Marie T. Egan

Deliberate Perioperative Systems Design Improves Operating Room Throughput

Background:New operating room (OR) design focuses more on the surgical environment than on the process of care. The authors sought to improve OR throughput and reduce time per case by goal-directed design of a demonstration OR and the perioperative processes occurring within and around it. Methods:The authors constructed a three-room suite including an OR, an induction room, and an early recovery area. Traditionally sequential activities were run in parallel, and nonsurgical activities were moved from the OR to the supporting spaces. The new workflow was supported by additional anesthesia and nursing personnel. The authors used a retrospective, case- and surgeon-matched design to compare the throughput, cost, and revenue performance of the new OR to traditional ORs. Results:For surgeons performing the same case mix in both environments, the new OR processed more cases per day than traditional ORs and used less time per case. Throughput improvement came from superior nonoperative performance. Nonoperative Time was reduced from 67 min (95% confidence interval, 64–70 min) to 38 min (95% confidence interval, 35–40 min) in the new OR. All components of Nonoperative Time were meaningfully reduced. Operative Time decreased by approximately 5%. Hospital and anesthesia costs per case increased, but the increased throughput offset costs and the global net margin was unchanged. Conclusions:Deliberate OR and perioperative process redesign improved throughput. Performance improvement derived from relocating and reorganizing nonoperative activities. Better OR throughput entailed additional costs but allowed additional patients to be accommodated in the OR while generating revenue that balanced these additional costs.

Automatic Detection and Notification of “Wrong Patient—Wrong Location” Errors in the Operating Room:

When procedures and processes to assure patient location based on human performance do not work as expected, patients are brought incrementally closer to a possible “wrong patient—wrong procedure” error. We developed a system for automated patient location monitoring and management. Realtime data from an active infrared/radio frequency identification tracking system provides patient location data that are robust and can be compared with an “expected process” model to automatically flag wrong-location events as soon as they occur. The system also generates messages that are automatically sent to process managers via the hospital paging system, thus creating an active alerting function to annunciate errors. We deployed the system to detect and annunciate “patientin-wrong-OR” events. The system detected all “ wrongoperating room (OR)” events, and all “wrong-OR” locations were correctly assigned within 0.50 ± 0.28 minutes (mean ± SD). This corresponded to the measured latency of the tracking system. All wrong-OR events were correctly annunciated via the paging function. This experiment demonstrates that current technology can automatically collect sufficient data to remotely monitor patient flow through a hospital, provide decision support based on predefined rules, and automatically notify stakeholders of errors.

A computerized perioperative data integration and display system

AbstractObject The operating room is rich in digital data that must be rapidly gathered and integrated by caregivers, potentially distracting them from direct patient care. We hypothesized that current desktop computers could integrate enough electronically accessible perioperative data to present a unified, contextually appropriate snapshot of the patient to the operating room team without requiring any user intervention. Materials and methods We implemented a system that integrates data from surgical and anesthesia devices and information systems, as well as an active radiofrequency identification location tracking system, to create a comprehensive, unified, time-synchronized database of all digital data produced by these systems. Next, a human factors engineering approach was used to identify selected data to show on a large format display during surgery. Results A prototype system has been in daily use in a clinical operating room since August 2005. The system functions automatically without any user input, as the display system self-configures based on cues from the primary data. The system is vendor agnostic with respect to input data sources and display options. Conclusion Automatic integration and display of team-synchronizing data from medical devices and hospital information systems is now possible using software that runs on a personal computer.