Bayesian Analysis and Prediction of Patients’ Demands for Visits in Home Care
| Autor: | Raffaele Argiento, Alessandra Guglielmi, Inad Nawajah, Ettore Lanzarone |
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| Rok vydání: | 2013 |
| Předmět: |
Development Demands
business.industry Service delivery framework Bayesian probability Settore ING-IND/34 - Bioingegneria Industriale Social Welfare Demand evolution Bayesian inference medicine.disease Future Planning Horizon Service delivery Social service Complex structure Settore MAT/06 - Probabilita' e Statistica Matematica Unplanned Changes Bayesian model Patients' conditions Bayesian Model Complete Modeling Approach Medicine Bayesian Analysis In patient Medical emergency Prediction errors business |
| Zdroj: | Springer Proceedings in Mathematics & Statistics ISBN: 9783319020839 The first Bayesian Young Statisticians Meeting, BAYSM 2013, pp. 129–133, Milano, 5/6 giugno 2013 info:cnr-pdr/source/autori:R. Argiento, A. Guglielmi, E. Lanzarone, and I. Nawajah/congresso_nome:The first Bayesian Young Statisticians Meeting, BAYSM 2013/congresso_luogo:Milano/congresso_data:5%2F6 giugno 2013/anno:2014/pagina_da:129/pagina_a:133/intervallo_pagine:129–133 |
| DOI: | 10.1007/978-3-319-02084-6_25 |
| Popis: | Home care (HC) providers are complex structures which include medical, paramedical, and social services delivered to patients at their domicile. High randomness affects the service delivery, mainly in terms of unplanned changes in patients' conditions, which make the amount of required visits highly uncertain. In this paper, we propose a Bayesian model to represent the HC patient's demand evolution over time and to predict the demand in future periods. Results from the application to a relevant real case validate the approach, since low prediction errors are found. |
| Databáze: | OpenAIRE |
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