11:30am - 12:30pm Wednesday, March 11

Location & Room

Orlando - Orange County Convention Center
W230A
Analysis of charge data from Ascension’s hospitals indicates that substantial opportunity exists to standardize clinical practice and length of stay (LOS) for our admitted patients. This session will discuss how Ascension data scientists and clinical analysts created and implemented a machine learning model leveraging internal administrative billing data to develop an “expected” LOS for each patient, thus better identifying areas of clinical opportunity than previous methods using the Center for Medicare and Medicaid Services (CMS) geometric mean LOS (GMLOS) for each diagnosis related group (DRG). Our results show that machine learning performs significantly better than the CMS GMLOS in terms of producing an efficacious “expected” length of stay. These results are used to provide a more reliable and targeted course for intervention while evaluating facilities, care groups, or provider groups for excess LOS days.Ni?o/a
Speakers: 
Data Scientist,
Ascension
Manager, Data Analytics,
Ascension
Continuing Education Credits: 
ABPM
1.00
AHIMA
1.00
CAHIMS
1.00
CME
1.00
CNE
1.00
CPHIMS
1.00