An intelligent case-based knowledge management system for quality improvement in nursing homes

Determinants of physical, psychological, and social well-being in older adults: a cross-sectional study in senior care facilities of Pakistan (2019/20)

BACKGROUND

Published research on senior care facilities in Pakistan is scarce and no large-scale study has been conducted to assess factors affecting well-being of older adults in these facilities. This study, therefore, investigated the effects of relocation autonomy, loneliness, and satisfaction with services along with socio-demographic characteristics on physical, psychological, and social well-being of older residents living in senior care facilities of Punjab, Pakistan.

METHODS

This cross-sectional study collected data from 270 older residents living in 18 senior care facilities across 11 districts of Punjab, Pakistan from November 2019 to February 2020 using multistage random sampling. Existing reliable and valid scales were used to collect information from older adults related to relocation autonomy (Perceived Control Measure Scale), loneliness (de Jong-Gierveld Loneliness Scale), satisfaction with service quality (Service Quality Scale), physical and psychological well-being (General Well-Being Scale), and social well-being (Duke Social Support Index). A psychometric analysis of these scales was carried out followed by three separate multiple regression analyses to predict physical, psychological, and social well-being from socio-demographic variables and key independent variables (relocation autonomy, loneliness, and satisfaction with service quality).

RESULTS

The results of multiple regression analyses showed that the models predicting physical (R² = 0.579), psychological (R² = 0.654), and social well-being (R² = 0.615) were statistically significant (p < 0.001). Number of visitors was a significant predictor of physical (b = 0.82, p = 0.01), psychological (b = 0.80, p < 0.001), and social (b = 2.40, p < 0.001) well-being. Loneliness significantly predicted physical (b = -0.14, p = 0.005), psychological (b = -0.19, p < 0.001), and social (b = -0.36, p < 0.001) well-being. Control over relocation process significantly predicted physical (b = 0.56, p < 0.001) and psychological (b = 0.36, p < 0.001) well-being. Satisfaction with services significantly predicted physical (b = 0.07, p < 0.001) and social (b = 0.08, p < 0.001) well-being.

CONCLUSION

Pragmatic, equitable and cost-effective interventions are needed to improve the wellbeing of older residents living in senior care facilities. Friendly behavior of mobilizing staff and adjusted residents to facilitate new residents, therapeutic interventions such as relocation support programs, reminiscence therapy and intergenerational support, and increasing their exposure and connection to the outside world, can raise their physical, psychological, and social well-being.

A case-based reasoning system for neonatal survival and LOS prediction in neonatal intensive care units: a development and validation study

Early prediction of neonates' survival and Length of Stay (LOS) in Neonatal Intensive Care Units (NICU) is effective in decision-making. We developed an intelligent system to predict neonatal survival and LOS using the "Case-Based Reasoning" (CBR) method. We developed a web-based CBR system based on K-Nearest Neighborhood (KNN) on 1682 neonates and 17 variables for mortality and 13 variables for LOS and evaluated the system with 336 retrospectively collected data. We implemented the system in a NICU to externally validate the system and evaluate the system prediction acceptability and usability. Our internal validation on the balanced case base showed high accuracy (97.02%), and F-score (0.984) for survival prediction. The root Mean Square Error (RMSE) for LOS was 4.78 days. External validation on the balanced case base indicated high accuracy (98.91%), and F-score (0.993) to predict survival. RMSE for LOS was 3.27 days. Usability evaluation showed that more than half of the issues identified were related to appearance and rated as a low priority to be fixed. Acceptability assessment showed a high acceptance and confidence in responses. The usability score (80.71) indicated high system usability for neonatologists. This system is available at http://neonatalcdss.ir/ . Positive results of our system in terms of performance, acceptability, and usability indicated this system can be used to improve neonatal care.

