A care pathway is defined as a complex intervention for the organisation of care processes for a specific group of patients during a specific period. Although the analysis of care pathways has been shown its benefits in clinical practices, little attention has been devoted to study how it can contribute to the optimization of the use of resources. In particular here we focus on the analysis of the history of a large number of patients' admissions, i.e. of data that belong to the routine flow of information that all hospital provide to the Local Healthcare Agency. One goal is the identification of the most likely sequence of wards/clinics for a patient; in fact, knowing which wards/clinics are more interrelated can be useful for a better hospital organization. Moreover we suggest the use of Bayesian Networks to predict the care pathway that each patient will undertake, given his/her history.

Conigliani, C., Petitti, T., Vitale, V. (2020). Bayesian networks for the analysis of inpatient admissions. STATISTICA APPLICATA, 32(2), 141-160.

Bayesian networks for the analysis of inpatient admissions

Caterina Conigliani
;
Vincenzina Vitale
2020-01-01

Abstract

A care pathway is defined as a complex intervention for the organisation of care processes for a specific group of patients during a specific period. Although the analysis of care pathways has been shown its benefits in clinical practices, little attention has been devoted to study how it can contribute to the optimization of the use of resources. In particular here we focus on the analysis of the history of a large number of patients' admissions, i.e. of data that belong to the routine flow of information that all hospital provide to the Local Healthcare Agency. One goal is the identification of the most likely sequence of wards/clinics for a patient; in fact, knowing which wards/clinics are more interrelated can be useful for a better hospital organization. Moreover we suggest the use of Bayesian Networks to predict the care pathway that each patient will undertake, given his/her history.
2020
Conigliani, C., Petitti, T., Vitale, V. (2020). Bayesian networks for the analysis of inpatient admissions. STATISTICA APPLICATA, 32(2), 141-160.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11590/363408
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