Decisiones de final de vida en tiempos de pandemia / End-of-life decisions during the COVID 19 pandemic

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Solving the negative impact of congestion in the postanesthesia care unit: a cost of opportunity analysis.

BACKGROUND: Congestion in the postanesthesia care unit (PACU) leads to the formation of waiting queues for patients being transferred after surgery, negatively affecting hospital resources. As patients recover in the operating room, incoming surgeries are delayed. The purpose of this study was to establish the impact of this phenomenon in multiple settings. METHODS: An operational mathematical study based on the queuing theory was performed. Average queue length, average queue waiting time, and daily queue waiting time were evaluated. Calculations were based on the mean patient daily flow, PACU length of stay, occupation, and current number of beds. Data was prospectively collected during a period of 2 months, and the entry and exit time was recorded for each patient taken to the PACU. Data was imputed in a computational model made with MS Excel. To account for data uncertainty, deterministic and probabilistic sensitivity analyses for all dependent variables were performed. RESULTS: With a mean patient daily flow of 40.3 and an average PACU length of stay of 4 hours, average total lost surgical opportunity time was estimated at 2.36 hours (95% CI: 0.36-4.74 hours). Cost of opportunity was calculated at $1592 per lost hour. Sensitivity analysis showed that an increase of two beds is required to solve the queue formation. CONCLUSIONS: When congestion has a negative impact on cost of opportunity in the surgical setting, queuing analysis grants definitive actions to solve the problem, improving quality of service and resource utilization.