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The Platform
Health IT Solutions builds and operates an event-based health data platform for organizations working in
community and public health settings, including provider organizations, regional collaboratives, and public partners.
The platform is designed to produce operational signals while maintaining consent enforcement,
auditability, and research-grade traceability.
The core design principle is simple: a person’s journey is not a set of disconnected records, it is a sequence of events across systems,
settings, and partners. The platform models those events consistently, orders them in time, and generates governed outputs that support
outreach, prevention, care coordination, evaluation, and accountability.
Event Model and Timeline
The platform is built on a unified event model that treats every interaction as a time-stamped signal in a person’s journey.
- Event model that represents clinical encounters, outreach activity, transitions, follow-up attempts, service delivery, assessments, and outcomes using consistent semantics
- Time-ordered timeline across sources to understand sequences, gaps, and trajectories rather than isolated point-in-time snapshots
- Cross-setting continuity to track individuals as they move between residential, outpatient, ED/hospital, community-based services, and partner environments
- Trajectory analysis support for engagement, retention, relapse risk signals, missed connections, and outcome evolution over time
The platform is designed to preserve the operational meaning of events, including who initiated an action, when it occurred, what it referenced, and what downstream action it triggered.
Canonical Event Log
Event ingestion normalizes heterogeneous source data into a canonical event log that supports both operations and evaluation.
- Canonical event schema that standardizes identifiers, timestamps, source metadata, event type, context, and linkages
- Source provenance captured end-to-end, including original source system, extract method, and transformation lineage
- Deterministic reconstruction of timelines from the canonical log to support repeatable evaluation and audit requests
- Derived views for operational dashboards and analytical extracts, each traceable back to canonical events
Reviewers can trace any operational signal, measure, or denominator back to the underlying canonical events and ultimately to the original source data.
Append-Only and Versioned Logic
The platform is designed to maintain historical truth even as definitions, partners, and systems evolve.
- Append-only event storage to preserve historical state and support defensible timelines
- Versioned transformations so that changes in parsing, mapping, cohort rules, or identity logic do not break reproducibility
- Explicit corrections handled as new events or versioned derivations rather than destructive updates
- Change tolerance for source-system updates, shifting program definitions, enrollment churn, and new partner participation
This supports retrospective review, re-runs of analysis, and governance requests without ambiguity about what was known and when it was known.
Operational Signals and Feedback Loops
The platform produces operationally meaningful signals that support action, not just reporting.
- Alerts generated from event patterns, thresholds, and time-bound rules (for example, new ED events for attributed cohorts)
- Flags representing risk or attention states derived from sequences (for example, repeated utilization, missed follow-up windows, disengagement patterns)
- Missed connections detection when expected operational actions do not occur within defined time windows
- Engagement breakdowns surfaced as timeline gaps, incomplete handoffs, or repeated failed contacts
Signals are produced with supporting context and provenance so staff can act, and so external reviewers can verify the basis of the signal.
Partner Participation Model
The platform is designed for multi-organization environments without requiring centralized ownership of identified data.
- Federated participation where each organization can retain control of its data and operate within its own governance constraints
- No shared infrastructure requirement for partners to participate, integration can be incremental and source-specific
- No data ownership transfer, partners do not need to surrender custody of identified data to contribute operational signals or governed extracts
- Shared logic, not shared databases, consistent definitions for cohorts, measures, and signals can be deployed across environments without forcing a single repository model
This reduces institutional risk while enabling shared accountability, consistent measurement, and cross-partner operational coordination.
Responsibility and Attribution Tracking
Accountability depends on knowing who owned the next action at each point in time, and whether that action occurred.
- Assignment events that record responsibility for outreach, follow-up, navigation, and coordination tasks over time
- Handoffs captured as explicit events, including transitions between teams, programs, settings, and organizations
- Time-bounded accountability so that responsibility changes do not erase prior ownership or obscure gaps
- Attribution and enrollment logic treated as governed assets that can be reviewed, versioned, and reproduced for evaluation and funding review
This supports defensible answers to: what happened, who was responsible, what was done, what was missed, and what changed afterward.
Identity and Consent as First-Class Platform Services
Cross-system timelines require identity resolution, and governance-ready timelines require time-bound consent enforcement.
- EMPI mechanics supporting deterministic and probabilistic matching across heterogeneous identifiers, without reliance on a single authoritative source
- Identity state over time, supporting merges, splits, corrected identifiers, and partner-specific identifiers while preserving historical traceability
- Consent as an event, modeled as time-bound states that can be granted, changed, and revoked with preserved history
- Enforcement at event and cohort level, applying consent constraints in ingestion, transformation, and access to operational lists and analytical datasets
Consent enforcement is not a policy statement, it is implemented as platform logic that controls what can be seen, by whom, for which cohorts, at which times.
Platform Services Layer
Capabilities are delivered as reusable platform services, operated continuously and maintained as systems and policies evolve.
- Ingestion pipelines for scheduled and event-driven data capture, normalization, validation, and provenance capture
- Identity services to resolve cross-system identities, maintain EMPI state, and support cohort construction
- Consent enforcement applied centrally and consistently across operational outputs, reports, and research extracts
- Extraction services that generate governed operational views, analytical extracts, and audit-ready deliverables
- Exportability guarantees, ensuring outputs can be produced in standard formats with documented definitions, lineage, and reproducible logic
Platform components are monitored, versioned, and updated as source systems change, partners evolve, and measurement requirements shift.