Detecting Medicare Fraud
- A First Model. The most interesting dataset is PartD, in which we have for each physician (identified by its NPI) and...
- Adding Some "Outlier Detection" Features. Let's add some features to our model. As we said before we could have some...
- Impact Coding Drugs. As we said previously, some drugs may be expensive to get or have "recreational drug...
Full Answer
How is Medicare fraud detection conducted?
Medicare Fraud & Abuse: Prevent, Detect, Report MLN Booklet Page 6 of 23 ICN MLN4649244 January 2021. What Is Medicare Fraud? Medicare . fraud. typically includes any of the following: Knowingly submitting, or causing to be submitted, false claims or making misrepresentations of fact to obtain a Federal health care payment for which no entitlement
What is Medicare fraud and abuse?
Detecting Medicare Fraud A First Model. The most interesting dataset is PartD, in which we have for each physician (identified by its NPI) and... Adding Some "Outlier Detection" Features. Let's add some features to our model. As we said before …
Can big data help automate Medicare fraud detection?
Jul 18, 2019 · Medicare fraud detection. Our research group has performed extensive research on detecting anomalous provider behavior using the CMS PUF data. In , Bauder and Khoshgoftaar proposed an outlier detection method based on Bayesian inference that detected fraud within Medicare. This study used a small subset of the 2012–2014 Medicare Part B data by selecting …
What is health care fraud?
Medicare Fraud & Abuse: Prevent, Detect, Report MLN Booklet Page 5 of 21 ICN MLN4649244 January 2021. What Is Medicare Fraud? Medicare . fraud. typically includes any of the following: Knowingly submitting, or causing to be submitted, false claims or making misrepresentations of fact to obtain a Federal health care payment for which no entitlement
How does Medicare detect fraud?
Detect fraud by examining both the Medicare Summary Notice (MSN) you receive from Medicare after your claims are paid, and/or the Explanation of Benefits (EOB) you receive from your Part C and/or Part D plan.
What are red flags for Medicare fraud?
Some red flags to watch out for include providers that: Offer services “for free” in exchange for your Medicare card number or offer “free” consultations for Medicare patients. Pressure you into buying higher-priced services. Charge Medicare for services or equipment you have not received or aren't entitled to.
What is considered Medicare abuse?
Medicare abuse includes practices that result in unnecessary costs to the Medicare program. Any activity that does not meet professionally recognized standards or provide patients with medically necessary services is considered abuse. Committing abuse is illegal and should be reported.
What are the 26 Red flag Rules?
In addition, we considered Red Flags from the following five categories (and the 26 numbered examples under them) from Supplement A to Appendix A of the FTC's Red Flags Rule, as they fit our situation: 1) alerts, notifications or warnings from a credit reporting agency; 2) suspicious documents; 3) suspicious personal ...
What is account take over fraud?
Account takeover fraud is a form of identity theft. It works through a series of small steps: A fraudster gains access to victims' accounts. Then, makes non-monetary changes to account details such as: Modifies personally identifiable information (PII)
A First Model
The most interesting dataset is PartD, in which we have for each physician (identified by its NPI) and drug, the total amount of prescriptions, total cost and total number of days prescribed. From this, we should be able to create a few features to qualify the chance of each physician to be a fraudster.
Adding Some "Outlier Detection" Features
Let's add some features to our model. As we said before we could have some physicians behaving normally except for certain drugs. We could catch that by checking for the outliers in cost distribution or more simply at the 99 percentile of the distribution.
Impact Coding Drugs
As we said previously, some drugs may be expensive to get or have "recreational drug use". As a result we could assume that actually prescribing some drugs can be a feature of importance for fraud detection. To check if this can be the case, let's have a look at the list of best " impact coded " drugs.
Adding Other Datasets Information
We can ask ourselves if there is a link between committing a fraud and receiving large payments from pharmaceutical companies. In this post, we will simply create a feature being the total sum of payments received in 2013 without distinction of payment type or company.
Conclusion
It seems possible to construct basic fraud models using the Medicare data. Of course, the performance is not very good due to the lack of labelled data.
How to detect Medicare fraud?
Educating yourself about Medicare fraud (and about Medicare in general) is the single best way to detect Medicare fraud. When you know your enemy, you know the way they operate. You know their common ploys. When you know how Medicare works, you can better recognize when people are exploiting it.
What to do if you don't understand Medicare?
