EHR-Embedded Clinical Intelligence
Physicians AI Insights turns fragmented chart review into an instant pre-visit brief. Open a chart and immediately see what changed, what's overdue, what's trending, and who needs intervention now.
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 platform layers pre-visit context, active care gaps, longitudinal risk signals, and note retrieval directly into the physician workflow — no second application, no report queue.
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
Closing care gaps directly improves MIPS and HEDIS quality scores — which drive Medicare reimbursement rates and payer contract performance. Better scores = higher reimbursement.
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
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.
HIPAA-Compliant by Architecture
No patient data ever leaves the platform. Every layer is built for compliance from day one.
Patient identity stored in a separate restricted database. Analytics use anonymous surrogate keys only.
6 masking policies — SSN, DOB, name, phone, email, address — enforced at the query engine level.
5 custom RBAC roles. Physicians see only their assigned patient panel. No unauthorized access.
All LLM inference runs within the Snowflake governance perimeter. No PHI sent to external APIs.
60-day rolling query log for HIPAA compliance. Every PHI access is tracked and auditable.
Clinical notes are scrubbed of identifiers before indexing for AI search.
Implementation
From contract to production clinical intelligence in approximately 60 days.
Weeks 1–2
Weeks 3–4
Weeks 5–6
Weeks 7–8
Ready to Transform Your Practice?
Contact us for a demo and learn how Physicians AI Insights can reduce chart prep, close care gaps, and give your physicians back their time.