2nd European International Conference on Industrial Engineering and Operations Management

Developing a Knowledge-Based Lean Six Sigma Model to Increase the Effectiveness of Healthcare Organisational Resources Management

Yousuf Al Khamisi
Publisher: IEOM Society International
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Track: Energy and Resource Efficiency
Abstract

Purpose– This paper develops a model of a Knowledge-Based (KB) System using Lean Six Sigma (L6σ) principles to increase the effectiveness of healthcare organisational resources management.

Design/methodology/approach– Using L6σ principles to enhance healthcare resources’ effectiveness needs a pre-assessment of the healthcare organisation’s capabilities. The model will be developed using a rule based approach of KB system. The KB system embeds Gauging Absence of Pre-requisite (GAP) for benchmarking and Analytical Hierarchy Process (AHP) for prioritization. A comprehensive literature review will be covered for the main contents of the model with a typical output of GAP analysis and AHP 

Findings–The proposed KB system has benchmarked the current status of healthcare resources with the ideal benchmark one (resulting from extensive evaluation) by the KB/GAP/AHP system of international organisational resources management in healthcare environments.

Research limitations/implications– Future work includes validating the implementation model in healthcare environments around the world.

Originality/value– This research presents a novel application of a hybrid KB/GAP/AHP methodology to implement L6σ principles to enhance Healthcare resources management. This approach will assist healthcare governor’s decision making to reach performance improvement against a best practice benchmark.

Keywords

Lean Six Sigma (L6σ), Knowledge-Based System (KBS), Healthcare Organisational Resources Management, Gauge Absence Prerequisites (GAP), and Analytical Hierarchy Process (AHP).

Acknowledgements

Authors extend their appreciation and gratitude to Sultan Qaboos University, Oman that has granted the financial support for this study.

Published in: 2nd European International Conference on Industrial Engineering and Operations Management, Paris, France

Publisher: IEOM Society International
Date of Conference: July 26-27, 2018

ISBN: 978-1-5323-5945-3
ISSN/E-ISSN: 2169-8767