AI increases operating-room usage by 16%
Operating room (OR) utilisation at the University of Colorado Hospital has increased by 16% after the implementation of an airtifical-intelligence-driven system that uses smart scheduling based on predictive analytics. OR blocks are units of time allocated to specific surgeons for specific procedures and in May, UCHealth teamed up with LeanTaas to make block management more efficient. LeanTaaS iQueue mines OR case data and creates smart-block schedules with machine learning that assigns the correct amount of OR block time to the appropriate surgeon using secure mobile interactions.

UCHealth today announced its inpatient operating room (OR) utilization at University of Colorado Hospital has seen a 16 percent increase for the blocks exchanged through mobile block swaps, in just three months with the launch of smart block scheduling based on predictive analytics.

The goal is to manage OR blocks – chunks of time allocated to particular surgeons for particular procedures – as efficiently as possible. In May, UCHealth began partnering with LeanTaaS, a leading Silicon Valley health care predictive analytics company, to make its OR block management process fair, transparent and frictionless. Serving more than 40 U.S. providers, LeanTaaS iQueue mines OR case data and uses machine learning to create smart block schedules that assign the right amount of OR block time to the right surgeon at the right time using simple and secure mobile interactions.

“Creating and managing OR block schedules that achieve revenue and utilization targets while balancing surgeon needs is very cumbersome and error-prone,” said Ashley Walsh, perioperative business manager at UCHealth. “iQueue leverages EHR data, understands utilization patterns and recommends block schedule changes supported by hard facts. In just a few months, we have seen 16 percent higher utilization of blocks requested through mobile block exchange. We’re thrilled with the results and look forward to many more improvements.”

Sanjeev Agrawal, president and CMO at LeanTaaS, added, “We started out by asking, ‘How can we leverage data and mobile to make OR block scheduling easy, transparent and fact-based?’ The answer was to first mine OR case data and use machine learning to understand utilization patterns and then create lightweight mobile interactions that provide timely, actionable alerts and facilitate seamless block exchanges. We’re excited about the initial results at UCHealth and look forward to many more improvements in the future.”

16 Percent Higher Block Utilization for Blocks Requested through Mobile Block Swaps

There are 38 inpatient ORs at University of Colorado Hospital, one of UCHealth’s six hospitals in the state. Increasing the OR block utilization – the share of actual OR time used of the total time allocated – using iQueue is making a big difference:

Surgeons are receiving a weekly text message with their latest OR metrics that show how they are utilizing their time and contributing to OR volumes. Top features include the ability to request and release block time anytime, anywhere, directly from their phones.

OR managers are able to see a 360-degree view of OR metrics without spending days, if not weeks, pulling data from several sources. Top features include the ability to facilitate block changes fairly and transparently.

Surgeon schedulers are able to request and release block time for their surgeons securely and by conveniently using only one application instead of sending dozens of emails and making numerous phone calls.

About LeanTaaS iQueue for Operating Rooms

iQueue mines OR case data, understands utilization patterns and uses predictive analytics to allocate the right OR to the right surgeon at the right time. It combines machine learning, operational constraints, and staff and surgeon preferences to ensure the highest and best utility of block time, using a three-step approach:

1. Provides deep visibility into OR utilization patterns: Web and mobile dashboards show exactly how OR time is being utilized and uncovers actionable insights, such as who isn’t best utilizing their allocated time, how surgeons are contributing to their groups and service lines, and how to accommodate block requests fairly and transparently. These dashboards enable OR managers and surgeons to have objective conversations and meet their goals.

2. Enables secure and convenient mobile block exchanges: iQueue continuously looks for abandoned blocks that may have otherwise gone unnoticed and makes them available to the right surgeons. Surgeons (and their schedulers) can easily request block time from their phone whenever and wherever they need. Surgeons can also release block time they don’t need right from their phone.

3. Suggests block changes with predictive analytics: iQueue continuously mines case data, understands utilization patterns, forecasts case volume and mix, and suggests block changes to ensure the best utility of OR block time. It answers questions such as who isn’t best utilizing their time well on particular days, who to take time away from, who needs more time and when, and supports the findings with hard facts. OR managers can easily make block changes with consistent data in a way that meets everyone’s objectives.

About UCHealth

UCHealth is a Front Range health system that delivers the highest quality patient care with the highest quality patient experience. UCHealth combines Memorial Hospital, Poudre Valley Hospital, Medical Center of the Rockies, Colorado Health Medical Group, and University of Colorado Hospital into an organization dedicated to health and providing unmatched patient care in the Rocky Mountain West. Separately, these institutions can continue providing superior care to patients and service to the communities they serve. Together, they push the boundaries of medicine, attracting more research funding, hosting more clinical trials and improving health through innovation.

Tags: UCHealth, LeanTaaS, iQueue, operating rooms, OR utilization, OR block scheduling, healthcare, predictive analytics, predictive modeling, lean practices, machine learning, hospitals, data science, data analytics, big data, infusion centers

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