Results for tag: "Healthcare Fraud Analytics"

Healthcare Fraud Analytics is a subset of Data Analytics that focuses on the detection and prevention of fraudulent activities in the healthcare industry. It uses data mining, machine learning, and predictive analytics to identify patterns of fraud and abuse. Healthcare Fraud Analytics can be used to detect billing fraud, insurance fraud, and other types of fraud. It can also be used to identify suspicious activities, such as billing for services that were not provided or billing for services at a higher rate than what is allowed. Healthcare Fraud Analytics can help healthcare organizations reduce costs, improve patient safety, and increase compliance with regulations. It can also help healthcare organizations identify and address potential fraud and abuse before it occurs. Some companies in the Healthcare Fraud Analytics market include LexisNexis Risk Solutions, SAS, IBM, Optum, and Health Fidelity. Show Less Read more