Evaluation of system modelling techniques for waste identification in lean healthcare applications

Maitha Alkaabi; Mecit Can Emre Simsekler; Raja Jayaraman; Abdulqader Al Kaf; Hussam Ghalib; Dima Quraini; Samer Ellahham; E. Murat Tuzcu; Kudret Demirli

doi:10.2147/RMHP.S283189

Evaluation of system modelling techniques for waste identification in lean healthcare applications

Maitha Alkaabi, Mecit Can Emre Simsekler, Raja Jayaraman, Abdulqader Al Kaf, Hussam Ghalib, Dima Quraini, Samer Ellahham, E. Murat Tuzcu, Kudret Demirli

Management Science & Engineering

Research output: Contribution to journal › Article › peer-review

7 Scopus citations

Abstract

Purpose: Waste identification plays a vital role in lean healthcare applications. While the value stream map (VSM) is among the most commonly used tools for waste identification, it may be limited to visualize the behaviour of dynamic and complex healthcare systems. To address this limitation, system modelling techniques (SMTs) can be used to provide a comprehensive picture of various system-wide wastes. However, there is a lack of evidence in the current literature about the potential contribution of SMTs for waste identification in healthcare processes. Methods: This study evaluates the usability and utility of six types of SMTs along with the VSM. For the evaluation, interview-based questionnaires were conducted with twelve stakeholders from the outpatient clinic at the Heart and Vascular Institute at Cleveland Clinic Abu Dhabi. Results: VSM was found to be the most useful diagram in waste identification in general. However, some SMTs that represent the system behaviour outperformed the VSM in identifying particular waste types, e.g., communication diagram in identifying over-processing waste and flow diagram in identifying transportation waste. Conclusion: As behavioural SMTs and VSM have unique strengths in identifying particular waste types, the use of multiple diagrams is recommended for a comprehensive waste identification in lean. However, limited resources and time, as well as limited experience of stakeholders with SMTs, may still present obstacles for their potential contribution in lean healthcare applications.

Original language	British English
Pages (from-to)	3235-3243
Number of pages	9
Journal	Risk Management and Healthcare Policy
Volume	13
DOIs	https://doi.org/10.2147/RMHP.S283189
State	Published - 2020

Keywords

Healthcare operations
Kaizen
Lean healthcare
System approaches
System modelling techniques
Value stream map
Waste identification

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10.2147/RMHP.S283189

Cite this

@article{b342078452b94a16905752c84b16c6bd,

title = "Evaluation of system modelling techniques for waste identification in lean healthcare applications",

abstract = "Purpose: Waste identification plays a vital role in lean healthcare applications. While the value stream map (VSM) is among the most commonly used tools for waste identification, it may be limited to visualize the behaviour of dynamic and complex healthcare systems. To address this limitation, system modelling techniques (SMTs) can be used to provide a comprehensive picture of various system-wide wastes. However, there is a lack of evidence in the current literature about the potential contribution of SMTs for waste identification in healthcare processes. Methods: This study evaluates the usability and utility of six types of SMTs along with the VSM. For the evaluation, interview-based questionnaires were conducted with twelve stakeholders from the outpatient clinic at the Heart and Vascular Institute at Cleveland Clinic Abu Dhabi. Results: VSM was found to be the most useful diagram in waste identification in general. However, some SMTs that represent the system behaviour outperformed the VSM in identifying particular waste types, e.g., communication diagram in identifying over-processing waste and flow diagram in identifying transportation waste. Conclusion: As behavioural SMTs and VSM have unique strengths in identifying particular waste types, the use of multiple diagrams is recommended for a comprehensive waste identification in lean. However, limited resources and time, as well as limited experience of stakeholders with SMTs, may still present obstacles for their potential contribution in lean healthcare applications.",

keywords = "Healthcare operations, Kaizen, Lean healthcare, System approaches, System modelling techniques, Value stream map, Waste identification",

author = "Maitha Alkaabi and Simsekler, {Mecit Can Emre} and Raja Jayaraman and {Al Kaf}, Abdulqader and Hussam Ghalib and Dima Quraini and Samer Ellahham and Tuzcu, {E. Murat} and Kudret Demirli",

note = "Funding Information: This publication is supported by the Khalifa University of Science and Technology under Award No. RCII-2019-002, Center for Digital Supply Chain and Operations Management, and Cleveland Clinic Abu Dhabi. The authors would like to thank all hospital staff who voluntarily participated in this study at the Heart and Vascular Institute at the Cleveland Clinic Abu Dhabi, UAE. Funding Information: This publication is supported by the Khalifa University of Science and T echnology under A ward No. RCII-2019-002, Center for Digital Supply Chain and Operations Management, and Cleveland Clinic Abu Dhabi. The authors would like to thank all hospital staff who voluntarily participated in this study at the Heart and V ascular Institute at the Cleveland Clinic Abu Dhabi, UAE. Publisher Copyright: {\textcopyright} 2020, Dove Medical Press Ltd. All rights reserved.",

year = "2020",

doi = "10.2147/RMHP.S283189",

language = "British English",

volume = "13",

pages = "3235--3243",

journal = "Risk Management and Healthcare Policy",

issn = "1179-1594",

publisher = "Dove Medical Press Ltd",

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TY - JOUR

T1 - Evaluation of system modelling techniques for waste identification in lean healthcare applications

