Healthcare.Blueprint-Predicting Length of Stay in Hospitals
This solution enables a predictive model for Length of Stay for in-hospital admissions.
This experiment is part of the larger Healthcare Blueprint deployed automatically to your Azure Machine Learning Workspace. Please refer to the blog and documentation for more details.
The solution enables a predictive model for Length of Stay for in-hospital admissions. Length of Stay (LOS) is defined in number of days from the initial admit date to the date that the patient is discharged from any given hospital facility. There can be significant variation of LOS across various facilities and across disease conditions and specialties even within the same healthcare system. Advanced LOS prediction at the time of admission can greatly enhance the quality of care as well as operational workload efficiency and help with accurate planning for discharges resulting in lowering of various other quality measures such as readmissions.