Safety process innovation in medical service industry

Luo, Chih‐Ming; Chang, Hung‐Fan

doi:10.1007/s11135-012-9697-0

Cited by 5 publications

(3 citation statements)

References 19 publications

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“…Although in studies such as Ginn et al (1998), Almannai et al (2008), Xingyu et al (2010), Tanık (2010), Luo and Chang (2013), Zheng et al (2013) and Bhuvanesh Kumar and Parameshwaran (2018), the outcomes of QFD were entered into FMEA, or in studies such as Chen (2016), the RPN of FMEA was entered into QFD as importance rating of customer demands, the proposed approach is a true type of the so-called “integration of FMEA and QFD” because the three main elements of FMEA formed the structure of QFD. In other words, the proposed approach can be considered as an innovation in the FMEA structure, not as a data provider prior to it or a data receiver after it.…”

Section: Discussionmentioning

confidence: 99%

Developing a two-phase QFD for improving FMEA: an integrative approach

Shaker

Shahin

Jahanyan

2019

IJQRM

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Purpose The purpose of this paper is to propose an integrative approach for improving failure modes and effects analysis (FMEA). Design/methodology/approach An extensive literature review on FMEA has been performed. Then, an integrative approach has been proposed based on literature review. The proposed approach is an integration of FMEA and quality function deployment (QFD). The proposed approach includes a two-phase QFD. In the first phase, failure modes are prioritized based on failure effects and in the second phase, failure causes are prioritized based on failure modes. The proposed approach has been examined in a case example at the blast furnace operation of a steel-manufacturing company. Findings Results of the case example indicated that stove shell crack in hot blast blower, pump failure in cooling water supply pump and bleeder valves failed to operate are the first three important failure modes. In addition, fire and explosion are the most important failure effects. Also, improper maintenance, over pressure and excess temperature are the most important failure causes. Findings also indicated that the proposed approach with the consideration of interrelationships among failure effects, failure mode and failure causes can influence and adjust risk priority number (RPN) in FMEA. Research limitations/implications As manufacturing departments are mostly dealing with failure effects and modes of machinery and maintenance departments are mostly dealing with causes of failures, the proposed model can support better coordination and integration between the two departments. Such support seems to be more important in firms with continuous production lines wherein line interruption influences response to customers more seriously. A wide range of future study opportunities indicates the attractiveness and contribution of the subject to the knowledge of FMEA. Originality/value Although the literature indicates that in most of studies the outcomes of QFD were entered into FMEA and in some studies the RPN of FMEA was entered into QFD as importance rating, the proposed approach is a true type of the so-called “integration of FMEA and QFD” because the three main elements of FMEA formed the structure of QFD. In other words, the proposed approach can be considered as an innovation in the FMEA structure, not as a data provider prior to it or a data receiver after it.

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Section: Discussionmentioning

confidence: 99%

Developing a two-phase QFD for improving FMEA: an integrative approach

Shaker

Shahin

Jahanyan

2019

IJQRM

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“…Today, it is used as a risk assessment tool in various fields [58]. Luo and Chang [59] used FMEA as a proper tool in their safety innovation model, in which they linked customer requirements and safety. FMEA has been proven to be one of the most important early preventative initiatives for companies and its popularity is still increasing; however, in the literature, there are several studies which have listed the shortcomings of risk priority number (RPN) calculations [60][61][62].…”

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confidence: 99%

Prioritization of Medical Errors in Patient Safety Management: Framework Using Interval-Valued Intuitionistic Fuzzy Sets

2020

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Medical errors negatively affect patients, healthcare professionals, and healthcare establishments. Therefore, all healthcare service members should be attentive to medical errors. Research has revealed that most medical errors are caused by the system, rather than individuals. In this context, guaranteeing patient safety and preventing medical faults appear to be basic elements of quality in healthcare services. Healthcare institutions can create internal regulations and follow-up plans for patient safety. While this is beneficial for the dissemination of patient safety culture, it poses difficulties in terms of auditing. On the other hand, the lack of a standard patient safety management system, has led to great variation in the quality of the provided service among hospitals. Therefore, this study aims to create an index system to create a standard system for patient safety by classifying medical errors. Due to the complex nature of healthcare and its processes, interval-valued intuitionistic fuzzy logic is used in the proposed index system. Medical errors are prioritized, based on the index scores that are generated by the proposed model. Because of this systematic study, not only can the awareness of patient safety perception be increased in health institutions, but their present situation can also be displayed, on the basis of each indicator. It is expected that the outcomes of this study will motivate institutions to identify and prioritize their future improvements in the patient safety context.

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“…Chen (2012) applied QFD for the healthcare industry to identify the priority of required improvements for service quality. Luo and Chang (2013) used the QFD method as a basis for safety process innovation in medical service industry. Kuo et al (2014) combined KANO and QFD as a planning tool to assess the relative importance of health food development.…”

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confidence: 99%

Determining the service demands of an aging population by integrating QFD and FMEA method

Chen¹

2014

Qual Quant

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Quality function deployment (QFD) techniques transform customer demands to service techniques, reducing design lead time and providing enhanced services to meet customer demands. A poor, aging service design exerts a negative effect on the quality of life of elderly people. Because government agencies have limited resources, improvement items cannot be implemented simultaneously. In this study, the risk priority number of failure mode and effect analysis (FMEA) was employed to determine improvement priorities for service demands. This methodology facilitates constructing a comprehensive Aging in Place policy and increases effective use of resources. The Aging in Place categories and policies are crucial. QFD and FMEA techniques were used in this study to design an Aging in Place policy and meet elderly people demands, provide a clear design, and improve service quality to match the demands and expectations of elderly people. The 16 service demands were identified by the experts and scholars. Six management techniques were obtained: education and training, space planning, medical facilities, human resources, transportation facilities, and recreational activities. According to the results, priority was as follows: (1) education and training; (2) space planning; (3) human resources.Keywords Aging in Place · Failure mode and effect analysis (FMEA) · House of quality · Quality function deployment (QFD) · Risk priority number (RPN) IntroductionCurrent progressions in medical science have decreased the risks of childbirth and lowered the mortality rate. The average global life expectancy has increased from 45 years of age to 75 years of age. Population aging has become a common global phenomenon. The World Health Organization (WHO) has indicated that a society with a population aged 65 and over

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Safety process innovation in medical service industry

Cited by 5 publications

References 19 publications

Developing a two-phase QFD for improving FMEA: an integrative approach

Developing a two-phase QFD for improving FMEA: an integrative approach

Prioritization of Medical Errors in Patient Safety Management: Framework Using Interval-Valued Intuitionistic Fuzzy Sets

Determining the service demands of an aging population by integrating QFD and FMEA method

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