Abstract
Elective surgeries are primarily scheduled according to surgeon availability with less consideration of patients' postoperative cardiac intensive care unit (CICU) length of stay. Furthermore, the CICU census can exhibit a high rate of variation in which the CICU is operating at over-capacity, resulting in admission delays and cancellations; or under-capacity, resulting in underutilized labor and overhead expenditures. To identify strategies to reduce variation in CICU occupancy levels and avoid late patient surgery cancellation. Monte Carlo simulation study of the daily and weekly CICU census at Boston Children's Hospital Heart Center. Data on all surgical admissions to and discharges from the CICU at Boston Children's Hospital between September 1, 2009 and November 2019 were included to obtain the distribution of length of stay for the simulation study. The available data allows us to model realistic length of stay samples that include short and extended lengths of stay. Annual number of patient surgical cancellations and change in average daily census. We demonstrate that the models of strategic scheduling would result in up to 57% reduction in patient surgical cancellations, increase the historically low Monday census and decrease the historically higher late-mid-week (Wednesday and Thursday) censuses in our center. Use of strategic scheduling may improve surgical capacity and reduce the number of annual cancellations. The reduction of peaks and valleys in the weekly census corresponds to a reduction of underutilization and overutilization of the system.
Highlights
Post-operative recovery following congenital heart disease (CHD) surgery requires specialized care in a cardiac intensive care unit (CICU)
Both show that CICU length of stay (LOS) is positively skewed; a majority of patients stay in the CICU for a few days while a small percentage of patients have extremely long LOS, with 0.45% exceeding 100 days
We found that an anticipatory scheduling model may reduce the number of cancellations by 13–14% and result in fewer high occupancy days, but with slightly higher variation in daily CICU census than the currently used model based on patient and surgeon preferences
Summary
Post-operative recovery following congenital heart disease (CHD) surgery requires specialized care in a cardiac intensive care unit (CICU). Quality of care is generally measured by low mortality, and metrics for waste include admission delays, surgical cancellations, extended length of stay (LOS), and the need for increased care due to complications. CICUs often operate at or near capacity, which result in cancellations of scheduled elective surgeries and delays when providing urgent non-surgical critical care [2]. Scheduling elective surgeries with consideration of expected CICU LOS can potentially maximize CICU capacity while minimizing waste. The CICU census (i.e., actual bed occupancy) can exhibit a high rate of variation in which a CICU may operate over capacity, resulting in admission delays and cancellations, or significantly under-capacity, resulting in wasted labor and overhead expenditures. We simulated the weekly CICU census at our institution with Monte Carlo methods to demonstrate occupancy patterns and describe scheduling strategies to reduce variation in CICU capacity
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