Dementia, a progressive condition with a higher incidence in the elderly, has become an emerging issue for public health. This is because, in addition to functional and social damage, it is responsible for one of the greatest costs for society as a whole. Hospital episodes, such as frequent trips to the emergency room, transitions to more complex care, as well as recurrent and prolonged hospitalizations, are the main factors that justify such a high cost, and especially at the end of life, they represent indicators of poor quality of care. However, there is still a gap in the literature regarding the factors associated with a higher risk for such indicators at the end of life. In view of this scenario, the present project aims to verify which factors are associated with hospital outcomes that portray a lower quality of care at the end of life in people with dementia, aged 60 years or more, over a four-year follow-up period, prior to the date of death of the participants. To answer this research question, data from the English Longitudinal Study of Aging (ELSA Study) will be used. Such data are made available to the Grupo de Estudos em Epidemiologia e Envelhecimento (GEPEN), thanks to the International Collaboration of Longitudinal Studies of Aging (InterCoLAging), a consortium of Longitudinal Studies led by the supervisor of this proposal, funded by CNPq, and headquartered at the Department of Gerontology from UFSCar where this study will be carried out. In this proposal, a retrospective longitudinal study will be carried out, which will include a subsample of individuals participating in the ELSA Study with a diagnosis of dementia. Such data will be linked to English mortality data and the English Hospital Episode Statistics (HES) registry which will allow such retrospective analyses. The analyzed hospital outcomes will be the presence of transition to more complex care, recurrent hospitalizations, represented continuously by the number of episodes in critical care, that is, patients who were hospitalized in intensive care units, and the length of stay of the critical care patient, calculated in days from admission to discharge or referral. Socioeconomic factors, life habits, clinical, sensory, anthropometric, functional conditions and characteristics of hospital admissions will be analyzed as exposure. To verify the intended association, a logistic regression model will be performed for the outcome of care transition, and linear regression models for the outcomes of number of episodes and length of stay in critical care. By understanding the factors associated with hospital outcomes at the end of life, this project aims to contribute to the development of effective health care models, so that strategies and interventions are directed towards improving the quality of care and preventing avoidable hospitalizations.
News published in Agência FAPESP Newsletter about the scholarship: