Procedure code overutilization detection from healthcare claims using unsupervised deep learning methods
Abstract Background Fraud, Waste, and Abuse (FWA) in medical claims have a negative impact on the quality and cost of healthcare. A major component of FWA in claims is procedure code overutilization, where one or more prescribed procedures may not be relevant to a given diagnosis and patient profile...
Main Authors: | Michael Suesserman, Samantha Gorny, Daniel Lasaga, John Helms, Dan Olson, Edward Bowen, Sanmitra Bhattacharya |
---|---|
Format: | Article |
Language: | English |
Published: |
BMC
2023-09-01
|
Series: | BMC Medical Informatics and Decision Making |
Subjects: | |
Online Access: | https://doi.org/10.1186/s12911-023-02268-3 |
Similar Items
-
Credit Card Fraud Detection Based on Unsupervised Attentional Anomaly Detection Network
by: Shanshan Jiang, et al.
Published: (2023-06-01) -
Proton Pump Inhibitors: Prescribing Practices, Appropriateness of Use, and Cost Incurred in a Tertiary Care, Public, Teaching Hospital in New Delhi, India
by: Nitish Verma, et al.
Published: (2019-01-01) -
UNSUPERVISED PROBABILISTIC ANOMALY DETECTION OVER NOMINAL SUBSYSTEM EVENTS THROUGH A HIERARCHICAL VARIATIONAL AUTOENCODER
by: Alexandre Trilla, et al.
Published: (2023-01-01) -
Life medicalization and the recent appearance of “pharmaceuticalization”
by: Ricard Meneu
Published: (2018-07-01) -
Are Tumor Marker Tests Applied Appropriately in Clinical Practice? A Healthcare Claims Data Analysis
by: Sabrina M. Stollberg, et al.
Published: (2023-11-01)