Abstract
This study advances healthcare process optimization, focusing on surgery roadmaps in the healthcare system, a scenario exemplifying optimization challenges due to limited information. This chapter emphasizes enhancing efficiency and resource utilization by employing lean manufacturing, operational research, simulation, data envelopment analysis, and non-dominance analysis. This study discovers 32 correlated patient pathways, showing shared activities and simultaneous multi-route impact from optimization strategies. Instead of merely analyzing pathway performance, the study applies data envelopment analysis to various investment scenarios, providing insights for healthcare decision-makers on improving patient care quality and efficiency. The juxtaposition of data envelopment analysis with a non-dominance algorithm in this mixed-method approach offers a robust framework for addressing healthcare operational challenges, particularly under information scarcity, and promotes continuous process improvement.
TopBackground
The literature strongly supports the transformative role of Lean Manufacturing, operational research techniques, simulation, and Data Envelopment Analysis (DEA) in boosting healthcare systems. For example, experts recognize Discrete-event simulation (DES) as a crucial tool for tackling dynamic and complex systems in healthcare, frequently used with Lean and Six Sigma methodologies to enhance efficiency metrics (Vázquez-Serrano et al., 2021). Similarly, a systematic review by Ortíz-Barrios and Alfaro-Saíz (2020) highlights the prominence of computer simulation and Lean Manufacturing in solving operational problems in Emergency Departments. Moreover, the integration of Lean tools with advanced technologies like Industry 4.0 has demonstrated improvements in production processes, indicating potential applicability in healthcare settings (Florescu & Barabas, 2022). These methodologies collectively provide a powerful framework for decision-making, quality improvement, and efficiency optimization in healthcare settings.
Key Terms in this Chapter
Operational Efficiency: The effectiveness of an organization in using its resources to produce the desired output. In healthcare, this term refers to using medical and administrative resources efficiently to provide high-quality patient care.
Design-Thinking: An iterative process that aims to understand users, challenge assumptions, and redefine problems to identify alternative strategies and solutions. In healthcare, professionals apply it to enhance patient experiences and service delivery, focusing on user-centered design.
Simulation Modeling: A technique for creating a digital model of a real-world system or process. In healthcare, simulation modeling is utilized for analyzing and enhancing patient flow, resource allocation, and process management using computers, simulating real processes without interruptions.
Non-Dominance in Efficient Frontier: A concept in performance measurement where the efficient frontier represents optimal trade-offs between different objectives. In healthcare, it's utilized to pinpoint the most efficient resource usage.
Lean Healthcare: The application of lean principles and methodologies in healthcare settings, aimed at reducing waste, improving patient care, and enhancing value delivery by optimizing workflows and processes.
Computational Complexity: The study of the resources a computer requires to solve a specific problem. Analysts often examine this in terms of the problem's size and the time needed to solve a mathematical problem.
Co-Creation: A process where multiple stakeholders collaboratively contribute to developing a new solution or service. In healthcare, this concept could involve patients, providers, administrators, relatives, researchers, policy makers, and so on, jointly creating strategies for improved patient care and operational efficiency.
Lean Manufacturing Techniques: Methods originally developed in manufacturing to optimize production processes, minimize waste, and boost efficiency. In healthcare, these techniques improve patient flow and reduce operational inefficiencies.
Data Envelopment Analysis: A non-parametric method in operations research and economics for measuring the efficiency of decision-making units, like hospitals, pathways, and other resources, by comparing their inputs and outputs. It aids in identifying efficient practices and areas needing improvement at the inputs or outputs to prioritize.
Exploratory Data Analysis: An approach to analyzing data sets to summarize their main characteristics, often employing statistical graphics and other data visualization methods. In healthcare, this method is vital for uncovering trends, patterns, and anomalies in patient or business data.