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Analysing the Costs of Integrated Care: A Case on Model Selection for Chronic Care Purposes

BACKGROUND: The objective of this study is to investigate whether the algorithm proposed by Manning and Mullahy, a consolidated health economics procedure, can also be used to estimate individual costs for different groups of healthcare services in the context of integrated care. METHODS: A cross-se...

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Detalles Bibliográficos
Autores principales: Carreras, Marc, Sánchez-Pérez, Inma, Ibern, Pere, Coderch, Jordi, Inoriza, José María
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Ubiquity Press 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5354209/
https://www.ncbi.nlm.nih.gov/pubmed/28316542
http://dx.doi.org/10.5334/ijic.2422
Descripción
Sumario:BACKGROUND: The objective of this study is to investigate whether the algorithm proposed by Manning and Mullahy, a consolidated health economics procedure, can also be used to estimate individual costs for different groups of healthcare services in the context of integrated care. METHODS: A cross-sectional study focused on the population of the Baix Empordà (Catalonia-Spain) for the year 2012 (N = 92,498 individuals). A set of individual cost models as a function of sex, age and morbidity burden were adjusted and individual healthcare costs were calculated using a retrospective full-costing system. The individual morbidity burden was inferred using the Clinical Risk Groups (CRG) patient classification system. RESULTS: Depending on the characteristics of the data, and according to the algorithm criteria, the choice of model was a linear model on the log of costs or a generalized linear model with a log link. We checked for goodness of fit, accuracy, linear structure and heteroscedasticity for the models obtained. CONCLUSION: The proposed algorithm identified a set of suitable cost models for the distinct groups of services integrated care entails. The individual morbidity burden was found to be indispensable when allocating appropriate resources to targeted individuals.