Abstract
ABSTRACT
Improving capacity management in the surgical resources is a critical activity for improving surgical service delivery to balance rising surgical demand with restricted hospital resources. While hospitals face inherent sources of variability (e.g., uncertain durations and arrivals of emergency cases), managing these variabilities can lead to more effective use of surgical resources. The purpose of this research is to investigate how hospital performance can be improved and surgical service capacity increased by managing the variabilities. Coordinating activities, taking a systems-wide perspective, and providing sufficient buffering can decrease elective surgery cancellations and enhance utilisation, the quality of care, and patient satisfaction. To address this purpose, this thesis is based on three distinct studies to meet three complementary research objectives.
The first objective was to examine the phenomenon of surgery cancellation of elective surgeries to identify opportunities to improve the quality of surgical service delivery by controlling variability through increasing coordination of surgery resources. A systematic review of 87 articles was conducted using Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) and assessing the methodological quality of systematic review with Measurement Tool to Assess Systematic Reviews (AMSTAR) guidelines. The results show the main reasons for surgery cancellations are related to internal factors that are controllable by hospital managers. The study outcomes lead to the subsequent research objectives to improve the surgical service delivery by increasing the coordination, system-wide perspective, and buffering between different activities and resources of the surgery process.
The second objective was to examine operating room planning and scheduling. The investigation focused on how coordination between involved resources and activities manages duration and arrival variability by adopting the Theory of Variability, Uncertainties, and Buffering (TVUB). To answer this objective, this study developed a new multi-objective mathematical model that includes both upstream and downstream resources and variabilities and uncertainties to improve coordination and determine the appropriate amounts of time buffering. The results showed that comprehensive scheduling based on TUVB and increased coordination between resources improves simple scheduling models by controlling variability (Law of Variability) and bottlenecks (Law of Bottlenecks) to support an even patient flow through the surgical process. This model supported the assignment and sequencing of electives and non-electives to the operating room while improving all objectives by making trade-off three stakeholder groups’ priorities: hospital managers, patients, and staff satisfaction.
The third objective was to evaluate Operating Room Capacity Management (ORCM) policies, such as assigning a dedicated operating room for emergencies. The policies support balancing resources for both elective and non-elective surgeries while considering time buffers to manage the emergency arrival variability and the bottleneck impact to enhance hospital performance. A discrete event simulation model was applied to investigate appropriate operating room capacity management and the hospital circumstance interaction on these policies. The results show that different policies must be set based on different circumstances, and no one policy is always superior. Furthermore, the sensitivity analysis of how the scheduling policy influences the ORCM policy demonstrates that adopting a comprehensive surgery scheduling increases the response rate and effectively improves the efficiency of ORCM policies.
This thesis contributes to operations management theory by investigating how hospitals can use operations research methods (e.g., using a scheduling model and Discrete Event Simulation) and factory physics theory (e.g., using variability, bottlenecks, and coordination between resources) for improvement. The frameworks provide a foundation for improving coordination and buffering among resources and adopting appropriate operating room capacity management policies to manage variability in the surgical process. While the second and third studies show that coordination among hospital resources and implementing the most appropriate ORCM policy improves outcomes, the third study also shows how a combination of these decisions can enhance outcomes further. This study provides a guideline to help hospital managers and health care policymakers to improve surgical service delivery by understanding the consequences and benefits for the hospital (e.g., improved utilisation) and patients (e.g., decreased cancellations) and how these outcomes will change depending on the mixture of ORCM policy and scheduling decisions.