identify fraud amp abuse through data analysis
Identify Fraud & Abuse through Data Analysis
Read:
- AHIMA Professional Code of Ethics
- Addressing Healthcare Fraud, Waste, and Abuse
- Preventing Provider Fraud through Health IT, Data Analytics
- Top Waste, Fraud, and Abuse Red Flags
- M4 lecture: Waste, Fraud, and Abuse
In your essay:
- Consider the False Claims Act, whistleblowers, the Anti-Kickback Statute (Stark), unbundling, Upcoding, role of OIG & RAC, and use of copy/paste and templates in the EHR
- Describe how data analysis identifies potential abuse or fraudulent trends
- Demonstrate your reading and research by including facts from these in your statements and citing your source(s).
- Provide a reference list in APA format of your sources that are cited in your essay. Use at least two sources
Attached Files:
- M4 EHRs, Upcoding, Overpayments, and the False Claims Act – Understanding the Risks.pdf M4 EHRs, Upcoding, Overpayments, and the False Claims Act – Understanding the Risks.pdf – Alternative Formats (2.473 MB)
- M4 Preventing Provider Fraud through Health IT, Data Analytics.pdf M4 Preventing Provider Fraud through Health IT, Data Analytics.pdf – Alternative Formats (2.916 MB)
- M4 Top waste, fraud, and abuse red flags, and how to identify them.pdf M4 Top waste, fraud, and abuse red flags, and how to identify them.pdf – Alternative Formats (688.055 KB)
- M4-Providers hope for Stark overhaul to boost value-based payment.pdf M4-Providers hope for Stark overhaul to boost value-based payment.pdf – Alternative Formats (4.606 MB)
- M4D AHIMA Code of Ethics.docx M4D AHIMA Code of Ethics.docx – Alternative Formats (48.337 KB)
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