Demonstration · Illustrative data · BI Consulting Services

American Vascular Associates × BI Consulting Services

Prepared for MeganSeptember 2026 · Multi-center OBL / ASC performance board

Every center, every referral, one view of the wait.

Fifteen physician-partnered vascular centers across nine states — volume, procedure mix, referral-to-procedure time, patient experience, revenue cycle and staffing, refreshed from the EMR and billing system into a single Power BI model.

The network as a vascular tree — 15 centers, 9 states

Each node is a center: sized by patient volume, coloured by median referral-to-procedure days. Branch width = group volume.

≤ 10 days11–14> 14 days
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Patient volume and referral-to-procedure time — 24 months

Bars: patients treated per month (selected period highlighted). Line: volume-weighted median days from referral to procedure.

In periodPriorDays to access
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Procedures by family

Encounters in period, share of total.

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Revenue cycle by center group

Charge lag (days from procedure to charge posted), first-pass denial rate, days in A/R — volume-weighted.

on targetwatchaction
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Procedure-room utilisation by center

Staffed room-hours used ÷ available. Target band 78–88%.

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Patient experience by center

Post-visit survey: % satisfied and Net Promoter Score on an 80–100 scale, ranked by NPS.

Satisfied %NPS
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Ask the data

Natural-language layer over the same model — answers cite the panel they came from.

Try alsoDenial rate by payer, Georgia, last quarterThrombectomy volume vs same month last yearWhich rooms are idle on Fridays?
Model: private, on-premise LLM over the Power BI semantic model · no PHI leaves the network · answer generated from the same filtered dataset shown above.
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Private AI on your own server

The "ask the data" ideas on this board are designed to run on a GPU server inside your own network — an open-weight model over your own documents, cited answers, no per-seat licence, nothing leaving the building. The short deck below explains how it works. Scroll through, or download it as a PDF.

Private AI Servers — slide 1 of 14
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