An intelligent case-based knowledge management system for quality improvement in nursing homes
| Pages | 103-121 |
| Published date | 12 February 2018 |
| DOI | https://doi.org/10.1108/VJIKMS-01-2017-0001 |
| Date | 12 February 2018 |
| Author | King Lun Tommy Choy,Kai Yuet Paul Siu,To Sum George Ho,C.H. Wu,Hoi Yan Lam,Valerie Tang,Yung Po Tsang |
| Subject Matter | Information & knowledge management,Knowledge management,Knowledge management systems |
An intelligent case-based
knowledge management system
for quality improvement in
nursing homes
King Lun Tommy Choy
Department of Industrial and Systems Engineering,
The Hong Kong Polytechnic University, Hung Hom, Hong Kong
Kai Yuet Paul Siu
Comfort Nursing Home, Taichung, Taiwan
To Sum George Ho
Department of Industrial and Systems Engineering,
The Hong Kong Polytechnic University, Hong Kong
C.H. Wu
Department of Supply Chain and Information Management,
Hang Seng Management College, Shatin, Hong Kong and
Department of Industrial and Systems Engineering,
The Hong Kong Polytechnic University, Hong Kong, and
Hoi Yan Lam,Valerie Tang and Yung Po Tsang
Department of Industrial and Systems Engineering,
The Hong Kong Polytechnic University, Hong Kong
Abstract
Purpose –This paper aims to maintain the high servicequality 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
performanceof its nursing staff continually.
Design/methodology/approach –An intelligent case-based knowledge managementsystem (ICKMS)
is developed with the integration of two artificial intelligence techniques, i.e. fuzzy logic and case-based
reasoning (CBR). In the system, fuzzylogic 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 feasibilityof the proposed system.
Findings –The empiricalfindings indicate that the ICKMS helps in identification of those nursing staffwho
cannot meet the essential servicestandard. Through the customized re-training program, the performanceof
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.
The authors would like to thank the Research Office of the Hong Kong Polytechnic University for
supporting the current project (Project Code: G-UA7Z).
Quality
improvement
in nursing
homes
103
Received24 January 2017
Revised24 July 2017
Accepted30 August 2017
VINEJournal of Information and
KnowledgeManagement Systems
Vol.48 No. 1, 2018
pp. 103-121
© Emerald Publishing Limited
2059-5891
DOI 10.1108/VJIKMS-01-2017-0001
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/2059-5891.htm
Practical implications –The findings and results of the study facilitate decision-making using the
ICKMS for the long-term serviceproviders to improve their performance and service quality by providinga
customizedre-training program to the nursing staff.
Originality/value –This study contributes to establishing a knowledge-based systemfor the long-term
serviceproviders for maintaining the high service quality in the health-careindustry.
Keywords Quality improvement, Knowledge management system, Long-term care services
Paper type Research paper
Introduction
The increasing ageing population is an unavoidable challenge for the health-care industry all
over the world, including Hong Kong (Crimmins and Levine, 2016). According to the Hong
Kong Census and Statistics Department, the proportion of the elderly people aged 65 and over
is projected to rise markedly, from 15 per centin2014to36percentin2064.Becauseofthis
increasing ageing population in Hong Kong, the need for public health-care services is expected
to increase continuously (Hui and Yu, 2009). To relieve the pressure on the public health
services, long-term care service providers, such as nursing homes and elderly centers, have
been introduced to provide support and reduce hospitalization of the elderly (Ouslander and
Berenson, 2011;Onder et al.,2012). In nursing homes, nurses and assistants have to perform
direct care activities (i.e. feeding, daily health checks and bathing), medication administration
(i.e. medicine preparation and documentation), indirect care activities (i.e. cleaning, stock
replenishment and equipment setup) and communication activities (Munyisia et al., 2011;
Thomson et al., 2009). Most of these activities have complicated procedures which require
professional knowledge and experience to undertake so as to provide effective treatment to the
elderly (Saxer et al.,2008;Wardh et al., 2012). However, because of the high turnover rate in the
health-care industry, there is a shortage of knowledgeable manpower such that quality services
cannot be guaranteed. According to Barry et al. (2012), the knowledge and attitude of nursing
assistants are critical factors in managing the quality of life for the elderly. Without appropriate
education and training provided to nursing home front-line assistants, the needs of the patients
are not recognized or barely detected by nursing assistants, hence no treatment can be provided
(Glaister and Blair, 2008;Skar, 2010). Moreover, theoretical studies have mainly focused on
examining the key indicators for measuring the quality of nursing homes. Research works
related to the design of systematic approaches and procedures based on relevant knowledge
that is applicable for assessing the performance of the nursing staff are limited. To tackle such
problems, an intelligent case-based knowledge management system (ICKMS) is designed to
improve the performance and service quality in nursing homes. By integrating the fuzzy logic
and the case-based reasoning (CBR) techniques, the performance of nursing assistants can be
measured systematically, whereas customized re-training programs for quality improvement
can be formulated based on previous experience and knowledge. The remainder of this paper is
organized as follows. Section 2 reviews the past literature concerning the current situation of
the ageing population, quality management in nursing homes and artificial intelligence (AI)
techniques for quality improvement. Section 3 presents the design of the ICKMS. Section 4
shows a case study to validate the feasibility of the proposed system. Section 5 provides the
results and discussion of the ICKMS. Section 6 gives the conclusions.
Literature review
Current challenges in the nursing industry
Because of the rapidly aging population all over the world,the need for nursing homes has
significantly increased. An overall health-care system is usually adopted in nursing homes
VJIKMS
48,1
104
To continue reading
Request your trial