Abstract
The ageing population has been a severe problem in the world. With the increasing aged population problem, society would face challenges in different dimensions, especially to the healthcare industry or healthcare system of a country. The demand for long-term care services would rise due to chronic diseases and physical deterioration among older people. A Long-term Care Plan 2.0 (LTCP 2.0) is suggested by Taiwan Government to solve the problem. They divide older people by region and age to reallocate the community care service to utilize community care service. The case-based reasoning (CBR) approach is suggested to use in the care plan formulation at LTCP 2.0. This chapter aims to identify key factors for care plan formulation, develop an intelligent decision support system for determining the level of care and formulating care plans using CBR, and set up a rating scheme for improving the quality of cases stored in the CBR library. An intelligent care planning system (ICPS) is constructed and implemented at an integrated community service centre located in Taiwan to achieve the defined objectives. The results show that the ICPS has improved care plan formulation, plan satisfaction and service satisfaction in the plan.
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References
Feng, Z. (2019). Global convergence: Aging and long-term care policy challenges in the developing world. Journal of Aging & Social Policy, 31(4), 291–297.
Kaplan, M. A., & Inguanzo, M. M. (2017). The social, economic, and public health consequences of global population aging: Implications for social work practice and public policy. Journal of Social Work in the Global Community, 2(1), 1–12.
Galiana, J., & Haseltine, W. A. (2019). Healthcare in the United States. In Aging Well (pp. 7–18). Palgrave Macmillan, Singapore.
Colombo, B., Antonietti, A., & Daneau, B. (2018). The relationships between cognitive reserve and creativity. A study on American aging population. Frontiers in psychology, 9, 764.
Storms, H., Marquet, K., Aertgeerts, B., & Claes, N. (2017). Prevalence of inappropriate medication use in residential long-term care facilities for the elderly: A systematic review. European Journal of General Practice, 23(1), 69–77.
Kyaw, K. T. (2019, November). Prediction of Long-term Care Utilization by Functional Status in the United States Aging population between 2008 to 2016. In APHA's 2019 Annual Meeting and Expo (Nov. 2-Nov. 6). American Public Health Association.
D’Adamo, H., Yoshikawa, T., & Ouslander, J. G. (2020). Coronavirus disease 2019 in geriatrics and long-term care: The ABCDs of COVID-19. Journal of the American Geriatrics Society, 68(5), 912–917.
Murphy, A., Kowal, P., Albertini, M., Rechel, B., Chatterji, S., & Hanson, K. (2018). Family transfers and long-term care: An analysis of the WHO Study on global AGEing and adult health (SAGE). The Journal of the Economics of Ageing, 12, 195–201.
Yeh, M. J. (2020). Long-term care system in Taiwan: The 2017 major reform and its challenges. Ageing & Society, 40(6), 1334–1351.
Hsu, H. C., & Chen, C. F. (2019). LTC 2.0: The 2017 reform of home-and community-based long-term care in Taiwan. Health Policy, 123(10), 912–916.
Chen, S. H., Pai, F. Y., & Yeh, T. M. (2020). Using the importance-satisfaction model and service quality performance matrix to improve long-term care service quality in Taiwan. Applied Sciences, 10(1), 85.
Aamodt, A., & Plaza, E. (1994). Case-based reasoning: Foundational issues, methodological variations, and system approaches. AI communications, 7(1), 39–59.
Kolodner, J. (2014). Case-based reasoning. Morgan Kaufmann.
Tang, V., Choy, K. L., Ho, G. T. S., Lam, H. Y., & Tsang, Y. P. (2019). An IoMT-based geriatric care management system for achieving smart health in nursing homes. Industrial Management & Data Systems.
Tang, V., Siu, P. K. Y., Choy, K. L., Lam, H. Y., Ho, G. T. S., Lee, C. K. M., & Tsang, Y. P. (2019). An adaptive clinical decision support system for serving the elderly with chronic diseases in healthcare industry. Expert Systems, 36(2), e12369.
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WU, C.H., LAM, C.H.Y., XHAFA, F., TANG, V., IP, W.H. (2022). Case Study in Elderly Consultancy Services. In: Wu, C., Lam, C.H., Xhafa, F., Tang, V., Ip, W. (eds) IoT for Elderly, Aging and eHealth. Lecture Notes on Data Engineering and Communications Technologies, vol 108. Springer, Cham. https://doi.org/10.1007/978-3-030-93387-6_9
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DOI: https://doi.org/10.1007/978-3-030-93387-6_9
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