ProgramsBMIS476 Integrated Project Management Capstone Course (Fall 2026)ProjectsFraud, Waste, and Abuse Triage Tool Development for Medicare Claims

Project Title: Fraud, Waste, and Abuse Triage Tool Development for Medicare Claims

Morton Analytics LLC

Details
Project Title Fraud, Waste, and Abuse Triage Tool Development for Medicare Claims
Project Topics Artificial Intelligence & Machine Learning Data Management Operations Quality Control Reporting, Financial Planning & Analysis Software Design & Development
Skills & Expertise AI Integration Critical Thinking Dashboard Development Data Processing Data Visualization financial analysis Fraud Detection Techniques Healthcare Billing Knowledge Large Language Models Problem Solving Project Management Python Rule-Based Detection Schema Design stakeholder communication
Project Synopsis: Challenge/Opportunity
Morton Analytics LLC is a data analytics firm specializing in providing actionable insights for healthcare providers and payers. Known for its expertise in handling large datasets and delivering strategic solutions, the company excels in transforming complex data into digestible, actionable information. However, the challenge lies in the efficient detection of fraud, waste, and abuse (FWA) within the vast volumes of Medicare claims data. This is a nuanced problem that requires not only technical prowess but also domain-specific knowledge of healthcare billing practices.

The current gap in FWA detection impacts the company by potentially allowing significant financial losses due to undetected fraudulent activities. The lack of a sophisticated, automated detection system means that Morton Analytics cannot fully leverage its data analytics capabilities to provide comprehensive solutions to its clients. This project offers students the opportunity to bridge this gap by developing a cutting-edge FWA triage tool that automates the detection process and enhances the company's service offerings.

This project unfolds in several phases: data processing and pipeline creation, rule-based detection implementation, AI integration for complex case analysis, dashboard development, and business case presentation. Each phase presents unique challenges and learning opportunities. Students will learn to manage real-world data volumes, apply machine learning techniques, and develop user-friendly interfaces, all while maintaining a focus on delivering business value.

This project is ideal for students because it combines technical, analytical, and business skills, providing a holistic learning experience that mirrors real-world professional scenarios. By tackling this project, students will develop critical skills in data analytics, project management, and solution development, all of which are highly valuable in careers such as consulting, finance, operations, and healthcare policy. The project is exciting and relevant because it directly impacts the efficiency and effectiveness of healthcare fraud detection, a field with significant financial and ethical implications.
Project Synopsis: Activities/Actions Required
  1. Analyze the CMS DE-SynPUF dataset to understand its structure and variables.
  2. Develop a data processing pipeline capable of handling large volumes of data.
  3. Define and implement a schema for efficient data management.
  4. Design rule-based detection algorithms for identifying duplicate billing and rate outliers.
  5. Integrate a large language model to evaluate procedure and diagnosis code pairings.
  6. Create case narratives based on AI analysis for investigator review.
  7. Develop a dashboard to visualize provider rankings and outlier cases.
  8. Conduct a financial analysis to quantify the impact of detected fraud and waste.
  9. Prepare a business case presentation to communicate findings and recommendations.
  10. Log and analyze AI API calls to ensure compliance and track performance.
Project Synopsis: Expected Results
  • Ability to process large datasets using a defined schema and reproducible pipeline.
  • Development of rule-based detection methods for fraud identification.
  • Effective application of AI to analyze complex medical billing scenarios.
  • Creation of a functional dashboard for data visualization and analysis.
  • Completion of a business case presentation with financial impact analysis.
  • Improved understanding of healthcare billing and fraud detection methods.
  • Hands-on experience with real-world data analytics and project management.
  • Enhanced skills in Python, data management, and AI integration.

Project Timeline

Touchpoints & Assignments Date Type

Project Teams Finalized

Sep 03 2026 Event

Learn More About CapSource Platform

 Sep 04 2026 Action Item

CapSource Intro Session

 Sep 08 2026 Event

Schedule Kickoff Meeting with Client

 Sep 10 2026 Event

Projects Assigned

 Sep 10 2026 Event

Submit Team Charter

 Sep 15 2026 Action Item

Submit Status Report #1

 Sep 15 2026 Action Item

Submit Signed NDA (if Required by Client)

 Sep 15 2026 Action Item

Project Kickoff Self Assessment

 Sep 15 2026 Evaluation

Submit Project Charter

 Sep 29 2026 Action Item

Submit Status Report #2

 Sep 29 2026 Action Item

Industry Mentor Temperature Check #1

 Sep 29 2026 Evaluation

Student Temperature Check #1

 Sep 29 2026 Evaluation

Submit Data Collection Plan

 Oct 13 2026 Action Item

Submit Status Report #3

 Oct 13 2026 Action Item

Student Temperature Check #2

 Oct 27 2026 Evaluation

Submit System Requirements Documentation

 Oct 27 2026 Action Item

Submit Status Report #4

 Oct 27 2026 Action Item

Industry Mentor Temperature Check #2

 Oct 27 2026 Evaluation

Submit Status Report #5

 Nov 10 2026 Action Item

Student Temperature Check #3

 Nov 10 2026 Evaluation

Industry Mentor Temperature Check #3

 Nov 10 2026 Evaluation

Submit Design Document

 Nov 10 2026 Action Item

Schedule Your Final Presentations with Client

Nov 10 2026 Action Item

Submit Status Report #6

 Nov 24 2026 Event

Submit Link to Project Workbook

 Dec 04 2026 Action Item

End of Project Self Reflection

 Dec 04 2026 Evaluation

Project Review! Please Provide Us With Your Feedback!

 Dec 04 2026 Evaluation

Share Your Experience!

 Dec 08 2026 Action Item

Program Managers

Name Organization
Clayton Looney University of Montana

Teams

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No Teams Available