Patient 360 & Care Coordination¶

Unified patient profiles with care gap identification, readmission risk prediction, and care team coordination.

Priority: P0 — Immediate ROI
Time to Value: 4-6 weeks
Category: Clinical & Care Management

Business Problem¶

Patient data is fragmented across EHR (clinical), revenue cycle (financial), imaging systems (diagnostics), and clinical notes (unstructured). Clinicians and care coordinators lack a complete picture:

Fragmented records — a patient's history spans multiple EHR instances (primary care, specialists, hospitals), each with partial information
Care gaps invisible — overdue screenings, immunizations, and chronic disease management milestones are buried in individual records, not surfaced proactively
Readmission surprises — patients discharged without adequate follow-up return to the ED within 30 days; readmission penalties cost hospitals millions annually
Care coordination breakdown — transitions between primary care, specialists, and post-acute settings lose information, leading to duplicated tests and contradictory treatments
Social determinant blindness — food insecurity, transportation barriers, and housing instability significantly impact health outcomes but are rarely captured or acted upon

Capabilities¶

Unified Patient Profile¶

Single longitudinal view combining EHR clinical data (diagnoses, medications, labs, vitals), revenue cycle (coverage, claims, financial clearance), imaging (results, pending studies), and NLP-extracted data from clinical notes.

Care Gap Identification¶

Automated detection of overdue preventive care (mammograms, colonoscopies, HbA1c tests, immunizations) and chronic disease management gaps based on evidence-based clinical guidelines.

Readmission Risk Prediction¶

ML model predicting 30-day readmission probability at discharge based on clinical acuity, comorbidities, prior utilization, medication complexity, social determinants, and post-discharge care plan adequacy.

Care Team Coordination Hub¶

Unified view of all providers involved in a patient's care (PCP, specialists, care coordinators, social workers) with shared task lists, transition alerts, and care plan tracking.

Incorporate SDoH screening data (Z-codes), community resource availability, and area-level deprivation indices into the patient profile to identify non-clinical barriers to health.

Data Sources & Ontology Mapping¶

flowchart LR
    subgraph Data Plane
        EHR["EHR / EMR"]
        RCM["Revenue Cycle"]
        IMAGING["Imaging & Lab"]
        NOTES["Clinical Notes"]
        POP["Population Data"]
    end

    subgraph Ontology Entities
        PATIENT["Patient / MRN"]
        CLINICAL["Clinical History"]
        ENCOUNTERS["Encounter Timeline"]
        COVERAGE["Insurance & Coverage"]
        SDOH["Social Determinants"]
    end

    subgraph AI Workflow
        MATCH["Patient Matching"]
        PROFILE["Profile Builder"]
        GAPS["Care Gap Detector"]
        READMIT["Readmission Predictor"]
    end

    EHR --> PATIENT
    EHR --> CLINICAL
    RCM --> COVERAGE
    RCM --> ENCOUNTERS
    IMAGING --> CLINICAL
    NOTES --> CLINICAL
    POP --> SDOH

    PATIENT --> MATCH
    CLINICAL --> PROFILE
    ENCOUNTERS --> PROFILE
    COVERAGE --> PROFILE
    SDOH --> PROFILE
    MATCH --> PROFILE

    PROFILE --> GAPS
    PROFILE --> READMIT

Ontology Entity	Source System	Key Fields
Patient / MRN	EHR + RCM	MRN, Name, DOB, Gender, Address, Insurance, PCP, Consent Status
Clinical History	EHR + Imaging + Notes	Diagnoses (ICD-10), Medications, Allergies, Lab Results, Vitals, Procedures, Imaging Results
Encounter Timeline	EHR + RCM	Encounter Date, Type (inpatient/outpatient/ED), Facility, Provider, Disposition, LOS
Insurance & Coverage	Revenue Cycle	Payer, Plan, Coverage Dates, Copay, Deductible, Prior Auth Requirements
Social Determinants	EHR (Z-codes) + Population Data	Housing Status, Food Security, Transportation, Employment, Area Deprivation Index

