In this paper, we aim to identify the main predictors at admission and estimate patients’ length of care (LOC), within the framework of the Portuguese National Network for Long-Term Integrated Care, considering two care settings: (1) home and community-based services (HCBS) and (2) nursing home (NH) units comprising Short, Medium, or Long Stay Care. This study relied on a database of 20,984 Portuguese individuals who were admitted to the official long-term care (LTC) system and discharged during 2015. A generalised linear model (GLM) with gamma distribution was adjusted to HCBS and NH populations. Two sets of explanatory variables were used to model the random variable, LOC, namely, patient characteristics (age, gender, family/neighbour support, dependency levels at admission for locomotion, cognitive status, and activities of daily living [ADL]) and external factors (referral entity, number of beds/treatment places per 1,000 inhabitants ≥65 years of age), maturity and occupancy rate of the institution, and care setting. The features found to most influence the reduction of LOC are: male gender, having family/neighbour support, being referred by hospitals to NH (or by primary care to HCBS), and being admitted to units with a lower occupancy rate and with fewer months in operation. Regarding the dependency levels, as the number of ADL considered “dependent” increases, LOC also increases. As for the cognitive status, despite the opposite trend, it was only statistically significant for NH. Furthermore, two additional models were applied by including “death,” although this feature is not observable upon admission. By creating a model that allows for an estimate of the expected LOC for a new individual entering the Portuguese LTC system, policy-makers are able to estimate future costs and optimise resources.

Keywords:
Long-term care, Length of care, Dependency levels, Nursing homes, Home and community-based services, Portugal

Neste artigo, pretendemos identificar os principais preditores na admissão e estimar a duração de cuidados dos doentes (LOC) na Rede Nacional de Cuidados Continuados Integrados, considerando duas tipologias de cuidados: Cuidados Domiciliários (HCBS) e três Tipologias de Internamento (NH), nomeadamente Cuidados de Curta, Média e Longa duração. Este estudo assenta numa base de dados de 20.984 indivíduos com admissão e alta durante o ano de 2015, na Rede Nacional de Cuidados Continuados. Um modelo linear generalizado (GLM) com distribuição Gama foi ajustado para as populações HCBS e NH. Dois conjuntos de variáveis explicativas foram utilizados para modelar a variável aleatória LOC, nomeadamente, características do doente (idade, género, apoio familiar / vizinhos, níveis de dependência na admissão para locomoção, cognitivo e atividades da vida diária) e fatores externos (entidade referenciadora, número de camas / locais de tratamento por 1.000 habitantes com 65 ou mais anos), maturidade e taxa de ocupação da instituição, assim como a tipologia de cuidados. As características que mais influenciam a redução da LOC são o género masculino, ter apoio familiar / vizinhos, ser encaminhado por hospitais das NH (pelos cuidados primários nas HCBS), receber cuidados em unidades com menor taxa de ocupação e com menos meses de funcionamento. Em relação aos níveis de dependência, à medida que aumenta o número de atividades diárias consideradas “dependentes,” aumenta igualmente a LOC. Quanto ao estado cognitivo, apesar da tendência oposta, apenas se verificou estatisticamente significativo nas NH. Além do mais, dois modelos adicionais foram realizados incluindo a “morte,” embora esse recurso não seja observável na admissão. Ao criar um modelo que permite estimar a LOC esperada para um novo indivíduo que entra no sistema LTC português, os decisores políticos serão capazes de estimar os custos futuros e otimizar recursos.

Palavras Chave Cuidados continuados, Duração de cuidados, Níveis de dependência, Cuidados institucionalizados, Cuidados domiciliários, Portugal

Keywords:
Long-term care, Length of care, Dependency levels, Nursing homes, Home and community-based services, Portugal
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2021
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