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  • 1
    Online Resource
    Online Resource
    Emerald ; 2018
    In:  VINE Journal of Information and Knowledge Management Systems Vol. 48, No. 1 ( 2018-02-12), p. 103-121
    In: VINE Journal of Information and Knowledge Management Systems, Emerald, Vol. 48, No. 1 ( 2018-02-12), p. 103-121
    Abstract: This paper aims to maintain the high service quality of the long-term care service providers by establishing a knowledge-based system so as to enhance the service quality of nursing homes and the performance of its nursing staff continually. Design/methodology/approach An intelligent case-based knowledge management system (ICKMS) is developed with the integration of two artificial intelligence techniques, i.e. fuzzy logic and case-based reasoning (CBR). In the system, fuzzy logic is adopted to assess the performance through the analysis of the long-term care services provided, nurse performance and elderly satisfaction, whereas CBR is used to formulate a customized re-training program for quality improvement. A case study is conducted to validate the feasibility of the proposed system. Findings The empirical findings indicate that the ICKMS helps in identification of those nursing staff who cannot meet the essential service standard. Through the customized re-training program, the performance of the nursing staff can be greatly enhanced, whereas the medical errors and complaints can be considerably reduced. Furthermore, the proposed methodology provides a cost-saving approach in the administrative work. Practical implications The findings and results of the study facilitate decision-making using the ICKMS for the long-term service providers to improve their performance and service quality by providing a customized re-training program to the nursing staff. Originality/value This study contributes to establishing a knowledge-based system for the long-term service providers for maintaining the high service quality in the health-care industry.
    Type of Medium: Online Resource
    ISSN: 2059-5891
    Language: English
    Publisher: Emerald
    Publication Date: 2018
    detail.hit.zdb_id: 2862559-6
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  • 2
    In: Expert Systems, Wiley, Vol. 36, No. 2 ( 2019-04)
    Abstract: With the increasing ageing population worldwide, providing effective nursing care planning in nursing homes is important in meeting the expectations of elderly patients and in streamlining the healthcare information process, hence maintaining high‐quality services. Instead of the traditional manual nursing care planning formulation based on expert experience and subjective judgement, this paper describes an adaptive decision support system, namely, the cloud‐based nursing care planning system, to enable decision making in formulating nursing care strategies. By integrating cloud computing technology and the case‐based reasoning (CBR) technique, medical records and documents pertaining to the elderly can be captured in real time, whereas appropriate treatment plans based on past similar treatment records can be formulated. However, the current case adaptation processes in CBR rely on domain experts to modify retrieved cases, which may not satisfy the needs of the elderly. Therefore, text mining is integrated in the case adaptation process of CBR for extracting up‐to‐date medical information from the Internet so that its efficiency can be improved. By conducting a pilot study in a nursing home, it was shown that the time for formulating applicable treatment plans for elderly patients can be reduced, and the service satisfaction level can be enhanced.
    Type of Medium: Online Resource
    ISSN: 0266-4720 , 1468-0394
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2019
    detail.hit.zdb_id: 284011-X
    detail.hit.zdb_id: 283676-2
    detail.hit.zdb_id: 2016958-9
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