Computer-Assisted Simulations Using R and RStudio to Assist in Operations Research and Analysis in the Context of Clinical Laboratory Management

Abstract

Operations research (OR) is a valuable yet underutilized field in clinical laboratory management, offering practical solutions to optimize workflows, resource allocation, and decision-making. Despite its potential, the adoption of OR methodologies remain limited due to a lack of training and familiarity among pathologists and laboratory professionals. This paper addresses this gap by presenting an accessible introduction and practical guide to analyzing operations research problems in clinical laboratories using computer-assisted simulations in R, implemented within the R Studio environment. The proposed framework emphasizes simplicity and flexibility, leveraging the extensive capabilities of base R to model and analyze critical OR questions. The paper outlines step-by-step methods for defining problems, constructing simulation models, and interpreting results, ensuring that readers can replicate and adapt these techniques to their unique laboratory contexts. Key features of the framework include its emphasis on reproducibility, customization, and the integration of data-driven insights into decision-making processes. Case studies and examples drawn from real-world laboratory scenarios illustrate the application of R simulations to address challenges such as minimizing turnaround times, balancing staffing levels, and managing inventory efficiently. This guide aims to empower laboratory professionals and pathologists with the tools and skills to integrate operations research into their practice, fostering a culture of innovation and efficiency in clinical settings. By bridging the gap between OR theory and practical application, this paper contributes to the broader adoption of computational approaches in laboratory management, ultimately enhancing the quality and sustainability of healthcare services.