Length-of-Stay (LOS) Prediction Models Relieve Patient Overflow
No one likes to wait in the emergency department of a hospital, even when they aren’t sick. But when illness is involved, fast accessibility to healthcare can literally be critical—especially in an emergency.
That’s why Klarrio, in partnership with Monash University’s Dr Joanne Enticott and PhD Student Kushan Ranakombu, built length-of-stay (LOS) prediction models for Monash Health District. Models were designed to allow the hospital to accurately forecast Length of Stay in the emergency department, in addition to predicting subsequent hospital admission rates.
Build Length-of-Stay Prediction Systems to Improve Efficiency
The Technology behind
”“Don’t be afraid to give up the good to go for the great.”— John D. Rockefeller
The Monash Health District models can be leveraged and extended to build real-time dashboards that will give hospital administrators the ability to better plan resources.
Dashboards can provide hospital management with both historical and predictive views on the status of multiple admissions criteria in real time, in addition to accurate length-of-stay predictions to manage patient load more efficiently.
The ultimate goal is to maintain a high quality of care , both in the emergency room and hospital-wide, despite ongoing changes in technology and increasingly complex healthcare needs.
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