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

Khamisi, Yousuf Nasser Al; Khan, Muhammad Nadeem; Munive-Hernandez, Jose Eduardo

doi:10.1108/ijlss-06-2017-0066

Cited by 30 publications

(23 citation statements)

References 47 publications

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“…Failures of KBS range from selecting the wrong problem domain, chasing the wrong talent to develop the KBS, poor verification and validation of the system, a lack of understanding of the expert's knowledge, and other causes. Currently, KBS is widely applied in business organizations to facilitate the decision making process (Udin, 2004, Nawawi, 2009, Milana et al, 2014, Aldairi, 2015, Al Khamisi et al, 2018aand Al Khamisi et al, 2018d because it is a time-saving and accurate decision-making tool. It makes uncommon expertise more commonly available and provides beginners trusted information.…”

Section: Knowledge Representationmentioning

confidence: 99%

The design of a knowledge-based system for quality management in healthcare: case study

Khamisi

Khan

2019

IJAOM

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Section: Knowledge Representationmentioning

confidence: 99%

The design of a knowledge-based system for quality management in healthcare: case study

Khamisi

Khan

2019

IJAOM

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“…The results of this test were published by authors. 40 A model consisting of strategic and operational levels is presented in Figure 1. It is the development process of KB-QMHE which covered the main strategic and operational issues affecting the QMHE.…”

Section: The Modelmentioning

confidence: 99%

“…In fact, the process of building and referencing each dimension has been elaborated in three published papers. [38][39][40] Knowledge-based system KBS is a computer software that can use a knowledge base to support decision-making to solve real-world problems. 43 The actual work of this system is to save experts' knowledge in its inference engine to be used by the user at any time.…”

Section: The Modelmentioning

confidence: 99%

Assessing quality management system at a tertiary hospital in Oman using a hybrid knowledge-based system

Khamisi

Khan

2018

International Journal of Engineering Business Management

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The cost of medical care is snowballing at an alarming and unmaintainable rate universally. Consequently, the need for a trusted quality management (QM) system at healthcare organizations is a must. Such system will aid the healthcare governance to increase the effectiveness and decrease the cost. It will help in minimizing the risk and enhancing patient safety. Several challenges facing healthcare QM in Oman are creating computerizing monitoring tool and confirming commitment of decision makers at all levels. The Report of Quality and Patient Safety (RQPS) in Oman 2016 highlighted the low level of patient safety and quality culture among staff. It recommended to inaugurate a well-defined organizational chart based on each healthcare organization's vision and mission. Therefore, it is important to design a national accreditation system that is accredited by an international accreditation body. Such step will help in prioritizing the needs and minimizing the cost of maintaining and upgrading systems. To overcome these challenges, this article is presenting a novel methodology of hybrid knowledge-based (KB) system to assess QM in healthcare environment (QMHE) using gauging absence of prerequisites tool for benchmarking and analytical hierarchy process for prioritizing. The KB-QMHE model can be used as a standard to assess QM at any healthcare organization around the globe. The results showed that 852 questions were answered by the quality managers in a tertiary hospital in Oman; the percentage of bad points in this hospital was 32%. The KB-QMHE model has clearly shown that the priority 1, in level 0, is to focus on the patient-centered dimension in the healthcare quality dimensions submodule. Output, also, suggested a prioritized action plan covering healthcare governance module, healthcare leadership module and healthcare organization's resources module in level 1-3. Keywords Knowledge-based system, quality management in healthcare environment, gauging absence of prerequisites, analytical hierarchy process, Oman Date

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“…Healthcare requires continuous and systematic improvement to remain cost-effective, provide better care and high quality of service (Singh et al , 2014). Healthcare organizations have started to give importance to improve quality performance such as total quality management, Six Sigma and lean thinking (Al Khamisi et al , 2019). All combinations of lean and Six Sigma have gained attention in the manufacturing and healthcare sector.…”

Section: Introductionmentioning

confidence: 99%

Assessment of readiness level for implementing lean six sigma in healthcare organization using fuzzy logic approach

Vaishnavi

Suresh

2020

IJLSS

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Purpose Lean Six Sigma (LSS) is a widely accepted business improvement methodology in healthcare, which aims to improve operations and quality and reduce cost, medical errors and waiting time by combing the principles of lean thinking with Six Sigma methodologies. To implement LSS successfully in healthcare organizations it is necessary to know the readiness level before starting the change process. Thus, the purpose of this paper is to assess the readiness level for the implementation of LSS in healthcare using a fuzzy logic approach. Design/methodology/approach The current study uses a fuzzy logic approach to develop an assessment model for readiness to implement LSS. The conceptual model for readiness is developed with 5 enablers, 16 criteria and 48 attributes identified from the literature review. The current study does the study in a medium-size hospital from India. Findings The fuzzy readiness for implementation of LSS index (FRLSSI) and fuzzy performance importance index (FPII) are calculated to identify the readiness level for the implementation of LSS in the case hospital. The FRLSSI is computed as average ready with (3.30, 5.06 and 6.83) and the FPII computed helps to identify 15 weaker attributes from 48 attributes. Research limitations/implications The current study uses only one hospital for study. In the future, the model can be tested in many hospitals. Practical implications The current study would be used by the managers of a healthcare organization to identify the readiness level of their organization to implement LSS. The proposed model is based on the identification of enablers, criteria and attributes to assess the readiness level of a healthcare organization and it helps to improve the readiness level to implement LSS effectively. Originality/value The present study contributes to the knowledge of readiness for the implementation of LSS in a healthcare organization. The conceptual model is developed for assessing the readiness level of a healthcare organization and it helps to improve the readiness level for successful implementation of LSS. Weaker attributes are identified and necessary corrective actions should be taken by the management to improve the readiness. The continuation of the assessment readiness model over a period of time would help to improve the readiness level of healthcare for the implementation of LSS.

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

Cited by 30 publications

References 47 publications

The design of a knowledge-based system for quality management in healthcare: case study

The design of a knowledge-based system for quality management in healthcare: case study

Assessing quality management system at a tertiary hospital in Oman using a hybrid knowledge-based system

Assessment of readiness level for implementing lean six sigma in healthcare organization using fuzzy logic approach

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