It’s been drilled into your head since you were young. If you don’t understand something, just ask! The same goes for Medicare fraud. If you notice something on your bill that you didn’t receive, if you feel as if you received care that wasn’t necessary, or you are just confused, ask your doctor or provider. You don’t want to falsely report your family doctor for fraud, but you also don’t want to let him get away with it if he is guilty. So just ask. If he is innocent, he will provide a clear explanation. If not, maybe you should report him.
Who is Dan Hoelscher?
Dan is a Certified Financial Planner™ Practitioner and holds Certified Senior Advisor (CSA)© and Certified Kingdom Advisor™ certifications. Since founding Seniormark, Dan has helped thousands of retirees throughout Ohio.
Is Medicare a scam?
If someone shows up on your doorstep and claims to a representative of Medicare, just slam the door. If you pick up the phone and someone asks for your Medicare number as a part of a “health survey,” hang up. It’s a scam. And these are only two of many! There is a reason why these people are called con artists. They get creative when it comes to fraud. So, as a rule of thumb, if they ask for personal information, it’s probably fraud. And if they claim to be a Medicare representative and ask for your Medicare number, it definitely is. Medicare already has your number; they are the ones that gave it to you!
How are fraudulent provider labels generated?
Fraudulent provider labels are generated by matching the NPI numbers of excluded individuals from the LEIE data set to the Medicare Part B data set. By matching on NPI numbers only, we can be fairly confident that we are not incorrectly labeling providers as fraudulent. One shortcoming to this approach is that the LEIE data set only lists NPI numbers for a small fraction of the excluded individuals, e.g. 25% in February of 2019. We believe that we can increase the total number of fraudulent labels by looking up missing NPI numbers in the NPPES registry, similar to [ 46 ], and we leave this for future work.
What is Medicare insurance?
Introduction. Medicare is a United States (U.S.) healthcare program established and funded by the Federal Government that provides affordable health insurance to individuals 65 years and older, and other select individuals with permanent disabilities [ 1 ]. According to the 2018 Medicare Trustees Report [ 2 ], in 2017 Medicare provided coverage ...
How many people are on Medicare in 2019?
Medicare enrollment has grown to 60.6 million as of February 2019 [ 3 ]. There are many factors that drive the costs of healthcare and health insurance, including fraud, waste, and abuse (FWA) within the healthcare system.
Who maintains the LEIE?
The LEIE is maintained by the Office of Inspector General (OIG), and its monthly releases list providers that are prohibited from participating in Federal healthcare programs. Under the Exclusion Statute [ 28 ], the OIG must exclude providers convicted of program-related crimes, patient abuse, and healthcare fraud.
What is Medicare Part B claim?
The Medicare Part B claims data set describes the services and procedures that healthcare professionals provide to Medicare’s Fee-For-Service beneficiaries. Records within the data set contain various provider-level attributes, e.g. National Provider Identifier (NPI), first and last name, gender, credentials, and address. The NPI is a unique 10-digit identification number for healthcare providers [ 67 ]. In addition to provider-level details, records contain claims information that describe a provider’s activity within Medicare over a single year. Examples of claims data include the procedure performed, the average charge amount submitted to Medicare, the average amount paid by Medicare, and the place of service. The procedures rendered are encoded using the Healthcare Common Procedures Coding System (HCPCS) [ 68 ]. For example, HCPCS codes 99219 and 88346 are used to bill for hospital observation care and antibody evaluation, respectively. Also included in the claims data is the provider type, a categorical value describing the provider’s specialty that is derived from the original claim.
Who performed the research and drafted the manuscript?
JMJ performed the research and drafted the manuscript. TMK worked with JMJ to develop the article’s framework and focus. TMK introduced this topic to JMJ. Both authors read and approved the final manuscript.
What is LEIE exclusion?
The LEIE exclusion type attribute is a categorical value that describes the offense and its severity. Following the work by Bauder and Khoshgoftaar [ 35 ], a subset of exclusion rules that are most indicative of fraud is selected for labeling Medicare providers. Table 3 lists the exclusion rules used in this paper along with their mandatory exclusion periods. We use the NPI numbers of excluded individuals that have been convicted under one of these rules to identify fraudulent providers within the Medicare Part B data set. For these providers in the Medicare Part B data set, whose NPI number matches those of the LEIE data set, claims that are dated prior to the provider’s exclusion date are labeled as fraudulent. In doing so, we are making the assumption that a provider’s claims activity prior to the date that they were excluded from Medicare reflects fraudulent activity, as they were soon after convicted.
