Continuous Compliance Infrastructure for Accreditation Bodies
Deterministic rule evaluation, clinical AI analytics, and continuous facility monitoring built for organizations that set and enforce healthcare standards.
233
executable compliance rules
17
condition types for clinical and operational standards
24/7
Facilities evaluated continuously, not once per survey cycle
What Happens Between Surveys
Facilities go dark between cycles
Accreditation evaluates a point in time. Between surveys, compliance status is unknown. Facilities that passed last year may have drifted. The accreditor has no visibility until the next scheduled review.
Standards enforcement is manual
Surveyors review documentation, interview staff, inspect records. Each survey is a labor-intensive, time-bounded event. The number of facilities an accreditor can evaluate is constrained by the number of surveyors available.
Cross-facility analytics require manual aggregation
National trends, regional patterns, and program-level benchmarks are assembled by hand from individual survey reports. The data exists, but it is not structured, not connected, and not queryable.
These constraints are structural. They follow from the fact that standards live in documents and compliance is measured by human observation at scheduled intervals. If standards lived in executable code and compliance data flowed continuously, the constraints disappear.
Standards Are Executable, Not Documentary
Every accreditation standard clause can be encoded as a testable rule. Personnel credential requirements, volume thresholds, report completeness criteria, quality indicator targets, equipment maintenance schedules, policy currency checks. Each becomes a condition with defined inputs, a deterministic evaluation, and a traceable provenance citation back to the published standard.
Encode
Standard clauses are authored as structured rule definitions. Each rule has an identifier, a human-readable description, a condition type and parameters, a compliance decision, and a provenance citation linking to the specific published standard clause.
Evaluate
The rule engine loads all rules at startup, validates their structure, and evaluates each one against facility data. The evaluation is deterministic: same input always produces the same output. No machine learning model is involved in rule evaluation.
Report
Each evaluation produces a compliance status with the evidence that was examined and the standard clause that was applied. Findings are traceable from the facility-level score down to the individual clinical record that caused a rule to fire.
Technical depth
17 condition types covering personnel, volumes, documentation, quality, equipment, and policy.
4 scoring models: graduated (weighted average), binary (all-pass required), threshold-count, and weighted.
New accreditation programs are a new rule directory. Write the rules, validate the schema, deploy. Enrolled facilities are evaluated at the next cycle.
Standards updates are version-controlled. Each rule carries a provenance citation. Disputes are resolved by examining the rule definition, the input data, and the evaluation logic.
Rule evaluation contains no AI. It is pure deterministic logic. AI sits above the evaluator for investigation, explanation, and analytics. The compliance decision itself is always reproducible.
Three Layers, One Platform
Rule Engine
The compliance foundation. 233 executable rules across multiple standards frameworks. 17 condition types. 4 scoring models. Deterministic evaluation against clinical and operational data ingested via FHIR R4 and facility attestations. Every rule carries a provenance citation to its published standard clause.
What it replaces: manual document review, self-reported compliance checklists, point-in-time survey assessments.
AI Analyst
A clinical AI agent with accreditation-specific tools. Natural-language queries against live compliance data. Mock survey simulation. Gap analysis across standards. Remediation plan drafting. Rule-fire explanation with evidence citations.
Human-in-the-loop approval gates on all actions that modify data or produce external documents.
What it replaces: manual compliance investigation, ad-hoc report assembly, survey preparation binders.
Continuous Monitoring
Nightly evaluation of all enrolled facilities. Drift detection: standards that were met yesterday but are not met today. Morning compliance briefings for accreditor and facility staff. Risk-based prioritization for facilities moving away from compliance.
What it replaces: the assumption that compliance status is static between survey cycles.
These three layers share one database, one audit trail, and one access control system. A finding from the rule engine surfaces in the AI analyst's investigation and triggers a monitoring alert. There is no data export between layers. It is one system.
Accreditor View and Facility View
Mode 1
Accreditor Platform
The accreditation organization deploys a cross-facility dashboard. All enrolled facilities are visible in one view. Compliance scores, findings, trends, and risk indicators are aggregated nationally, regionally, and per-facility.
- Cross-facility compliance dashboard with drill-down
- Risk-based survey scheduling
- Standards management: author, version, deploy, and evaluate rule packs
- AI analyst with multi-facility queries
- Program-level benchmarking across all enrolled facilities
The accreditor controls the standards. The platform enforces them.
Mode 2
Facility Portal
Individual facilities connect to the platform and see their own compliance status. They do not see other facilities.
- Real-time compliance scores against all enrolled standards
- Evidence shelf: documentation organized by standard clause
- Mock survey preparation: simulate a survey against current data
- Gap analysis: compare current state against target
- FHIR R4 integration with existing electronic health records
The accreditor deploys the platform and defines the standards. Facilities connect and are evaluated continuously. The accreditor sees national compliance in real time. Facilities see their own readiness. Both sides benefit from the same data flowing through the same rule engine.
Built for the Highest-Stakes Environments
Architectural Isolation
Clinical data and demographic data are stored in separate environments with independent access controls. A breach of one environment does not expose the other. Accreditor users see compliance scores and findings. They do not see patient records.
Per-Jurisdiction Data Residency
Each deployment runs in its own cloud environment within the jurisdiction's boundaries. US deployments run on US infrastructure under HIPAA controls. International deployments run on in-country infrastructure under local data protection law.
Deterministic Audit Trail
Every evaluation, every access, every modification is recorded in an append-only audit log. Entries are cryptographically hashed to prevent retroactive modification. The audit trail is the system of record for what was evaluated, when, and what the result was.
No Almighty Administrator
Technical staff who maintain the platform cannot view clinical data without explicit authorization from a clinical administrator. System access and clinical access are separate permission domains.
Schedule a Briefing
We work with accreditation organizations and health systems to evaluate whether continuous compliance infrastructure fits their standards framework and facility network. If you are responsible for accreditation programs, standards development, or compliance operations, we would welcome a conversation.
Schedule a BriefingRegain, Inc. — Delaware C-Corporation — regain.ai