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.

Multiple regression model to analyze the total LOS for patients undergoing laparoscopic appendectomy / Trunfio, Teresa Angela; Scala, Arianna; Giglio, Cristiana; Rossi, Giovanni; Borrelli, Anna; Romano, Maria; Improta, Giovanni. - In: BMC MEDICAL INFORMATICS AND DECISION MAKING. - ISSN 1472-6947. - 22:1(2022), p. 141. [10.1186/s12911-022-01884-9]

Multiple regression model to analyze the total LOS for patients undergoing laparoscopic appendectomy

Trunfio, Teresa Angela;Scala, Arianna
;
Romano, Maria;Improta, Giovanni
2022

Abstract

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.
2022
Multiple regression model to analyze the total LOS for patients undergoing laparoscopic appendectomy / Trunfio, Teresa Angela; Scala, Arianna; Giglio, Cristiana; Rossi, Giovanni; Borrelli, Anna; Romano, Maria; Improta, Giovanni. - In: BMC MEDICAL INFORMATICS AND DECISION MAKING. - ISSN 1472-6947. - 22:1(2022), p. 141. [10.1186/s12911-022-01884-9]
File in questo prodotto:
File Dimensione Formato  
s12911-022-01884-9.pdf

accesso aperto

Tipologia: Versione Editoriale (PDF)
Licenza: Non specificato
Dimensione 1.19 MB
Formato Adobe PDF
1.19 MB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/891564
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 36
  • ???jsp.display-item.citation.isi??? 8
social impact