Search

Objective To deal with the increasing long-term care (LTC) needs of elderly people in Taiwan, the government launched the Ten-year Long-term Care Project (TLTCP) in 2007, and through the care management system, care plans for those in need were distributed and implemented by care managers according to the single assessment process. Based on the emphasis of linking the right need assessment to the care plan, this study aimed to explore the need profiles of LTC recipients with regard to their health indicators to serve as a validity check on the identified dependency levels and care plans in the current care management system. Design A model based on latent class analysis (LCA) was used for dealing with the issue of health heterogeneity. LCA provides an empirical method that examines the interrelationships among health indicators and characterizes the underlying set of mutually exclusive latent classes that account for the observed indicators. The analysis included a total of 2901 elderly care recipients in the LTC dataset from a southern city, 1 of the 5 major metropolitan areas in Taiwan. The identified dependency levels of the samples and their care plans in need assessment were compared and discussed. Results Four need profiles were explored in the LTC dataset. Apart from the low (LD) (32.95%) and moderate dependent groups (MD) (17.48%), there were 2 groups identified among the high-dependency levels, including the severe physical and psychological dependency (SPP) (26.37%) and the comorbidities and severe dependency (CSD) groups (23.20%), which in sum were approximately identified as high dependency (HD) by care managers in the LTC dataset. In addition, the CSD group currently costs more for their care plans on average in LTC services (NT. 277,081.15, approximately 9200 USD) than the SPP group (NT. 244,084.21) and the other groups. Conclusion Need assessment is a key to success in care management in LTC. The results of this study showed the importance of focusing on multifacet indicators, especially the mental and social health indicators in need assessments by improving the unified assessment process to sensitively detect those with various needs and then link them to the right care plan. [ABSTRACT FROM AUTHOR]

Abstract: The health care needs of elderly people were influenced by their heterogeneity. This study aimed to identify the health latent classes of elderly people by using latent class analysis to deal with heterogeneity and examine their socio-demographic characteristics. Data came from the 2005 National Health Interview Survey (NHIS) in Taiwan. In total, 2449 elderly individuals with available health indicators were examined in latent class analysis (LCA), and 2217 elderly community-dwellings with complete socio-demographic data were analyzed by multinomial logistic regression. Four health latent classes were identified which included 1066 (43.5%) people in the High Comorbidity (HC), 152 (6.2%) in the Functional Impairment (FI), 252 (10.3%) in the Frail (FR), and 979 (40.0%) in the Relatively Healthy (RH) group. Multinomial logistic regressions revealed socio-demographic characteristics among health classes. The variables associated with an increased likelihood of being in the FR group were age, female, and living with families. They were also correlated to ethnicity and educations. Apart from age and gender, the Functional Impairment group was less likely to be ethnicity of Hakka, more likely to live with others than were the RH group. The HC group tended to be younger, with higher educations, and more likely to live in urban area than the Functional Impairment group. The correlations between health classes and socio-demographic factors were discussed. The health status of elderly people includes a variety of health indicators. A person-centered approach is critical to identify the health heterogeneity of elderly people and manage their care needs by targeting differential aging. [Copyright &y& Elsevier]