TRANSFORMING HEALTHCARE SYSTEM: AN ADVANCED APPROACH TO FRAUD DETECTION AND PREVENTION

Abstract

In the complex landscape of healthcare, where health insurance serves as a financial safety net during medical emergencies, the surge in fraudulent activities poses a significant threat. This paper introduces an advanced fraud detection solution meticulously designed for health insurance claims. Health insurance is paramount in shielding individuals from the financial burden associated with unexpected medical expenses. However, the alarming increase in fraudulent activities within the healthcare industry demands a proactive defense mechanism to uphold the integrity of health insurance systems. To address this challenge, our proposed solution leverages a sophisticated blend of cutting-edge technologies. The key components include a mixture of clinical concepts, Latent Dirichlet allocation (LDA), and recurrent neural networks (RNN). This amalgamation aims to elevate the accuracy of fraud detection in health insurance claims. By employing LDA, we extract concept weights that encapsulate the nuanced relationships within clinical codes, laying the foundation for a more granular analysis of insurance claims. The architecture unfolds in two pivotal steps. First, the generation of concept weights through LDA provides a comprehensive understanding of the mixture of clinical concepts present in each claim. Subsequently, these weights undergo LSTM-based encoding. The LSTM, known for capturing sequential dependencies, plays a crucial role in unraveling the hierarchical relationships among clinical codes. This process results in a nuanced and effective representation of health insurance claims, empowering the system to distinguish between legitimate and fraudulent activities. In conclusion, this advanced fraud detection solution stands as a powerful and adaptive tool in the realm of health insurance. By integrating a mixture of clinical concepts, LDA, and LSTM, we enhance the system's ability to discern fraudulent activities with unparalleled accuracy. This not only safeguards individuals from financial risks but also fortifies the overall integrity and trustworthiness of health insurance systems. In an ever- evolving landscape, our proposed solution provides a robust defense against emerging fraudulent tactics, ensuring the reliability of health insurance services.