Oregon Health & Science University reduces abandoned OR blocks by 51% with LeanTaaS iQueue
Oregon Health & Science University deployed Machine Learning & Predictive Analytics for Surgical & Perioperative Care in Hospital & Health System. As reported by leantaas.com: 51% reduction in abandoned blocks.
Source-reported figures (cited source: leantaas.com)
What Oregon Health & Science University was trying to fix
OHSU faced a shortage of available block time to allocate to new surgeons at its South Operating Rooms and Doernbecher Children's Hospital. Surgical services lacked visibility of available blocks, with all block owners operating independently and no accountability for inefficient use. There was no single source of truth, unclear metrics, and no standardized release times for blocks, which created a lack of surgeon trust in the performance metrics by which they were being evaluated.
What Oregon Health & Science University deployed
OHSU deployed iQueue for Operating Rooms at both SOR and DCH to improve OR access, increase surgeon accountability for allocated time, and add transparency through objective performance metrics. The implementation introduced a new framework for measuring OR utilization focused on collectable time — segments where a case could have been scheduled but wasn't — and on scheduled downtime. iQueue data now supplements existing infrastructure, helping perioperative leaders proactively close ORs during high census, and OHSU collaborated with LeanTaaS to develop an Availability Alerts management portal to notify surgeons when needed OR time becomes available.
Results
Since implementing iQueue, OHSU ORs experienced a steady decrease in collectable time as surgeons proactively release time they cannot use. The system delivered 25 additional cases per month in prime time, a 5% increase in staffed room utilization, a 5x increase in block utilization, and a 51% reduction in abandoned blocks.
Key Takeaways
- Transparent, objective performance metrics are critical to building surgeon trust and driving behavioral change around block release.
- Focusing measurement on 'collectable time' rather than traditional utilization metrics creates more actionable insights for OR leaders.
- Collaborative vendor partnerships that allow health systems to co-develop features (e.g., Availability Alerts) accelerate adoption and outcomes.
Evidence for Oregon Health & Science University's Surgical & Perioperative Care deployment
- Reported outcome metrics
- 3 cited below
- Cited source
- leantaas.com
- Last updated
- Source link checked
Vendor
Details
- Industry
- Hospital & Health System
- Use Case
- Surgical & Perioperative Care
- AI Technology
- Machine Learning & Predictive Analytics
- Company Size
- Enterprise
Have a similar implementation?
Share your customer's AI results and link it to your vendor profile.
Submit a case study →