Knowledge-based lean six sigma system for enhancing quality management performance in healthcare environment

Abstract

Purpose

This paper aims to present the development of a knowledge-based system (KBS) to support the implementation of Lean Six Sigma (L6s) principles applied to enhance quality management (QM) performance within a health-care environment.

Design/methodology/approach

The process of KBS building has been started by acquiring knowledge from experts in field of L6σ and QM in health care. The acquired knowledge has been represented in a rule-based approach for capturing L6σ practices. These rules are produced in IF […].THEN way where IF is the premise and THEN is the action. The produced rules have been integrated with gauging absence pre-requisites (GAP) technique to facilitate benchmarking of best practice in a health-care environment. A comprehensive review of the structure of the system is given, detailing a typical output of the KBS.

Findings

Implementation of L6s principles to enhance QM performance in a health-care environment requires a pre-assessment of the organisation’s competences. The KBS provides an enhanced strategic and operational decision-making hierarchy for achieving a performance benchmark.

Research limitations/implications

The KBS needs validation in real health-care environment, which will be done in Oman’s hospitals.

Practical implications

The paper is intended to benefit QM practitioners in the health-care sector during decision-making to achieve performance improvement against a best practice benchmark.

Originality/value

This research presents a novel application of a hybrid KBS with GAP methodology to support the implementation of L6s principles to enhance QM performance in a health-care environment.

Citation

Al Khamisi, Y.N., Khan, M.K. and Munive-Hernandez, J.E. (2019), "Knowledge-based lean six sigma system for enhancing quality management performance in healthcare environment", International Journal of Lean Six Sigma, Vol. 10 No. 1, pp. 211-233. https://doi.org/10.1108/IJLSS-06-2017-0066