How far is too far? Identifying suspicious travel patterns in healthcare claims using machine learning

• Published in: 2023 International Conference on Machine Learning and Applications (ICMLA) pp. 610 - 617
• Main Authors: Wang, Kai, Lasaga, Daniel, Helms, John, Bowen, Edward, Bhattacharya, Sanmitra
• Format: Conference Proceeding
• Language: English
• Published: IEEE 15.12.2023
• Subjects: Anomaly Detection; Codes; Detectors; Gastroenterology; Geographic Information Systems; GIS; Machine learning; Medical services; Mental health; Neural Networks; Pain

Fraud in healthcare services and claims poses a significant threat to healthcare expenditure, accessibility to health services, and quality of care of members. One important type of member-provider collusion is where members travel unreason-able distances seeking healthcare services. Such activities...