AU - Alkaabi, Maitha

AU - Simsekler, Mecit Can Emre

AU - Jayaraman, Raja

AU - Al Kaf, Abdulqader

AU - Ghalib, Hussam

AU - Quraini, Dima

AU - Ellahham, Samer

AU - Tuzcu, E. Murat

AU - Demirli, Kudret

N1 - Funding Information: This publication is supported by the Khalifa University of Science and Technology under Award No. RCII-2019-002, Center for Digital Supply Chain and Operations Management, and Cleveland Clinic Abu Dhabi. The authors would like to thank all hospital staff who voluntarily participated in this study at the Heart and Vascular Institute at the Cleveland Clinic Abu Dhabi, UAE. Funding Information: This publication is supported by the Khalifa University of Science and T echnology under A ward No. RCII-2019-002, Center for Digital Supply Chain and Operations Management, and Cleveland Clinic Abu Dhabi. The authors would like to thank all hospital staff who voluntarily participated in this study at the Heart and V ascular Institute at the Cleveland Clinic Abu Dhabi, UAE. Publisher Copyright: © 2020, Dove Medical Press Ltd. All rights reserved.

PY - 2020

Y1 - 2020

N2 - Purpose: Waste identification plays a vital role in lean healthcare applications. While the value stream map (VSM) is among the most commonly used tools for waste identification, it may be limited to visualize the behaviour of dynamic and complex healthcare systems. To address this limitation, system modelling techniques (SMTs) can be used to provide a comprehensive picture of various system-wide wastes. However, there is a lack of evidence in the current literature about the potential contribution of SMTs for waste identification in healthcare processes. Methods: This study evaluates the usability and utility of six types of SMTs along with the VSM. For the evaluation, interview-based questionnaires were conducted with twelve stakeholders from the outpatient clinic at the Heart and Vascular Institute at Cleveland Clinic Abu Dhabi. Results: VSM was found to be the most useful diagram in waste identification in general. However, some SMTs that represent the system behaviour outperformed the VSM in identifying particular waste types, e.g., communication diagram in identifying over-processing waste and flow diagram in identifying transportation waste. Conclusion: As behavioural SMTs and VSM have unique strengths in identifying particular waste types, the use of multiple diagrams is recommended for a comprehensive waste identification in lean. However, limited resources and time, as well as limited experience of stakeholders with SMTs, may still present obstacles for their potential contribution in lean healthcare applications.

AB - Purpose: Waste identification plays a vital role in lean healthcare applications. While the value stream map (VSM) is among the most commonly used tools for waste identification, it may be limited to visualize the behaviour of dynamic and complex healthcare systems. To address this limitation, system modelling techniques (SMTs) can be used to provide a comprehensive picture of various system-wide wastes. However, there is a lack of evidence in the current literature about the potential contribution of SMTs for waste identification in healthcare processes. Methods: This study evaluates the usability and utility of six types of SMTs along with the VSM. For the evaluation, interview-based questionnaires were conducted with twelve stakeholders from the outpatient clinic at the Heart and Vascular Institute at Cleveland Clinic Abu Dhabi. Results: VSM was found to be the most useful diagram in waste identification in general. However, some SMTs that represent the system behaviour outperformed the VSM in identifying particular waste types, e.g., communication diagram in identifying over-processing waste and flow diagram in identifying transportation waste. Conclusion: As behavioural SMTs and VSM have unique strengths in identifying particular waste types, the use of multiple diagrams is recommended for a comprehensive waste identification in lean. However, limited resources and time, as well as limited experience of stakeholders with SMTs, may still present obstacles for their potential contribution in lean healthcare applications.

KW - Healthcare operations

KW - Kaizen

KW - Lean healthcare

KW - System approaches

KW - System modelling techniques

KW - Value stream map

KW - Waste identification

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U2 - 10.2147/RMHP.S283189

DO - 10.2147/RMHP.S283189

M3 - Article

AN - SCOPUS:85099288748

SN - 1179-1594

VL - 13

SP - 3235

EP - 3243

JO - Risk Management and Healthcare Policy

JF - Risk Management and Healthcare Policy

ER -

Evaluation of system modelling techniques for waste identification in lean healthcare applications

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Keywords

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