Laparoscopic cholecystectomy (LC) interventions have had a great impact on health management and the effect has been evident in reducing the length of stay (LOS). This parameter is usually used as a performance indicator in order to measure the goodness of a health process. The prediction and control of this indicator is of considerable relevance for the management of hospital practice. In the following work the aim is to predict LOS for patients having LC surgery, using a linear model, at the University Hospital "San Giovanni di Dio and Ruggi d'Aragona"of Salerno (Italy) and at the A.O.R.N. "Antonio Cardarelli". Data were collected over two different years in order to compare the benefits of implementing some corrective actions introduced during the extracted time interval to increase the performance of the process under consideration. Linear regression models were implemented for each year and for each hospital. Obtained results show that in both hospitals a good predictive power of the models (R2= 0.84 and R2 = 0.97 and R2= 0.96 and R2 = 0.97 respectively).
A multiple regression model for modelling the hospital patients LOS' of laparoscopic cholecystectomy: a bicentric study
Santalucia I.;
2022-01-01
Abstract
Laparoscopic cholecystectomy (LC) interventions have had a great impact on health management and the effect has been evident in reducing the length of stay (LOS). This parameter is usually used as a performance indicator in order to measure the goodness of a health process. The prediction and control of this indicator is of considerable relevance for the management of hospital practice. In the following work the aim is to predict LOS for patients having LC surgery, using a linear model, at the University Hospital "San Giovanni di Dio and Ruggi d'Aragona"of Salerno (Italy) and at the A.O.R.N. "Antonio Cardarelli". Data were collected over two different years in order to compare the benefits of implementing some corrective actions introduced during the extracted time interval to increase the performance of the process under consideration. Linear regression models were implemented for each year and for each hospital. Obtained results show that in both hospitals a good predictive power of the models (R2= 0.84 and R2 = 0.97 and R2= 0.96 and R2 = 0.97 respectively).I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
