In regulated industries such as healthcare, identifying errors is only part of the equation. The real question is this: what is the total financial impact across the full population? Statistical extrapolation provides that answer. Statistical extrapolation uses results from a properly selected sample to estimate findings across an entire universe of claims, transactions, or records. When designed…
Data Analytics
Beyond Rules: Smarter Anomaly Detection with Machine Learning
Smarter detection starts with letting the data speak for itself. Unsupervised machine learning is becoming an increasingly valuable tool for detecting anomalies in complex healthcare datasets. As data continues to grow in both volume and complexity, traditional approaches to identifying unusual patterns are being challenged by the need for more scalable, adaptive solutions. One effective approach is the Isolation Forest algorithm,…
Responsible AI in Fraud Analytics
AI and machine learning are increasingly central to fraud analytics in complex, highly regulated environments. As adoption accelerates, much of the public conversation focuses on algorithms, new architectures, improved accuracy metrics, and automation at scale. While these advances matter, real-world experience shows that algorithms themselves are rarely the limiting factor. Today’s machine learning algorithms are already highly capable….
The Rise of GLP-1 Fraud in Medicare, Medicaid, and Commercial Insurance: Data Driven Approaches to Investigations
The booming demand for GLP-1 receptor agonists such as Ozempic, Wegovy, and Mounjaro, used for weight loss and Type 2 diabetes, has sparked a surge in fraudulent activity across Medicare, Medicaid, and commercial insurance. From inappropriate prescribing and billing anomalies to falsified diagnoses, payers are confronting an emerging fraud scheme that demands both advanced data…
Highlighting Public Tools That Advance Medicaid Transparency and Oversight
Let’s talk about…the power of public data tools. Public data dashboards are vital tools for strengthening accountability in healthcare programs. In Medicare and Medicaid, they equip beneficiaries, agencies, and policymakers with insight into how services are delivered and how that information can inform policy development and updates. By making complex data accessible and actionable, these…
Medicare’s $60 Billion Challenge
Medicare loses an estimated $60 billion annually to fraud, waste, and abuse (FWA), a serious drain on critical health resources that directly affects the care and well-being of millions of beneficiaries. These losses not only compromise the integrity of the program but also erode public trust in one of our nation’s most essential public health…
What Is Statistical Extrapolation and Why Does It Matter?
Extrapolation is a statistical method used to estimate values for an entire population based on a smaller, randomly selected sample. In healthcare audits, this technique allows auditors to review a manageable subset of claims and project the findings to the full universe, saving time and resources while maintaining statistical integrity when applied properly. This approach…
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Combating Fraud with Data Analytics: The Fight for Healthcare Fraud Continues
News on an addiction treatment facility operator caught paying $2.9M in kickbacks underscores the urgent need for robust fraud prevention. The fight for healthcare integrity continues at IntegrityM. Here, we unlock the power of data analytics to transform insights into impactful actions. Join us in shaping the future of healthcare integrity.
Quality Data has to Lead the AI Charge
Author: Natasha Williams, Chief Operating Officer There is a wave of excitement in the industry surrounding artificial intelligence (AI), and not without reason. AI, with its ability to synthesize massive quantities of information at lightning speed, promises limitless possibility. I share in the collective optimism surrounding this new frontier. The detection and prevention of fraud,…
What you need to know about the 2021 Open Payments Program Expansion
IntegrityM strongly encourages new ‘covered recipients’ to familiarize themselves with the Open Payments system, so that they can have a successful experience in CY2022. Open Payments Program Background: Under the Physician Payment Sunshine Act (Section 6002 of the Patient Protection and Affordable Care Act of 2010 “PPACA”), the Centers for Medicare and Medicaid Services (CMS)…
Four Schemes to be Wary of Amid Soaring COVID-19 Fraud Reports
While combating fraud, waste, and abuse is a federal initiative upheld by each state, administrators achieve this through various means. Some state OIGs report that their work is primarily focused on beneficiary fraud, while some work in both beneficiary and provider fraud. Furthermore, state OIGs do not always see the same types of fraud, waste,…
Data Analytics & COVID-19 Recovery: A Math-Free Explanation
Data Analytics is an indispensable tool being used in COVID-19 recovery efforts. Many of us take for granted that this is being used, but are not quite sure how. IntegrityM CTO Swathi Young and COO Natasha Williams break down the basics of Data Analytics and COVID-19 to shed light on the role this field plays….
Contact Tracing 101: 5 Quick Facts on Our Most Effective Tool to #flattenthecurve
What is Contact Tracing? Contact Tracing is not new. It has been used to control infectious disease for decades. Contact Tracing is one of the oldest public health tactics and has been used with smallpox, Ebola, tuberculosis, and AIDS. So what exactly is contact tracing? It is the process of supporting patients with suspected or…
Signs of Fraud in Payment Arrangements!
Fraud in Medicare Advantage often operates under the radar, but relationships or subtle patterns can reveal its presence. To uphold program integrity, look beyond obvious data anomalies and consider these critical warning signs: Unusual referral patterns between providers/suppliers Frequent turnover of enrollment agents Unexpected spikes in plan-switching behavior At IntegrityM, we recognize that effective fraud…
Comparative Billing Reports: A Valuable Tool for Outreach and Education
In 2016, there were more than 63,600 drug overdose deaths in the United States — this is more than three times the rate in 1999 according to a report from the National Center for Health Statistics (NCHS), part of the US Center for Disease Control and Prevention (CDC).i In a July 2017 report, The U.S….
So You’ve Detected an Outlier… Now What?
Fighting fraud, waste, and abuse in health care programs is labor intensive often requiring multiple experts including but not limited to data analysts and statisticians, certified coders, clinicians, auditors and fraud investigators. According to The National Health Expenditure Accounts (NHEA), U.S. health care expenditures rose by 2.8 percent in 2015 accounting for approximately 17.8 percent…
Statistical Bias in Health Care Fraud Detection and Prevention Systems
Organizations across the health care program integrity industry are using analytic solutions for fraud detection and prevention that intake and analyze data to signal the threat of fraud. These solutions can process huge amounts of data from multiple sources and remove much of the human element of potential fraud detection. When we think about these…
Data Matching Techniques For Healthcare Fraud Detection
Healthcare fraud very seldom happens in a vacuum. Therefore, data matching — the ability to identify, match, and merge records that correspond to the same entities — is essential to healthcare data analysis. Using The NPPES Database For Data Matching The Centers for Medicare & Medicaid Services issues a unique identification number called a national…
Medicare Overpayment Recovery: Identifying and Calculating Overpayments
In fiscal year (FY) 2015, the error rate for the Medicare fee-for-service (FFS) program was 12.1 percent, or $43.3 billion. This result is an improvement over FY 2014, in which Medicare FFS had an improper payment rate of 12.7 percent, or $45.8 billion. Identifying Medicare overpayments is no easy task. The Medicare program is large…
GLȲD(Σ): Revolutionizing Healthcare Data and Statistical Analysis
What if there was a healthcare data analysis solution that could save you a significant amount of time in the sampling and extrapolation process, resulting in substantial cost savings, and therefore greatly increasing your return on every dollar invested into this process? More results with less time and costs! Manually performing sampling and extrapolation can…
