How SAS Detects and Prevents Health Care Fraud, Waste and Abuse
Fraud, waste and abuse in health care divert billions away from patient care annually. Faster, more aggressive investigation and detection of key risk indicators at every stage of the process is key to controlling costs and protecting patients.
A holistic view of clinical conditions & events
- Gain a more comprehensive view of patient care across a variety of conditions and procedures to identify important event interdependencies.
- Determine the true cost of clinical conditions, better manage payment models and improve patient outcomes.
Value-based care & payment models
- Confidently predict and manage financial and clinical risks and rewards associated with contracting for value.
- Use clinical data to adjust for acuity within provider populations, thus increasing adoption of a value-based care model.
Fraud data management
- Consolidate historical data from internal and external sources – claims systems, watch lists, third parties, unstructured text, etc.
- Discover connections among entities sooner to expose organized fraud rings or collusive activities.
Detection & alert generation with embedded AI
- Gain awareness earlier with alerts based on a calculated propensity for improper billing at first submission.
- Reduce false positives to improve investigative focus.
- Uncover suspicious activity sooner with an end-to-end framework that includes modern statistical, machine learning, deep learning and text analytics algorithms.
How does America's largest dental insurer use SAS to properly allocate funds and improve patient outcomes?
SAS helped DentaQuest:
- Implement a powerful analytics platform to detect fraud, monitor business performance and comply with guidelines set by the Centers for Medicare & Medicaid Services.
- Model data from claims, providers and other sources, reviewing more than 50 different indicators of potential fraud, waste and abuse in the models to flag suspicious claims.
- Prioritize cases based on severity to tackle the most pressing cases first.
How does a Dutch health insurer use SAS to detect fraud and misuse before payments are made?
SAS helped Dutch health insurer CZ:
- Analyze claims in real time to ensure that each claim is legitimate before money goes out the door.
- Analyze health provider profiles more closely using a hybrid detection method that employs a combination of rules, anomaly detection, predictive models and social network analysis.
- Integrate disparate information on claims and costs to detect previously unknown fraud schemes and spot linked entities to stem larger losses.
- Establish a second-generation health care cost-management program designed to quickly detect, investigate and report on suspicious claims.