AI Workflow¶

Patient Matching — Probabilistic matching across EHR instances and external data sources using MRN, name, DOB, SSN (last 4), address, and phone to build a Master Patient Index
Profile Assembly — Aggregate clinical history (problems, medications, allergies, labs), encounter timeline, coverage details, SDoH factors, and NLP-extracted findings from clinical notes
Care Gap Detection — Apply evidence-based guidelines (HEDIS, USPSTF, ADA, AHA) against patient's clinical record to identify overdue screenings, labs, immunizations, and chronic disease milestones
Readmission Risk Scoring — Gradient-boosted model trained on historical readmissions; features include LACE+ score components, medication count, SDoH flags, discharge disposition, and follow-up appointment status
Transition of Care Alerts — For patients transitioning between care settings (hospital → SNF → home), generate alerts for the receiving provider with critical information: medication reconciliation, pending results, follow-up needs
SDoH Action Matching — For patients with identified social barriers, match to available community resources (food banks, transportation services, housing programs) based on location and eligibility
Output — Patient 360 dashboard in EHR for clinicians; care gap worklists for care coordinators; readmission risk alerts at discharge; transition-of-care notifications for receiving providers

Dashboard & Alerts¶

Key Metrics¶

KPI	Description	Target
30-Day Readmission Rate	% of discharged patients readmitted within 30 days	< 10% (CMS target)
Care Gap Closure Rate	% of identified care gaps addressed within 90 days	> 75%
Patient Matching Accuracy	% of patient records correctly linked across systems	> 98%
Transition of Care Completion	% of transitions with medication reconciliation + follow-up scheduled	> 90%
SDoH Screening Rate	% of patients with completed SDoH assessment	> 60%
Care Coordinator Caseload Efficiency	Patients managed per coordinator with care gap closure rate maintained	20% improvement

Alert Rules¶

Alert	Trigger	Severity	Action
High readmission risk	Patient at discharge with readmission probability > 0.35	Critical	Trigger enhanced discharge planning; schedule 48-hour follow-up call; assign care coordinator
Critical care gap	High-risk patient overdue for HbA1c >6 months (diabetic) or mammogram >18 months	High	Push to care gap worklist; generate patient outreach (portal message, phone call)
Transition of care	Patient transferred to SNF/home health without medication reconciliation completed	High	Alert receiving provider; flag incomplete transition
SDoH barrier identified	Patient screens positive for food insecurity or transportation barrier	Medium	Route to social worker; match to community resources
Duplicate patient detected	Two records with >90% match probability found across systems	Medium	Queue for manual review; prevent duplicate orders/billing

ROI Model¶

Metric	Before	After	Impact
30-day readmission rate	14.5%	10.2%	30% reduction → $4.2M avoided CMS penalties + costs
Care gap closure	48% of gaps addressed	72% of gaps addressed	50% improvement → better outcomes + quality bonuses
Duplicate patient rate	8% of records	2% of records	75% reduction → fewer medical errors
Care coordinator productivity	85 patients per coordinator	110 patients per coordinator	29% improvement → $1.2M labor savings
Preventable ED visits	3,200 / year	2,100 / year	34% reduction → $3.3M cost avoidance

Estimated Annual ROI

$8M - $15M annually from readmission reduction, care gap closure, ED avoidance, and coordinator productivity — across a mid-size health system with 25,000+ annual discharges.

Implementation Notes¶

Patient matching across EHR instances requires a robust EMPI (Enterprise Master Patient Index); expect 90-95% auto-match rates with manual review for ambiguous cases
Care gap detection requires mapping clinical guidelines to computable rules against EHR-structured data (diagnoses, procedures, labs)
Readmission model needs minimum 24 months of discharge-to-readmission data with clinical features at time of discharge
SDoH integration depends on screening tool adoption (PRAPARE, AHC-HRSN); area-level data (ADI, SVI) can supplement individual screening
HIPAA compliance must be maintained throughout; all data access must follow minimum necessary standard and role-based access controls

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