Workflow Prototype · Illustrative Data
This prototype illustrates pre-visit briefs, note search, and follow-up views using sample data. It is not a verified production EHR integration; clinical use would require deployment-specific integration, validation, and review.
Since Last Visit
A1C rose from 6.9 to 7.4 in 3 months. Jardiance 10 mg added. No follow-up scheduled.
Active Care Gaps
Diabetic eye exam overdue 14 months. Annual foot exam missing. Flu shot not documented.
Lab Trends
Medications
6 active Rx. No interactions flagged. Metformin + Jardiance combo noted.
The Chart Prep Problem
Critical trends hide across dozens of encounters, care gaps slip through manual workflows, and clinical notes go unsearched. Your EHR has the answers — it just can't tell you.
Manual review burns time before the visit even starts.
Preventive, lab, and follow-up opportunities fall between clicks.
More searching, less synthesis, too little time with the patient.
What It Does
The demonstration brings pre-visit context, care-gap examples, risk views, and note retrieval into one sample workflow.
AI-generated patient summary appears when you open a chart — changes since last visit, trending labs, medication context, and risk evidence.
Ask clinical questions in plain English. The semantic layer translates them into precise, standards-aware data retrieval.
Automated alerts for overdue screenings, missing labs, vaccine opportunities, and follow-up failures while there's still time to act.
Patients sorted by urgency and disease direction so you know who needs the longer visit and who is quietly deteriorating.
Panel-level quality metrics, provider benchmarks, payer mix, and open care gaps — without waiting on manual reporting cycles.
Semantic search across notes, discharge summaries, reports, and imaging impressions — with citations, not vague keyword hits.
Pre-Visit Intelligence
When a physician opens the chart, the AI brief is already waiting — synthesizing what changed, what's overdue, and what needs attention so the visit starts with clarity, not chart-diving.
Since Last Visit
A1C rose from 6.9 to 7.4 in 3 months. Jardiance 10 mg added. No follow-up scheduled.
Active Care Gaps
Diabetic eye exam overdue 14 months. Annual foot exam missing. Flu shot not documented.
Lab Trends
Medications
6 active Rx. No interactions flagged. Metformin + Jardiance combo noted.
Ask Your Data Anything
The system translates physician questions into database queries using LOINC, ICD-10, RxNorm, CPT, and CVX mappings. No codes to memorize — just ask the way you think.
Selected Query
Identifies the diabetic cohort, applies the most recent A1C observation, and returns patients who need glycemic follow-up first.
ICD-10 E11% + LOINC 4548-4 > 7.0 Care Gap Detection
The system continuously evaluates screening schedules, lab monitoring windows, immunization timelines, and referral follow-ups — flagging gaps while there's still time to act.
Screening
Lab
Immunization
Follow-up
Care-gap views can support quality-measure review. Definitions, reporting requirements, and any reimbursement implications need to be assessed for the specific program and practice.
Risk Stratification
Helps physicians know who needs a longer visit and catch decompensation before it becomes an emergency.
Acute deterioration, emergency indicators
Multiple uncontrolled conditions, significant gaps
1–2 uncontrolled conditions or minor gaps
Controlled, current on screenings
Beyond static risk scores — track how each patient's conditions evolve over time.
A1C trending down, BP at goal
Conditions controlled, on maintenance
Key metrics worsening, needs intervention
Nothing Gets Missed
Cross-references care plans and referrals against subsequent encounters to find patients falling through the cracks.
Population Health Dashboard · Illustrative Data
Quality measures, provider comparisons, payer visibility, and cohort slicing — from static reports to daily operating intelligence.
Compare panel performance across your practice — identify coaching opportunities and best practices.
Visit volume and revenue trends by insurance type from encounter data.
Slice by condition, medication, risk tier, provider, date range — any combination.
Clinical Note Search
Semantic search across notes, reports, imaging conclusions, and discharge summaries — with citations instead of vague keyword hits.
Clinical notes are split into passages and PII is automatically scrubbed.
Passages are embedded using hybrid vector + keyword search.
Physicians ask a natural language question about any patient or topic.
Relevant passages returned with visit dates, authors, and citations.
Security Design Considerations
Data flows, permissions, retention, and applicable obligations must be reviewed for the specific deployment before patient data is used.
Review whether patient identifiers should be held separately from analytics data, with access limited by role and purpose.
Define and test masking rules for sensitive fields such as names, dates of birth, contact details, and identifiers.
Define roles and permitted patient or cohort access, then test those boundaries against the deployment requirements.
Review model-processing locations and data transfers. Confirm permitted services and contractual requirements before configuring inference.
Agree on audit-log coverage, retention, and review procedures, and test that relevant access events are captured.
Evaluate identifier removal before indexing and test for residual sensitive information.
Implementation
An illustrative eight-week plan. Actual scope and timing depend on data readiness, integrations, validation, and required reviews.
Weeks 1–2
Weeks 3–4
Weeks 5–6
Weeks 7–8
Ready to Transform Your Practice?
Discuss the prototype, your clinical workflow requirements, and the evidence needed before any production implementation.
Or email us directly at jrapisarda@bioinfosolutions.com