Stood up an automated, always-on compliance program for an enterprise health plan — replacing manual spreadsheets and point-in-time consultant reviews with a continuous system that watches the provider network year-round
HealthcareAutomated compliance for an enterprise health plan — provider-directory accuracy, CMS network adequacy, and audit-readiness run as an always-on program instead of a manual fire drill.
Healthcare / Health Insurance (US Medicare Advantage & D-SNP)
clearspringhealthcare.com
Directory accuracy
- Provider record 0148Match
- Provider record 0149Match
- Provider record 0150Stale
- Provider record 0151Match
- Provider record 0152Phantom
Accuracy
96.4%
CMS adequacy
Pass
The challenge
Clear Spring Health is an enterprise-scale U.S. Medicare Advantage and Special Needs Plan carrier, operating a large provider network across multiple states. At that scale, CMS compliance — keeping the provider directory accurate, proving network adequacy, and staying audit-ready — is unforgiving: a sprawling network (in our InsureLytix work it surfaced as roughly a 59.8K-provider network across MA and D-SNP lines) cannot be policed with spreadsheets, quarterly consultant sprints, and manual phone verification without leaving ghost listings, stale records, and audit exposure. They needed compliance run as an always-on program, not a periodic fire drill.
Healthcare
Healthcare / Health Insurance (US Medicare Advantage & D-SNP)
What we built
The system, in parts.
Provider-directory accuracy engine: continuous cross-checks against authoritative sources (NPI registry and plan-of-record data), classifying every row as match, stale, or phantom so the directory stays close to ground truth at network scale
Decay alerting and remediation queues that flag records drifting out of date and route them for correction before they become audit findings — turning a recurring liability into a managed workflow
CMS network-adequacy monitoring: time-and-distance / drive-time checks against CMS standards with county-level pass/fail scoring, so adequacy gaps surface continuously instead of at quarter-end
Document-to-structured-data intake: messy roster, credentialing, and provider-update files normalized onto a clean provider/facility model with row-level validation, so unstructured payer documents feed the compliance program without manual re-keying
Audit-readiness layer: durable, timestamped logs of every check, classification, and remediation decision, giving the plan a defensible trail and keeping humans in oversight of every change
Outcomes
What changed for them.
Provider-directory accuracy and network adequacy shift from periodic, manual reviews to an always-on, CMS-aligned program for an enterprise-scale plan
Ghost-network and stale listings are caught continuously and routed to remediation, reducing the audit-finding surface across a large multi-state network
Compliance staff are freed from spreadsheet reconciliation and manual phone verification to focus on exceptions and judgment calls
Unstructured roster and credentialing documents become clean, structured, validated records without manual data entry
Every compliance decision is logged and reviewable, giving the plan a defensible audit trail with humans in control
How it’s built
The stack.
Engagement summarized from delivery records; some figures are directional.
Provider-directory accuracy engine (match / stale / phantom classification)NPI registry & plan-of-record cross-checksCMS network-adequacy / time-and-distance scoringCounty-level adequacy pass/fail analyticsDocument extraction & schema validation (roster / credentialing intake)Decay alerting & remediation queuesImmutable audit loggingHuman-in-the-loop review
More work
See allTwo ways to start
Want a system like this?
Tell us the workflow you want to run itself. We will scope a focused first project — designed, built, and operated, with humans in control.