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Healthcare Application Catalogue

Enterprise AI applications for hospital and health system operations, powered by the Semantic Ontology Layer.

Data Plane Overview

The application catalogue draws from a unified data plane spanning clinical systems, revenue cycle platforms, and unstructured medical data sources:

graph TD
    subgraph Data Plane
        EHR["EHR / EMR<br/><i>Patient Records, Diagnoses, Medications, Orders</i>"]
        RCM["Revenue Cycle / Billing<br/><i>Claims, Coding, Denials, Payer Contracts</i>"]
        HIS["Hospital Information System<br/><i>Admissions, Scheduling, Beds, Supply Chain</i>"]
        IMAGING["Medical Imaging & Lab<br/><i>Radiology, Pathology, Lab Results, PACS</i>"]
        NOTES["Clinical Notes & Comms<br/><i>Physician Notes, Discharge Summaries, Referrals</i>"]
        POP["Population & External Data<br/><i>Public Health, SDoH, Payer Claims, Registries</i>"]
    end

    subgraph Semantic Ontology Layer
        ONT["Unified Healthcare Ontology<br/><i>Entity Resolution · Relationship Mapping · Business Rules</i>"]
    end

    subgraph Application Catalogue
        P360["Patient 360"]
        CDS["Clinical Decision Support"]
        REV["Revenue Cycle"]
        OPS["Operational Efficiency"]
        PHM["Population Health"]
        SUPPLY["Supply & Pharmacy"]
        QUALITY["Clinical Quality"]
        REG["Regulatory Compliance"]
    end

    EHR --> ONT
    RCM --> ONT
    HIS --> ONT
    IMAGING --> ONT
    NOTES --> ONT
    POP --> ONT

    ONT --> P360
    ONT --> CDS
    ONT --> REV
    ONT --> OPS
    ONT --> PHM
    ONT --> SUPPLY
    ONT --> QUALITY
    ONT --> REG

Data Plane Components

Structured Enterprise Systems

System Market-Leading Products Role
EHR / EMR Epic (EpicCare Inpatient/Ambulatory), Oracle Health (Cerner) Millennium, MEDITECH Expanse, Allscripts/Veradigm, athenahealth (ambulatory), NextGen Healthcare, eClinicalWorks Patient demographics, clinical data, diagnoses (ICD-10), medications, lab orders, vitals, clinical workflows, CPOE
Revenue Cycle / Billing Epic Resolute (Professional/Hospital Billing), Waystar, R1 RCM, Change Healthcare (Optum), Experian Health, Availity, nThrive/Finvi, athenahealth RCM Claims submission, medical coding (CPT/HCPCS/DRG), denial management, prior authorization, payer contracts, patient billing, collections
Hospital Information System SAP S/4HANA for Healthcare, Oracle Health (Millennium Operations), Infor CloudSuite Healthcare, Workday (HR/Finance), GHX (supply chain exchange), Vizient (GPO analytics) ADT (admissions/discharge/transfer), bed management, OR scheduling, materials management, supply chain, HR, financials

Semi-Structured & Unstructured Sources

Source Market-Leading Products Role
Medical Imaging & Lab GE Healthcare PACS (Centricity/Edison), Philips IntelliSpace PACS, Sectra PACS, Agfa HealthCare, Hologic; LIS: Epic Beaker, Cerner PathNet, Sunquest, Orchard Harvest Radiology images (DICOM), pathology reports, lab results (HL7/FHIR), diagnostic findings, imaging AI pre-reads
Clinical Notes & Communications Nuance DAX Copilot (ambient clinical intelligence), 3M M*Modal, Abridge, Suki AI, Microsoft DAX Copilot, DeepScribe; Secure messaging: TigerConnect, Vocera (Stryker) Physician dictation, ambient documentation, progress notes, discharge summaries, referral letters, care team messaging
Population & External Data Arcadia.io (population health data platform), Innovaccer, Azara DRVS, Milliman MedInsight, CMS public use files, CDC WONDER, LexisNexis SDOH, Area Deprivation Index (ADI), AHRQ SDoH databases Population demographics, social determinants of health, payer claims databases, epidemiological data, risk adjustment, benchmarking

Application Catalogue

P0 — Immediate ROI

Application Primary Data Sources ROI Signal Time to Value
Patient 360 & Care Coordination EHR, RCM, Imaging, Notes Reduce readmissions 15-25%, improve care gap closure 30% 4-6 weeks
Clinical Decision Support EHR, Imaging, Notes Reduce adverse drug events 20-30%, improve protocol adherence 25% 4-6 weeks

P1 — High Value

Application Primary Data Sources ROI Signal Time to Value
Revenue Cycle Optimization RCM, EHR, Notes Reduce denial rate 25-40%, accelerate collections 15-20 days 6-8 weeks
Operational Efficiency & Capacity HIS, EHR, RCM Improve bed utilization 10-15%, reduce OR idle time 20% 6-8 weeks

P2 — Strategic Value

Application Primary Data Sources ROI Signal Time to Value
Population Health Management EHR, Population Data, RCM Reduce high-risk ER visits 20-30%, improve preventive care 25% 8-10 weeks
Supply Chain & Pharmacy Intelligence HIS, EHR, Imaging Reduce supply waste 15-25%, optimize formulary spend 8-12% 8-10 weeks

P3 — Operational Excellence

Application Primary Data Sources ROI Signal Time to Value
Clinical Quality & Safety EHR, Notes, HIS Reduce HAIs 20-30%, improve quality measure scores 15% 10-12 weeks
Regulatory & Compliance Automation All Systems, Notes 70% reporting effort reduction, maintain accreditation readiness 10-12 weeks

Ontology Entity Map

Key business entities resolved across systems by the Semantic Ontology Layer:

Business Entity EHR / EMR Revenue Cycle Hospital Information System
Patient MRN / Patient Record Guarantor / Account ADT Record
Encounter Visit / Episode Claim / Charge Admission / Discharge
Provider Ordering / Attending Physician Billing Provider / NPI Staff / Schedule
Diagnosis Problem List (ICD-10) Claim Diagnosis —
Procedure Order / Result CPT / HCPCS Code OR Schedule / Case
Medication MAR / Prescription NDC / Drug Charge Pharmacy Inventory

Architecture Pattern

Every application in this catalogue follows a consistent execution pattern:

flowchart LR
    A["Ontology Layer<br/><i>Resolved Entities</i>"] --> B["AI Workflow Engine<br/><i>LLM + Clinical Rules</i>"]
    B --> C["Dashboard & Alerts<br/><i>Real-time Visualization</i>"]
    B --> D["Action Layer<br/><i>Recommendations · Orders · Escalations</i>"]
  1. Data Ingestion — Ontology layer resolves entities across EHR, Revenue Cycle, HIS, and unstructured clinical data (patient matching, encounter linking, terminology normalization)
  2. AI Workflow Execution — LLM-powered pipelines apply clinical logic, predictive models, coding intelligence, and operational optimization
  3. Presentation — Dashboards surface clinical KPIs, financial metrics, and operational status; alerts trigger on clinical deterioration, denial patterns, and capacity constraints
  4. Action — Recommendations surface in clinician workflows (EHR alerts), revenue cycle queues (denial follow-up), and operational dashboards (bed management, OR scheduling)

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