A Two-Echelon Responsive Health Analytic Model for Triggering Care Plan Revision in Geriatric Care Management

Due to the increasing ageing population, how can caregivers effectively provide long-term care services to meet the older adults’ needs with finite resources is emerging. In addressing this issue, nursing homes are striving to adopt smart health with the internet of things and artificial intelligence to improve the efficiency and sustainability of healthcare. This study proposed a two-echelon responsive health analytic model (EHAM) to deliver appropriate healthcare services in nursing homes under the Internet of Medical Things environment. A novel care plan revision index is developed using a dual fuzzy logic approach for multidimensional health assessments, followed by care plan modification using case-based reasoning. The findings reveal that EHAM can generate patient-centred long-term care solutions of high quality to maximise the satisfaction of nursing home residents and their families. Ultimately, sustainable healthcare services can be within the communities.

The role of cloud computing in knowledge management for small and medium enterprises: a systematic literature review

Purpose

Knowledge management (KM) is widely adopted by organisations to improve their performance and make informed decisions. Prior research has confirmed that Information Systems (IS) play a critical role in effective KM. The purpose of this study is to examine the existing literature on the role of cloud-based KM systems (C-KMS) in small- and medium-sized enterprise (SMEs) by understanding its impact on the five KM processes: knowledge acquisition, creation, storage, sharing and usage.

Design/methodology/approach

This study conducted a systematic literature review by examining 133 journal articles and 24 conference papers from 2010 to 2021 on the role of cloud computing in KM for SMEs.

Findings

This study revealed that there are numerous empirical analyses on KM processes and tools in SMEs; however, only few studies demonstrate how the whole gamut of KM processes can adopt cloud computing in SMEs. Therefore, SMEs are ineffective at KM with limited IS intervention. This paper offers a proposition on how C-KMS can impact all five KM process, thereby increasing its effectiveness of KM in SMEs. This study analysed the benefits of C-KMS that brings to SMEs in terms of availability, scalability, reliability, security and cost.

Research limitations/implications

This systematic review is restricted to certain databases (ScienceDirect, Sage journals, Scopus and Emerald Insight) and specific IS conference proceedings to source articles. The selection of search criteria and time frame is based on this study’s assessment and choice. This study adds value to our understanding of the role of KM in SMEs, and it reinforces the role of cloud computing in effectively managing knowledge in SMEs. The proposal of C-KMS for the enhancement of KM has significant implications for SMEs to effectively use knowledge for their survival and superior performance.

Practical implications

This study suggests three practical implications. First, adopting and using C-KMS provide a strong foundation to manage knowledge for SMEs in a cost-effective way. Second, C-KMS improves the effectiveness of KM by increasing availability of knowledge artifacts, which in turn aids SMEs’ growth. Third, C-KMS is useful to codify SME’s knowledge, and accordingly supports employees to acquire and use knowledge based on their requirements.

Social implications

This study discussed C-KMS with contemporary social issues, such as the COVID-19 pandemic challenges for SMEs and demonstrated how C-KMS can support SMEs to handle such crises by managing knowledge effectively.

Originality/value

This research highlights the importance of the implementation of a C-KMS for the enhancement of KM in SMEs. The review provides empirical evidence on the challenges faced by SMEs regarding KM, as they often only have enough resources to focus on a single KM process, predominantly knowledge sharing. Consequently, a holistic approach to KM cannot be realised by SMEs. In this context, the findings of this study offer theoretical and practical insights into the role of cloud computing by addressing the challenges of KM in SMEs.

Identification and Evaluation of Factors Influencing the Quality of Elderly Services Supply Chain Based on DEMATEL-ISM-TOPSIS Method

With the intensification of aging, the importance of the elderly care service supply chain is gradually being recognized by people. A systematic analysis of the quality of elderly care services from the perspective of the supply chain will help provide decision-making reference for improving the quality of elderly care services. The evaluation index system of elderly care services` quality is constructed from the perspective of the integrated SCOR model. The integrated DEMATEL-ISM-TOPSIS method is proposed for evaluation and analysis. The research pointed out the surface and deep influencing factors as well as the weight of each evaluation factor of the elderly care services` quality. The interpretative structure model was constructed to point out the hierarchical relationship and the principal-subordinate logical relationship of each evaluation factor. The weight of the quality factors of elderly care services was obtained, and the applicability of the model and method was verified by an evaluation case of elderly service institutions.