Cloud
On-premise gateway with cloud compute
A guided path from first look to design partner.
See your data operationalized
Start with DQM on a sample of your feeds: watch the data get profiled, normalized, and enhanced — the data-intelligence work done for you (on synthetic data in the demo).
Prove it for providers and researchers
Confirm the improved data drives care-gap and HEDIS workflows providers can trust, and de-identified research output (k ≥ 11) researchers can use.
Become a design partner
Move from proof to a design-partner engagement — early access, roadmap influence, and a scoped path to a first paid pilot.
Questions buyers ask early
The first pass on the site should answer the basics, then hand buyers to proof surfaces and a walkthrough.
How long does deployment take?
Pilot deployment takes 2-3 weeks, Growth tier 4-8 weeks, and Enterprise 8-12 weeks. The timeline depends on your infrastructure readiness and integration complexity.
Do you support our EHR?
We support Epic, Cerner, Athena, and any FHIR R4-compliant server. If your EHR supports FHIR, we can integrate with it.
Can we customize the measures?
Yes! We include 52 HEDIS measures out of the box, and you can add unlimited custom measures using our CQL framework. Custom measures start at $3K-8K each.
Is our data secure and compliant?
Yes. We're HIPAA-compliant with multi-tenant isolation, HIPAA audit logging, TLS 1.3 encryption, and role-based access control. Data never leaves your FHIR server - we query it directly.
Become our next data-intelligence partner.
The fastest way to evaluate HDIM is to see it on your data story together: operationalized data quality, the answers providers can trust, and de-identified research output — in one session.