Architect at Tata consultancy Services, USA.
Review Article
Global Journal of Engineering and Technology Advances, 2023, 16(01), 099–112.
Article DOI: 10.30574/gjeta.2023.16.1.0128
Global Journal of Engineering and Technology Advances, 2023, 16(01), 099-112
Medicare management faces several challenges for the U.S. government despite its supreme importance as a healthcare program for millions. Worrying into the future was the continual problem of improper Medicare payments, the results of fraud, careless clerical work, or unfavorable mistakes. Such funds are channeled in the wrong direction, taking billions of taxpayer money and putting tremendous strain on the country's healthcare sector. However, a new friend is AI, which presents a radical way of tackling these inefficiencies that would otherwise cost a lot of money.
By leveraging AI, new analytical tools can take in vast Medicare bills in real-time and effectively identify outliers and patterns that may indicate mispayments. Due to the application of machine learning technology, AI can identify and flag fraudulent submissions, coding errors, and billing issues more effectively than conventional techniques. These capabilities are prone to enhancement through the use of predictive analytics, flagging either high-risk providers or activities that require further scrutiny.
Returning the misplaced or misused funds is significantly faster through insights powered by artificial intelligence. Automation advances the process of resolutions, while AI aids decision-makers in suggesting ways to enhance policies to eliminate future differences. These systems remain dynamic; they improve each cycle of data collected in the field and fed into the system.
Integrating AI in checking Medicare disbursements saves millions and also secures the system's credibility in the healthcare sector. Situated as it is in moderating mistakes and managing fraud, an AI is an accountable guardian of state resources necessary for Medicare while reciprocating satisfaction to both the taxpayers and beneficiaries of Medicare services.
AI; Medicare; Improper Payments; Fraud Detection; Analytics; Machine Learning; Data Mining
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Viswaprakash Yammanur. AI-driven analytics: Transforming the detection and recovery of improper Medicare payments in the U.S. Global Journal of Engineering and Technology Advances, 2023, 16(1), 099-112. Article DOI: https://doi.org/10.30574/gjeta.2023.16.1.0128
