Data-driven simulation use to determine bed resource requirements for the redesign of pre- and post-operative care areas

Abstract

Perioperative services have a high impact on a hospital's financial success. In order to increase patients' privacy and satisfaction, while restraining cost, a redesign of the existing Post-Anesthesia Care Unit (PACU) was suggested at the Mayo Clinic. A simulation model was created to determine the number of beds required in the redesign of the PACU to maintain Operating Room (OR) blocking below 5 %. Since OR time and resources are more costly than the PACU, limiting the resource scarcity of the PACU should minimize delays through the surgical suites. By assuming PACU resourcing as secondary to managing the OR, the underlying complexity of the surgical scheduling did not have to be analyzed. Real data was fed into the simulation model that successfully captured the complexity of the system without the work-intensive requirements of theoretical modeling. The results of the analysis were incorporated into the design plans for remodeling the PACU.