Developing an anomaly detection framework for Medicare claims

James Kemp, Christopher Barker, Norm Good, Michael Bain

Research output: Chapter in Book/Conference paperConference paperpeer-review

Abstract

Detection rates of non-compliant activity in Australian provider medical claims are below international benchmarks, and new methods are required. Since the Department of Health requires interpretability and incorporation of expert feedback as key components of its decision support systems many existing fraud detection techniques are unsuitable. As part of an Industry PhD project we have developed several new anomaly detection techniques which have been implemented in a prototype software system for the Australian Government Department of Health. We discuss the goals of the project and outline our approach to rapid prototyping and implementing processes to achieve expert-validated improvements in detection rates.
Original languageEnglish
Title of host publicationProceedings of ACSW 2023
Subtitle of host publicationAustralasian Computer Science Week 2023
PublisherAssociation for Computing Machinery (ACM)
Pages234–237
Number of pages4
ISBN (Electronic)9798400700057
DOIs
Publication statusPublished - 30 Jan 2023
Externally publishedYes
Event2023 Australasian Computer Science Week, ACSW 2023 - Melbourne, Australia
Duration: 31 Jan 20233 Feb 2023

Publication series

NameACM International Conference Proceeding Series

Conference

Conference2023 Australasian Computer Science Week, ACSW 2023
Country/TerritoryAustralia
CityMelbourne
Period31/01/233/02/23

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