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For ACOs & value-based care

Close care gaps before the scorecard — on data you can trust.

Most platforms leave the data-cleaning to you, then measure quality on whatever quality the data happens to have. HDIM operationalizes and enhances your data first, then drives care-gap closure and HEDIS on it — in near real time, so quality work happens before the scorecard, not after. Your PHI never leaves your boundary.

How it works

Step 1
Operationalize the data (DQM)

Data Quality Monitor profiles your feeds, then normalizes and enriches them in place — the data-intelligence work is done for you, not a project your team staffs.

Step 2
Close gaps before the scorecard

Higher-quality data drives near-real-time care-gap closure and HEDIS measurement, so your quality team acts while it can still move shared-savings performance.

Step 3
Prove it for review

Buyer-grade evidence — architecture, controls, deployment — that your quality and compliance reviewers can use internally.

Operator-safe by construction

  • De-identified research output enforces a k ≥ 11 small-cell floor.
  • PHI stays inside your boundary — nothing is centralized.
  • Full audit trail; SOC 2 readiness posture.
  • Demos run on synthetic data only.