Does Parallel Workflow Impact Anesthesia Quality?

Abstract

Redesigns of workflow to allow parallel processing of OR tasks in the Operating Room of the Future at Massachusetts General Hospital have reduced non-operative time, increasing OR throughput. Automatically gathered anesthesia times were studied to address concerns that the new process constricted anesthesia work time. Upon close examination, it was found that ‘Induction Time’ was the only time interval not impacted by extraneous influences that invalidated other metrics based on the automatic data. ‘Induction Time’ increased in the Operating Room of the Future as compared to Standard Operating Rooms.

Introduction

We evaluated whether improved patient throughput attributed to parallel processing workflow in our Operating Room of the Future (ORF) project has reduced the time available for anesthesia work. If anesthesia work time were reduced, quality could be negatively affected.

Methods

With IRB approval, we used a retrospective matched design, controlling for surgeon and case type, with 219 case pairs in each environment (Standard Operating Room (SOR) and ORF). We obtained the data for this study by integrating two databases containing automatically recorded perioperative data.

Results and Conclusion

Anesthesia times for the ORF and SORs are illustrated in Fig. 1. Close examination of the actual work process revealed that computerized ‘Total Preop Anes Time’ for the ORF and SORs was impacted by extraneous influences, invalidating these data. Specifically, anesthesia teams may not report ‘overlaps’ in the care of patients treated sequentially in a single OR, even if individual team members from an anesthesia team are involved in the care of individual sequential patients scheduled for the same OR. Such a situation occurs when one anesthesia team member is preparing a patient for surgery in the Induction Room while another team member cares for a patient in the OR. In this situation, anesthesia work time spent with the preoperative patient is not registered, and the ‘registered’ times are artificial. Thus, our result contains a cautionary tale: the context (i.e., real working conditions) within which automatic data are gathered, and the detailed meaning of each milestone becomes almost as important as the data itself in designing and interpreting studies that depend on automatically collected data.

Figure 1.

Anesthesia times for the ORF and SORs.

Our detailed work process review indicated that ‘Induction Times’ were valid data. The ORF parallel workflow allowed ‘Induction Time’ to increase vs. SOR (p<0.0001). Thus, parallel workflow reduces total process time, yet preserves quality by protecting key processes from time pressure.