Multiple regression model to analyze the total LOS for patients undergoing laparoscopic appendectomy.
Appendectomy
Length of stay
Multiple linear regression
Public health
Journal
BMC medical informatics and decision making
ISSN: 1472-6947
Titre abrégé: BMC Med Inform Decis Mak
Pays: England
ID NLM: 101088682
Informations de publication
Date de publication:
24 05 2022
24 05 2022
Historique:
received:
28
12
2021
accepted:
16
05
2022
entrez:
24
5
2022
pubmed:
25
5
2022
medline:
27
5
2022
Statut:
epublish
Résumé
The rapid growth in the complexity of services and stringent quality requirements present a challenge to all healthcare facilities, especially from an economic perspective. The goal is to implement different strategies that allows to enhance and obtain health processes closer to standards. The Length Of Stay (LOS) is a very useful parameter for the management of services within the hospital and is an index evaluated for the management of costs. In fact, a patient's LOS can be affected by a number of factors, including their particular condition, medical history, or medical needs. To reduce and better manage the LOS it is necessary to be able to predict this value. In this study, a predictive model was built for the total LOS of patients undergoing laparoscopic appendectomy, one of the most common emergency procedures. Demographic and clinical data of the 357 patients admitted at "San Giovanni di Dio e Ruggi d'Aragona" University Hospital of Salerno (Italy) had used as independent variable of the multiple linear regression model. The obtained model had an R This work designed an effective and automated strategy for improving the prediction of LOS, that can be useful for enhancing the preoperative pathways. In this way it is possible to characterize the demand and to be able to estimate a priori the occupation of the beds and other related hospital resources.
Sections du résumé
BACKGROUND
The rapid growth in the complexity of services and stringent quality requirements present a challenge to all healthcare facilities, especially from an economic perspective. The goal is to implement different strategies that allows to enhance and obtain health processes closer to standards. The Length Of Stay (LOS) is a very useful parameter for the management of services within the hospital and is an index evaluated for the management of costs. In fact, a patient's LOS can be affected by a number of factors, including their particular condition, medical history, or medical needs. To reduce and better manage the LOS it is necessary to be able to predict this value.
METHODS
In this study, a predictive model was built for the total LOS of patients undergoing laparoscopic appendectomy, one of the most common emergency procedures. Demographic and clinical data of the 357 patients admitted at "San Giovanni di Dio e Ruggi d'Aragona" University Hospital of Salerno (Italy) had used as independent variable of the multiple linear regression model.
RESULTS
The obtained model had an R
CONCLUSION
This work designed an effective and automated strategy for improving the prediction of LOS, that can be useful for enhancing the preoperative pathways. In this way it is possible to characterize the demand and to be able to estimate a priori the occupation of the beds and other related hospital resources.
Identifiants
pubmed: 35610697
doi: 10.1186/s12911-022-01884-9
pii: 10.1186/s12911-022-01884-9
pmc: PMC9131683
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
141Informations de copyright
© 2022. The Author(s).
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