Predictive analytics for cardio-thoracic surgery duration as a stepstone towards data-driven capacity management.

ABSTRACT: Effective capacity management of operation rooms is key to avoid surgery cancellations and prevent long waiting lists that negatively affect clinical and financial outcomes as well as patient and staff satisfaction. This requires optimal surgery scheduling, leveraging essential parameters like surgery duration, post-operative bed type and hospital length-of-stay. Common clinical practice is to use the surgeon's average procedure time of the last N patients as a planned surgery duration for the next patient. A discrepancy between the actual and planned surgery duration may lead to suboptimal surgery schedule. We used deidentified data from 2294 cardio-thoracic surgeries to first calculate the discrepancy of the current model and second to develop new predictive models based on linear regres

SUBMITTER: Nikolova-Simons M 

PROVIDER: S-EPMC10630382 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature