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Identifying the long-term care beneficiaries: differences between risk factors of nursing homes and community-based services admissions

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Abstract

Background

The Portuguese long-term care sector is classified into home and community-based services (HCBS) and three nursing home (NH) units: convalescence, medium term and rehabilitation, and long term and maintenance.

Aims

To identify the main factors of admission into each care setting and explore to what extent these populations are different. 14,140 patients from NH and 6844 from HCBS were included from all over the country.

Methods

A logistic regression was estimated to identify determinants of admission into NH care, using sociodemographic characteristics, medical conditions and dependence levels at admission as independent variables, and region of care, referral entity and placement process as control variables. Then, ordered logistic regression was used to identify the contribution of the above factors in each specific NH unit.

Results

Being female, not being married, not having family/neighbour support, being literate, having mental illness, being cognitively or physically impaired are the main predictors of being admitted into a NH. Within the NH units, placements of the large majority of patients were accurately predicted, based on the available variables. However, for around half of the patients referred to long-term care units, the model expected placements into medium-term units, while for those admitted into short-stay units, the model returned that 29% could have benefited from being admitted into a medium-term care unit.

Discussion and conclusions

Patients’ accurate placement is a highly complex and challenging process, demanding more variables than the ones available for the model here presented. Our work confirms the need to collect other type of variables to improve the placement decision process.

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Acknowledgements

We want to acknowledge the Portuguese Central Administration of Health System for providing the information registered by the Integrated Bio-psychosocial Assessment Instrument. NR gratefully acknowledges financial support from FCT (Project CEMAPRE—UID/MULTI/00491/2013 financed by FCT/MCTES through national funds).

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Authors and Affiliations

  1. Escola Nacional de Saúde Pública, Universidade NOVA de Lisboa, Lisbon, Portugal

    Hugo Lopes

  2. Health Economics Group, Division of Health Research, Furness College, Lancaster University, Lancaster, LA1 4YG, UK

    Céu Mateus

  3. ISEG, University of Lisbon, and CEMAPRE, Rua do Quelhas 6, 1200-781, Lisbon, Portugal

    Nicoletta Rosati

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  1. Hugo Lopes
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  3. Nicoletta Rosati
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Correspondence to Hugo Lopes.

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There was no funding involved in this study, and none of the authors have any conflict of interest to declare.

Statement of human and animal rights

This article does not contain any experiments on human subjects or animal performed by any of the authors.

Ethical approval and Informed consent

We hereby inform that the manuscript meets all ethical standards and that at no point during the investigation were the authors able to univocally identify any patient, since all records were previously anonymized by the entity responsible for collecting all data, namely the Portuguese Central Administration of Health System.

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Lopes, H., Mateus, C. & Rosati, N. Identifying the long-term care beneficiaries: differences between risk factors of nursing homes and community-based services admissions. Aging Clin Exp Res 32, 2099–2110 (2020). https://doi.org/10.1007/s40520-019-01418-w

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  • DOI: https://doi.org/10.1007/s40520-019-01418-w

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