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Case study · Healthcare Providers · Operations

Perioperative and infusion scheduling optimization — 19% OR utilization lift

An academic medical center struggled with OR gaps, infusion chair idle time and last-minute cancellations. pronix.ai built an agentic scheduling optimizer that released unused blocks, packed infusion chairs and proactively reached out to patients — lifting OR utilization 19% and cutting same-day cancellations by 27%.

Client
Academic medical center, 42 ORs and 180 infusion chairs
Industry
Healthcare Providers
Platform
Epic · Kore.ai Agent Platform · Azure AI Foundry
By pronix.ai CX Engineering8 min readQ2 2026
+19%
OR utilization
-27%
Same-day cancellations
-34%
Infusion chair idle time
+2.3M
Annual incremental capacity

*Representative outcome; results vary by client, scope and platform configuration.

The challenge

OR utilization hovered at 68%, infusion chairs sat empty during peak demand windows, and 14% of scheduled procedures canceled same-day. Schedulers worked in silos by department and couldn't see cross-resource constraints.

Our approach

Step 01

Agentic block-release assistant

The agent monitored surgeon block usage, predicted release candidates and prompted schedulers to release or swap blocks before they aged into waste.

Step 02

Infusion chair packing

An optimization model packed infusion appointments by chair, nurse and pharmacy availability — reducing idle chair time and patient wait.

Step 03

Proactive patient outreach

Voice and text reminders confirmed appointments, screened for barriers like transport or prep questions, and offered reschedule before the slot became a same-day cancellation.

Step 04

Human scheduler co-pilot

Schedulers reviewed agent recommendations in Epic and approved with one click — they stayed in control while the agent handled the combinatorial work.

We didn't hire more schedulers. We gave our existing team an assistant that sees the whole board.

VP Perioperative Services
For COOFor VP Perioperative ServicesFor CIOFor CMO

Illustrative case study. Scenarios, metrics, quotes and client details are representative composites based on Pronix engagements and industry benchmarks unless a named client is shown with written consent. Outcomes vary by client, scope, data quality and platform configuration. Nothing on this page is a guarantee, warranty or professional advice. See our Terms of Use for the full disclaimer.

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