Solution Brief
Medicaid and Medicare Fraud
Strengthen your state budget by quickly detecting and preventing fraud and improper payments
The issue
The problem of fraud in government assistance programs exploded in 2020 because of the COVID-19 pandemic. As organizations face ever-increasing and innovative fraud schemes, they must be able to rapidly detect and adapt to new threats. According to the US Centers for Medicare and Medicaid Services (CMS), the Medicaid improper payment rate was 7.38% or $31.2 billion in 2023. Changes to Medicare and Medicaid rules due to COVID-19 have only made things worse.
Fraud and improper payments are conservatively estimated to be from 3% to 10% of all Medicaid spending – a significant portion of one of the largest, fastest-growing expenditures in US state budgets. Lacking a financial incentive for managed care organizations to combat fraud and improper payments, containing costs for traditional fee-for-service and managed care models is the only way to realize savings. By adopting a sound method to tackle fraud, states can also recover previously lost funds, prevent future improper payments, and significantly influence growing Medicaid and Medicare expenditures.
The challenge
Multiple data silos and formats
It’s difficult to combine all data sources into a usable format. SAS collects and integrates diverse data from systems and program silos, then applies robust advanced analytics and visualizations to detect and prevent fraud, waste and abuse faster.
Limited investigator resources
Small teams of investigators struggle to quickly identify fraud schemes and review cases efficiently. SAS streamlines the process by combining data into a single, unified platform for analysis, then accurately scoring and prioritizing alerts and routing them to investigators. Advanced case management tools help investigators triage and effectively investigate high caseloads.
Ineffective payment recovery
The traditional pay-and-chase approach to fraud makes it hard for states to recover fraudulent expenditures. SAS incorporates multiple techniques – like automated business rules, multivariate anomaly detection, predictive modeling, text mining and network link analysis – to uncover fraud and improper payments before they occur. This enables agencies to preemptively review providers before claims are paid.
(Integrate data from different sources to accurately identify fraudulent behavior;Investigate fraudulent activity rapidly and stop payment before it is made;Prioritize push alerts for your investigators)
Our approach
Our comprehensive solution from SAS helps you detect and prevent health care fraud, waste and abuse faster through automation and manage payment integrity issues from every angle.
We provide software and services to help you:
Get faster, better insights
Integrate data from different sources into a unified platform, covering the entire data and AI life cycle, helping you increase detection rates, decrease false positive alerts and make trustworthy decisions.
Alert generation
SAS offers a comprehensive alert generation process using predictive modeling and automated business rules, enabling you to predict fraudulent claims. Many fraud detection systems are query-based and assume users will know what questions to ask of the data. SAS automates this process, using advanced analytics to push prioritized alerts to investigators so they can focus on what matters most.
Anomaly detection
Apply anomaly detection using over 1,400 health care-specific scenarios, revealing unusual behaviors and identifying high-risk claims and claim lines, including medical unlikely edits.
Social network analysis
Identify linkages among claims faster with a unified visualization interface and build social networks and gain a holistic view of fraud risk and discrepancies.
Analytic insights for everyone
Access to analytic insights for all users across the health ecosystem, whether they prefer to code or use a low code/no code interface.
Stay ahead with a flexible, unified platform
Our cloud-native solution is explainable, repeatable and fast – and works with virtually all programming languages, including open source.
SAS difference
Other solutions rely almost exclusively on claims data and limited provider and recipient data obtained during enrollment.
SAS helps large health insurance providers, payers, pharmacy benefit managers and government organizations address complex challenges across all aspects of government assistance programs. This ranges from eligibility and enrollment to managed care oversight, post-payment detection and recovery of improper payments, and prepayment identification and prevention of improper claims.
SAS can help by providing:
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SAS Health has an easy-to-use interface that allows you to input claims data and associated payments and group them into categories in a low- code/no- code environment.
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SAS Payment Integrity for Health Care helps identify linkages among claims, patients, providers and facilities – and then identify suspicious behaviors within these networks.
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SAS Payment Integrity for Health Care allows you to generate alerts and create customized reports to predict, prevent and manage payment integrity issues.
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With SAS Payment Integrity for Health Care, you can create custom views faster, saving internal resources time, quantifying impact and ROI, and encouraging leadership to continue investing in resources. Customizable dashboards allow you to quantify violations and associated costs.
CMS has identified more than $10 billion in potential savings by identifying discrepancies in billing, utilization and payments.
SAS in Health Care
>60
>60 countries with SAS health care customers
100%
100% of Fortune Global 50 health care and life sciences are SAS customers
>1,700
>1,700 health and social services customers worldwide