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iQueue for Operating Rooms Case Study – Ohio Health

OhioHealth is a family of not-for-profit hospitals and healthcare facilities in Central Ohio. The largest hospital in the system, Riverside Methodist Hospital in Columbus, is a 1,059-bed teaching institution that has served patients since 1892.

Problem

Following the height of the COVID-19 pandemic, OhioHealth’s Surgical Services Leadership Team prioritized a “back to basics” approach towards achieving operational efficiency within the number of operating rooms available. A significant challenge they faced was fully utilizing OR time and accurately allocating resources, given often inaccurate case length scheduling requests from 70% non-employed and 30% employed surgeons and clinic schedulers.

The surgical teams’ reliance on EHR case length suggestion capabilities or expected case length based on tribal knowledge failed to address inefficiencies related to performing procedures in the allotted OR schedule timeframe. These inaccurate predictions resulted in extended daily OR schedules past primetime hours, increased overtime, and dissatisfaction among employees and medical staff. Leadership recognized that scheduling cases accurately based on credible data, and timely reporting in order to improve resource allocation during primetime hours, was critical to supporting overall efficiency in the OR.

Solution

OhioHealth implemented iQueue for Operating Rooms’ Analyze module to identify opportunities for operational improvements based on credible and actionable data. The Analyze module provided a single source of truth for perioperative analytics and visibility into real-time daily operational metrics, with predictive and prescriptive perioperative analytics to show likely future developments and offer suggested actions in response.

The Case Length Finder tool within Analyze showed OR schedulers the recommended length of time for procedures based on the specific surgeon and procedure code during the scheduling process. The Case Length Finder tool has further provided the OhioHealth leadership team scheduling workflow consistency and a more predictable daily OR schedule, resulting in the ability to complete the same volume of cases in fewer physical rooms and reduce the number of occupied ORs past primetime hours. The ability to better predict length of procedures in specific rooms each day increased physician and staff satisfaction, reduced overtime, and overall improved resource allocation and utilization.

Results

0%
increase in case length accuracy for greater room utilization predictability and greater ease of staffing
Reduced daily number of rooms occupied after primetime hours from 13 to 8, yet sustained overall volume
%
Increased staff satisfaction and reduced costs associated with running additional rooms “after hours”
%
Improved alignment of specialty staff with scheduled complex cases
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