| Referenced in our Newsletter Volume 3, Issue 3 - March 2004
Prescription Fraud Patterns Link Chart During 2004, losses due to Medicare fraud, according to some industry experts, will exceed $20 billion dollars. Much of this can be attributed to physicians billing and coding fictitious filings, inflated claims, and other types of improper actions. With the new prescription drug benefits recently signed into law as part of the Medicare reform act, the program can expect to see even more types and patterns of fraud and abuse. The following "observations" are derived from a real-world pharmacy data set where much of the information described prescription-related features. Thus, there were fields for amount dispensed, day's supply, various class descriptors, state payments, gender, and other statuses of the claim. Specifically, the names of the patients and doctors were removed for this discussion and the interpretation of the results is subject to further domain expertise. The model created for this analysis is shown below. The CLAIM represents the overall transaction and supports all the attributes for the record. For each CLAIM, there is a single RECEIPIENT (e.g., the patient) and a single PROVIDER (e.g., the pharmacy) who filled the prescription.  A proactive query into the database (using Summarize) reveals a RECIPIENT with multiple CLAIMS that supports the same prescription. In this case, the prescriptions were all for Hydrocodone/APAP. Hydrocodone/APAP is a medication for relieving pain - which is used in Vicodin. Hydrocodone is habit forming and has been part of many high-profile drug abuse cases in recent times. In the diagram below, there are 4 prescriptions shown for Hydocodone filled by the RECEIPIENT (shown in the red color) at the same pharmacy location. Looking at the dates of each claim indicates a new prescription was filled each week. Drilling down on the details shows the specifics of each CLAIM including the day's supply - indicating that there may be an abusive situation forming in this case.  Another example found in the database shows commonality for CLAIMS. Sodium Chloride is taken as an intravenous solution used to supply water and electrolytes to the body. Additionally, it can be used to mix/dilute other forms of IV medications. Dexamethasone is considered a form of steroid like Cortisone and is typically used to treat inflammation, joint pains, and even lymphoma. In the following diagram, the RECEIPIENT has filled the same combination of prescriptions 3 times over a 5 day period using the same pharmacy. In this case the frequency of the CLAIMS is suspect because the dates are exact for each type of CLAIM filed.  In this next example, we focus on patterns with larger numbers of prescriptions filled for a single recipient. In the following diagram there are many duplicate CLAIMS made for the same type of prescription. Although this is not unusual for many medications that are taken regularly or have a certain number of refills, it is the details of those reoccurring CLAIMS that raise suspicion in this case. In the example below, the details for the cluster for the drug Premarin (a form of estrogen) shows that there are two CLAIMS made on the same day each for a 30 day supply. The cluster showing Vioxx (used for osteoarthritis) also has two CLAIMS made within 1 week of each other for a 30 day supply. Needless to say, many insurance companies won't cover the cost of the additional or duplicate medications without cause.  In this final example, the RECEIPIENT shown has filed a large number of CLAIMS on the same date. The larger group of CLAIMS, shown in the lower part of this diagram, were all filed on the same day. In fact, there are 12 different prescriptions filled on 05/01 representing over $1000 in co-pay costs. This type of "spike" in CLAIMS processing should be reviewed to determine if there are any abuses occurring in the system. A sample of the types of prescriptions filled is shown below:  There were several other types of patterns exposed in this data set, including the utilization of multiple pharmacies to fill orders within a fairly short time frame - which might be indicative of circumventing protections (checks and balances) within a system. Additionally different combinations of prescriptions, frequencies, dosages, dates, locations, and other variables has lead to the discovery of other patterns not shown here. |