Lean, Six Sigma, and Simulation: Evidence from Healthcare Interventions

Diego Tlapa, Ignacio Franco-Alucano, Jorge Limon-Romero (), Yolanda Baez-Lopez () and Guilherme Tortorella
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Diego Tlapa: Facultad de Ingeniería, Arquitectura y Diseño, Universidad Autónoma de Baja California, Ensenada 23080, Mexico
Ignacio Franco-Alucano: Facultad de Ingeniería, Arquitectura y Diseño, Universidad Autónoma de Baja California, Ensenada 23080, Mexico
Jorge Limon-Romero: Facultad de Ingeniería, Arquitectura y Diseño, Universidad Autónoma de Baja California, Ensenada 23080, Mexico
Yolanda Baez-Lopez: Facultad de Ingeniería, Arquitectura y Diseño, Universidad Autónoma de Baja California, Ensenada 23080, Mexico
Guilherme Tortorella: Department of Mechanical Engineering, University of Melbourne, Melbourne, VIC 3010, Australia

Sustainability, 2022, vol. 14, issue 24, 1-25

Abstract: In the Industry 4.0 era, healthcare services have experienced more dual interventions that integrate lean and six sigma with simulation modeling. This systematic review, which focuses on evidence-based practice and complies with the PRISMA guidelines, aims to evaluate the effects of these dual interventions on healthcare services and provide insights into which paradigms and tools produce the best results. Our review identified 4018 studies, of which 39 studies met the inclusion criteria and were selected. The predominantly positive results reported in 73 outcomes were mostly related to patient flow: length of stay, waiting time, and turnaround time. In contrast, there is little reported evidence of the impact on patient health and satisfaction, staff wellbeing, resource use, and savings. Discrete event simulation stands out in 74% of the interventions as the main simulation paradigm. Meanwhile, 66% of the interventions utilized lean, followed by lean-six sigma with 28%. Our findings confirm that dual interventions focus mainly on utilization and access to healthcare services, particularly on either patient flow problems or problems concerning the allocation of resources; however, most interventions lack evidence of implementation. Therefore, this study promotes further research and encourages practical applications including the use of Industry 4.0 technologies.

Keywords: lean; six sigma; simulation; industry 4.0; patient flow; wait time; length of stay (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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