What is heat in Medicare?
The DOJ, OIG, and HHS established HEAT to build and strengthen existing programs combatting Medicare fraud while investing new resources and technology to prevent and detect fraud and abuse . HEAT expanded the DOJ-HHS Medicare Fraud Strike Force, which targets emerging or migrating fraud schemes, including fraud by criminals masquerading as health care providers or suppliers.
What is the OIG self disclosure protocol?
The OIG Provider Self-Disclosure Protocol is a vehicle for providers to voluntarily disclose self-discovered evidence of potential fraud. The protocol allows providers to work with the Government to avoid the costs and disruptions associated with a Government-directed investigation and civil or administrative litigation.
What is the role of third party payers in healthcare?
The U.S. health care system relies heavily on third-party payers to pay the majority of medical bills on behalf of patients . When the Federal Government covers items or services rendered to Medicare and Medicaid beneficiaries, the Federal fraud and abuse laws apply. Many similar State fraud and abuse laws apply to your provision of care under State-financed programs and to private-pay patients.
What is the OIG?
The OIG protects the integrity of HHS’ programs and the health and welfare of program beneficiaries. The OIG operates through a nationwide network of audits, investigations, inspections, evaluations, and other related functions. The Inspector General is authorized to, among other things, exclude individuals and entities who engage in fraud or abuse from participation in all Federal health care programs, and to impose CMPs for certain violations.
What is the Stark Law?
Section 1395nn, often called the Stark Law, prohibits a physician from referring patients to receive “designated health services” payable by Medicare or Medicaid to an entity with which the physician or a member of the physician’s immediate family has a financial relationship , unless an exception applies.
What is the OIG exclusion statute?
Section 1320a-7, requires the OIG to exclude individuals and entities convicted of any of the following offenses from participation in all Federal health care programs:
Is there a measure of fraud in health care?
Although no precise measure of health care fraud exists, those who exploit Federal health care programs can cost taxpayers billions of dollars while putting beneficiaries’ health and welfare at risk. The impact of these losses and risks magnifies as Medicare continues to serve a growing number of beneficiaries.
What is Medicare fraud?
Healthcare fraud is a main problem that causes substantial monetary loss in Medicare/Medicaid and insurance industry. The Centers for Medicare and Medicaid Services (CMS) have setup Medicare Part D programs since 2006. CMS relies on it to detect and prevent fraud, waste and abuse in Part D program.
How much did healthcare cost in 2014?
healthcare spending from 2012 to 2014 has increased by 6.7% to reach $3 trillion and Medicare spending accounts for 20% of all health-care spending in the U.S. at about $600 billion.
What is descriptive analytics?
• Descriptive Analytics for Fraud Detection Descriptive analytics or unsupervised learning aims at finding unusual anomalous behavior deviating from the average behavior or norm. When used for fraud detection, unsupervised learning is often referred to as anomaly detection, since it aims at finding anomalous and thus suspicious observations. Unsupervised learning can be useful for fraud detection and thus have no labeled historical data set available (such as LEIE). It can also be used in existing fraud models by uncovering new fraud mechanisms. We will try to use the nearest-neighbour based techniques, Clustering-based methods and other algorithms.
What is the AUC curve?
We will use the Area Under receiver operating character istic Curve (AUC) performance metric. AUC is used to assess the capabilities of binary classification methods. The ROC curve is used to characterize the trade-off between true positive rate and false positive rate, depicting a learner’s performance across all decision thresholds. Perfect classification is indicated by an AUC value of 1, with a range from 0 to 1. Due to the severe class imbalance of the testing data, AUC is used as the performance measure for our experiment.
What is a capstone project?
This project is dedicated to building big data solutions with tangible applications at the intersection of healthcare and insurance industry . This Capstone project will build a Medicare Fraud Detection model to analyze open data and predict/detect the fraudulent Medicare providers based on fraud patterns, anomaly analysis and geo-demographic metrics, with FDA drug data’s help this model is also trying to figure out the Opiate prescriptions and Overdoses related fraudulence. All datasets will be based solely on publicly available Medicare data from the Centers for Medicare and Medicaid Services (CMS), FDA/openFDA and other open data resources.
