A new model designed to enhance hospital operations could significantly improve surgeons’ efficiency.
Researchers investigated issues related to the timing and scheduling of surgeries and patient recovery-unit stays.
Researchers developed an integrated elective surgery assignment, sequencing, and scheduling problem (ESASSP). They found that implementing solutions based on their study’s models could significantly reduce congestion in recovery units, delays in operating rooms, overtime, idle time and costs.
The study was conducted by researchers from Carnegie Mellon University, the University of Southern California (USC), Texas Tech University, and the Medical University of South Carolina. It was published in the European Journal of Operational Research.
Rema Padman, professor of management science and healthcare informatics at Carnegie Mellon’s Heinz College, and the study’s co-author, said: ‘Our findings offer valuable insights into the ESASSP and demonstrate the practical impact of our integrated approaches.’
The ESASSP is a tough, resource-limited scheduling challenge highlighted by the study’s authors. Key issues include coordinating costly resources, such as operating rooms, ICU beds, and ward beds with limited capacity.
Additionally, assigning surgeries often leads to overtime, long waits, congestion in recovery units and premature discharges from ICUs and wards, all of which risk poorer health outcomes.
Given these challenges, hospitals could greatly benefit from integrated approaches to addressing the ESASSP.
This study analyses three sets of real-world surgical data and provides key insights for healthcare providers:
• Hospitals performing elective surgeries should use an integrated stochastic optimisation model for scheduling to cut costs by 24% to 60%.
• There’s a trade-off between surgical volume and operational performance, with no clear best approach.
• Data-driven models can help hospitals where surgery duration and recovery times are hard to predict or are constantly changing.
The authors caution that while their proposed models could provide practitioners with guidelines for ESASSP decisions, they are not directly implementable in practice without further work to develop and test tools that ensure successful adaptation, especially since most hospitals lack staff with expertise in optimisation.
Karmel S Shehadeh, assistant professor of industrial and systems engineering at USC, who led the study, said: ‘Prior studies have tackled isolated components of the ESASSP. Ours introduces the first models that account for uncertainties and ambiguities in surgery durations and post-operative lengths of stay in recovery units, while also addressing the challenges of optimising surgery schedules under the limited capacities of the ICU and other wards.’
