Home Care (HC) service is an alternative to conventional hospitalization and consists of delivering medical, paramedical and social services to patients at their homes rather than in hospitals or nursing homes. Human resource planning in HC is a difficult task and, for a good quality of planning, knowledge of future patients’ demands is required. The aim of this paper is to propose a Bayesian model for predicting the number of visits required by HC patients, which is fundamental for planning human and material resources, and at the same time describing the natural history of Care Profiles. We model patients’ holding times, i.e., the duration of Care Profiles, and the number of nurses’ visits at each future time slot. The model has been applied to the real data of one of the largest public HC providers in Italy. We computed the estimates of all model parameters and the predictions for both new patients and patients already in the charge. Preliminary results show the applicability of the approach in the practice and good quality of predictions.
(2014). Joint Prediction of Demand and Care Duration in Home Care Patients: a Bayesian Approach / Previsione Congiunta della Domanda e della Durata di Cura in Assistenza Domiciliare: un Approccio Bayesiano . Retrieved from http://hdl.handle.net/10446/193141
Joint Prediction of Demand and Care Duration in Home Care Patients: a Bayesian Approach / Previsione Congiunta della Domanda e della Durata di Cura in Assistenza Domiciliare: un Approccio Bayesiano
Argiento, Raffaele;Lanzarone, Ettore
2014-01-01
Abstract
Home Care (HC) service is an alternative to conventional hospitalization and consists of delivering medical, paramedical and social services to patients at their homes rather than in hospitals or nursing homes. Human resource planning in HC is a difficult task and, for a good quality of planning, knowledge of future patients’ demands is required. The aim of this paper is to propose a Bayesian model for predicting the number of visits required by HC patients, which is fundamental for planning human and material resources, and at the same time describing the natural history of Care Profiles. We model patients’ holding times, i.e., the duration of Care Profiles, and the number of nurses’ visits at each future time slot. The model has been applied to the real data of one of the largest public HC providers in Italy. We computed the estimates of all model parameters and the predictions for both new patients and patients already in the charge. Preliminary results show the applicability of the approach in the practice and good quality of predictions.File | Dimensione del file | Formato | |
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