The length of stay (LOS) in hospital is one of the main parameters for evaluating the management of a health facility, of its departments in relation to the different specializations. Healthcare costs are in fact closely linked to this parameter as well as the profit margin. In the orthopedic field, the provision of this parameter is increasingly complex and of fundamental importance in order to be able to evaluate the planning of resources, the waiting times for any scheduled interventions and the management of the department and related surgical interventions. The purpose of this work is to predict and evaluate the LOS value using machine learning methods and applying multiple linear regression, starting from clinical data of patients hospitalized with lower limb fractures. The data were collected at the "San Giovanni di Dio e Ruggi d’Aragona" hospital in Salerno (Italy).

Predictive analysis of lower limb fractures in the orthopedic complex operative unit using artificial intelligence: the case study of AOU Ruggi / Scala, A.; Borrelli, A.; Improta, G.. - In: SCIENTIFIC REPORTS. - ISSN 2045-2322. - 12:1(2022), p. 22153. [10.1038/s41598-022-26667-0]

Predictive analysis of lower limb fractures in the orthopedic complex operative unit using artificial intelligence: the case study of AOU Ruggi

Scala A.
;
Improta G.
2022

Abstract

The length of stay (LOS) in hospital is one of the main parameters for evaluating the management of a health facility, of its departments in relation to the different specializations. Healthcare costs are in fact closely linked to this parameter as well as the profit margin. In the orthopedic field, the provision of this parameter is increasingly complex and of fundamental importance in order to be able to evaluate the planning of resources, the waiting times for any scheduled interventions and the management of the department and related surgical interventions. The purpose of this work is to predict and evaluate the LOS value using machine learning methods and applying multiple linear regression, starting from clinical data of patients hospitalized with lower limb fractures. The data were collected at the "San Giovanni di Dio e Ruggi d’Aragona" hospital in Salerno (Italy).
2022
Predictive analysis of lower limb fractures in the orthopedic complex operative unit using artificial intelligence: the case study of AOU Ruggi / Scala, A.; Borrelli, A.; Improta, G.. - In: SCIENTIFIC REPORTS. - ISSN 2045-2322. - 12:1(2022), p. 22153. [10.1038/s41598-022-26667-0]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/919668
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