Estimating lifetime healthcare costs with morbidity data
dc.contributor.author
dc.date.accessioned
2024-01-29T16:31:42Z
dc.date.available
2024-01-29T16:31:42Z
dc.date.issued
2013-10-25
dc.identifier.issn
1472-6963
dc.identifier.uri
dc.description.abstract
Background: In many developed countries, the economic crisis started in 2008 producing a serious contraction of the financial resources spent on healthcare. Identifying which individuals will require more resources and the moment in their lives these resources have to be allocated becomes essential. It is well known that a small number of individuals with complex healthcare needs consume a high percentage of health expenditures. Conversely, little is known on how morbidity evolves throughout life. The aim of this study is to introduce a longitudinal perspective to chronic disease management. Methods: Data used relate to the population of the county of Baix Empordà in Catalonia for the period 2004-2007 (average population was N = 88,858). The database included individual information on morbidity, resource consumption, costs and activity records. The population was classified using the Clinical Risk Groups (CRG) model. Future morbidity evolution was simulated under different assumptions using a stationary Markov chain. We obtained morbidity patterns for the lifetime and the distribution function of the random variable lifetime costs. Individual information on acute episodes, chronic conditions and multimorbidity patterns were included in the model. Results: The probability of having a specific health status in the future (healthy, acute process or different combinations of chronic illness) and the distribution function of healthcare costs for the individual lifetime were obtained for the sample population. The mean lifetime cost for women was 111,936, a third higher than for men, at 81,566 (all amounts calculated in 2007 Euros). Healthy life expectancy at birth for females was 46.99, lower than for males (50.22). Females also spent 28.41 years of life suffering from some type of chronic disease, a longer period than men (21.9). Conclusions: Future morbidity and whole population costs can be reasonably predicted, combining stochastic microsimulation with a morbidity classification system. Potential ways of efficiency arose by introducing a time perspective to chronic disease management
dc.format.mimetype
application/pdf
dc.language.iso
eng
dc.publisher
BioMed Central
dc.relation.isformatof
Reproducció digital del document publicat a: https://doi.org/10.1186/1472-6963-13-440
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BMC Health Services Research, 2013, vol. 13, art.núm.440
dc.relation.ispartofseries
Articles publicats (D-EM)
dc.rights
Attribution 4.0 International (CC BY 4.0)
dc.rights.uri
dc.source
Carreras Pijuan, Marc Ibern, Pere Coderch, Jordi Sánchez Pérez, Inma Inoriza, José María 2013 Estimating lifetime healthcare costs with morbidity data BMC Health Services Research 13 art.núm.440
dc.title
Estimating lifetime healthcare costs with morbidity data
dc.type
info:eu-repo/semantics/article
dc.rights.accessRights
info:eu-repo/semantics/openAccess
dc.type.version
info:eu-repo/semantics/publishedVersion
dc.identifier.doi
dc.identifier.idgrec
038114
dc.type.peerreviewed
peer-reviewed
dc.identifier.eissn
1472-6963