A New Service Model for Identifying and Improving the Quality of Emergency Department Operations in Tertiary Settings

The conceptual framework adapted by this thesis discusses improving the quality of care in tertiary care hospitals’ Emergency Department (ED), which is challenged by the ever-increasing number of patients seeking emergency treatment. The demand for emergency services is much more than supply, and resources are comparatively less, which can lead to deterioration of patient satisfaction and reduction in quality of services. Emergency department managers are trying to achieve a balance between quality services for patients and efficiency for providers. This research looks at many and varied causes of waiting in the emergency department and examines its effect on patients and staff. The research presents a compelling argument that the causes and effects of waiting are more than just inconveniences, and result in suboptimal patient outcomes, and patient satisfaction. Literature from various operations management and emergency medicine journals is critically reviewed to identify relevant issues of longer waiting times and resource utilization. Whilst past studies predominantly look at one of either input, throughput, or output processes for improvement; all three need consideration as these are interdependent measures to achieve enhanced quality care. Thus, the objective of the study is to develop a service model for decision-makers to identify the best opportunities for improvement with flexibility and statistical reliability considering all interdependent processes. This study focuses on inevitable complexities within ED processes and services and addresses opportunities for improvement using Lean principles coupled with a simulation optimization approach. Complexities such as differences in healthcare systems worldwide, patient acuity, different locations of ED, physical layouts, and staffing levels identified need to develop an improvement model. Developing a simulation model in an ED environment is challenging because of uncertainty in patient elements and difficulty in obtaining the necessary data. This research seeks to optimize the use of existing human resources in resource-constrained ED environments, ensuring that they are allocated efficiently to reduce waiting times and length of stay. It integrates both simulation and optimization tools that allow the evaluation of different ED configurations and resource allocation strategies for efficiency and cost-effectiveness. It presents an organised method for assessing the impact of different decisions on ED operations in a controlled and risk-free environment, ultimately leading to more informed and effective resource allocation planning. It helps to continuously monitor and adapt to changing conditions and operational challenges within the ED. The efficacy and intricacy of the new developed model was validated in a tertiary care hospital in India.

The research contributes theoretically with a new simulation optimization framework to reduce waiting and total length of stay of patients in ED and to achieve overall performance improvement; extending contribution in the current applied research and is a novelty of the research as no past studies addressed improvement model in the context of ED set-up with limited budget and resources and integrating Lean theoretical frameworks and a simulation-optimization approach. The research revealed specific factors contributing to patient waiting times which included resource allocation issues, bottleneck triage process for category-3 patients and operational inefficiencies. Waste reduction methods such as Lean principles were identified as a potential solution. Implementing Lean principles within the ED was a viable approach for improving operations by eliminating waste, thus contributing to greater efficiency. The developed simulation model and mathematical model for optimal staff scheduling are both contextually relevant and replicable in similar healthcare settings. It acknowledges the multifaceted nature of ED operations, encompassing areas such as patient flow, resource allocation and quality measures. The study uncovered the effectiveness of implementing an alternative triage method for category 3 patients in reducing waiting times for all non-urgent patients. Although this study is focused on the tertiary care Indian hospital operations, the improvement model and strategies developed during the research can be implemented successfully in other EDs that operate in similar manner.

The implementation of triage process improvement and optimal staff scheduling has led to a substantial reduction in the total length of stay for all patients in the ED (45.18%) and resulted in marked reductions in waiting times for patients across all categories ranging from 30.90% to 60.47%. The success of this research lies in its comprehensive approach, incorporating Lean principles, simulation and optimization techniques. The interconnected use of these strategies has allowed for a thorough analysis, efficient resource allocation, operational efficiency and continuous improvement in real-world ED settings. The continuous improvement mindset embedded in these methodologies and the tangible improvements in total length of stay and waiting times underscore the real-world impact of this research, benefiting both patients and healthcare providers in the dynamic environment of ED. The developed model in this research may serve as a blueprint for improving operations across diverse healthcare environments.