Key result
A machine learning approach was developed and assessed to predict hospital length of stay using data from over 3000 cases of kidney surgery.
Why the study?
Predicting hospital length of stay is crucial for optimizing patient management and clinical operations in patients undergoing kidney surgery.
Can a machine learning approach predict hospital length of stay in patients undergoing kidney surgery?
Observational (n=3,000)
No
Can a machine learning approach predict hospital length of stay in patients undergoing kidney surgery?
Machine learning models can be used to predict hospital length of stay for patients undergoing kidney surgery, potentially optimizing patient management and clinical operations.
ML models feasible for LOS prediction after kidney surgery; hypothesis-generating and requires prospective validation before use.
The analysis of the hospital length of stay could provide a new perspective in the design of strategies to optimize the patients’ management, the clinical operations, and, not least, improve the overall healthcare service quality perceived by both patients, healthcare staff, and healthcare administrators and decision-makers. In the case of kidney injuries, the possibility to predict the length of stay is crucial for ensuring proper management of the patients undergoing surgical interventions. It is therefore significant for clinicians to have the option to anticipate the length of stay of patients and to deal with the main features influencing it to decrease the hospital length of stay. In this work we center around patients undergoing kidney surgery. Information was gathered from more than 3000 cases of kidney surgeries at the national hospital "A.O.R.N. Antonio Cardarelli" of Naples. A machine learning approach has been proposed to classify and predict the LOS of patients undergoing kidney surgery, and the tested algorithms have been assessed and compared in terms of performance metrics. Best predictive models have been identified and described in view of their potential impact in the improvement of the kidney surgery management procedures.
No takes yet. Share an insight, caveat, or question.
Marino et al. (2022) conducted an observational in Kidney surgery (n=3,000). Machine learning predictive models was evaluated on Hospital length of stay (LOS). A machine learning approach was developed and assessed to predict hospital length of stay using data from over 3000 cases of kidney surgery.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: