9.5 Insurance Crimes


9.5 Insurance Crimes

Insurance fraud and health care-related crimes are widespread and very costly to carriers, the government, and the consumer public. Insurance fraud involves intentional deception or misrepresentation intended to result in an unauthorized benefit. An example would be billing for health care services that have not been rendered. Health care crime involves charging for services that are not medically necessary, do not conform to professionally recognized standards, or are unfairly priced. An example would be performing a laboratory test on a large numbers of patients when only a few should have it. Health care crime may be similar to insurance fraud, except that it is not possible to establish that the abusive acts were done with intent to deceive the insurer.

Although no precise dollar amount can be determined, some authorities contend that insurance fraud constitutes a $100-billion-a-year problem. The U.S. General Accounting Office estimates that $1 out of every $7 spent on Medicare is lost to fraud and health care crime. Medicare lost nearly $12 billion last year alone to fraudulent or unnecessary claims. It is important that carriers have the intelligence to process claims with payment, recall them, cancel them, reduce them, or seek clarification from medical staff or patient.

9.5.1 False Claims

False-claim schemes are the most common type of health-insurance fraud. The goal in these schemes is to obtain undeserved payment for a claim or series of claims.

MO: This includes billing for services, procedures, or supplies that were not provided or used, as well as misrepresentation of what was provided, when it was provided, the condition or diagnosis, the charges involved, or the identity of the provider recipient. This may also involve providing unnecessary services or ordering unnecessary tests.

Detection Technique: Depending on the insurance carrier, there are various methods used in an attempt to identify false claims, including red-flag reviews by fraud specialists, both on-line and behind the scenes. A carrier may also use an expert system, which is a rule-based program that codifies the rules of a human reviewer. Link analysis may be used to look for a ring of fraudulent providers, and, of course, data mining tools, such as neural networks, may be used for training and detection if samples of fraud cases exist. The net amount of the claim may be too large compared to the average amount of similar claims.

9.5.2 Illegal Billing

Illegal billing schemes involve charging a carrier for a service that was not performed.

MO: This includes unbundling of claims—that is, billing separately for procedures that normally are covered by a single fee. A variation is double billing, charging more than once for the same service, also known as upcoding, the scam of charging for a more complex service than was performed. This may also involve kickbacks in which a person receives payment or other benefits for making referrals.

Detection Technique: The methods are the same as with false claims. In addition, a carrier may use models and rules developed by insurance specialists, coupled with those from data mining analyses, such as decision trees or rule generators to detect these schemes.

9.5.3 Excessive or Inappropriate Testing

Billing for inappropriate tests—both standard and nonstandard—appears to be much more common among chiropractors and joint chiropractic/medical practices than among other health care providers.

MO: The most commonly abused tests include:

  • Computerized inclinometry: Inclinometry is a procedure that measures joint flexibility.

  • Nerve conduction studies: Personal injury mills often use these inappropriately to follow the progress of their patients.

  • Surface electromyography: this measures the electrical activity of muscles, which can be useful for analyzing certain types of performance in the workplace. However, some chiropractors claim that the test enables them to screen patients for "subluxations." This usage is invalid.

  • Thermography: Chiropractors who use thermography typically claim that it can detect nerve impingements, or "nerve irritation" and is useful for monitoring the effect of chiropractic adjustments on sub-luxations. These uses are not medically appropriate.

  • Ultrasound screening: Ultrasonography is not appropriate for diagnosing muscle spasm or inflammation or for following the progress of patients treated for back pain.

  • Unnecessary X rays: It is not appropriate for chiropractors to routinely X-ray every patient to measure the progress of patients who undergo spinal manipulation.

  • Spinal videofluoroscopy: This procedure produces and records X-ray pictures of the spinal joints that show the extent to which joint motion is restricted. For practical purposes, however, a simple physical examination procedure, such as asking the patient to bend, provides enough information to guide the patient's treatment.

Detection Technique: Many insurance administrators are concerned about chiropractic claims for "maintenance care," which is a periodic examination and "spinal adjustment" of symptom-free patients, which is not a covered service. To detect such care, many companies automatically review claims with more than 12 visits. However, this number can be adjusted. In 1999, the U.S. Inspector General recommended automatic review after no more than 12 visits for Medicare recipients. Some chiropractors attempt to avoid review by issuing a new diagnosis after the 12th visit. Link analysis has been used to detect some of these perpetrators, as well as have data mining and expert systems. Data mining analyses should zero in on the percentage of diagnostic test costs to the average net amount of similar claims, as well as a comparison of the cost of one or more diagnostic tests to the average amount of similar claims.

9.5.4 Personal Injury Mills

Many instances have been discovered in which corrupt attorneys and health care providers, usually chiropractors or medical clinics, combine to bill insurance companies for nonexistent or minor injuries. The typical scam includes "cappers" or "runners," who are paid to recruit legitimate or fake auto-accident victims or worker's compensation claimants. Victims are commonly told they need multiple visits.

MO: Mills fabricate diagnoses and reports, providing expensive, but unnecessary, services. The lawyers then initiate negotiations on settlements based upon these fraudulent or exaggerated medical claims.

Detection Technique: Mill activity can be suspected when claims are submitted for many unrelated individuals who receive similar treatment from a small number of providers. These claims are typically manually reviewed by claim specialists; however, link analysis and rule generators can also be used for screening large volumes of claims.

9.5.5 Miscoding

In processing claims, insurance companies rely mainly on diagnostic and procedural codes recorded on the claim forms. Their computers are programmed to detect services that are not covered. Most insurance policies exclude non-standard or experimental methods. To help boost their income, many non-standard practitioners misrepresent what they do and may misrepresent their diagnoses.

MO: Brief or intermediate-length visits may be coded as lengthy or comprehensive visits. Patients receiving chelation therapy may be falsely diagnosed as suffering from lead poisoning and may be billed for infusion therapy or simply an office visit. The administration of quack cancer remedies may be billed as chemotherapy. Live-cell analysis may be billed as one or more tests for vitamin deficiency. Nonstandard allergy tests may be coded as standard ones.

Detection Technique: Any code that is not standard must be subject to review and matched against prior claims from similar clinics or practitioners, typically performed by red-flag claim specialists. Clustering of historical data can be used to detect outliers automatically, and to check a disease (illness) against average duration and cost using a historical claims database to generate a histogram.

In the insurance industry, there are various methods by which carriers attempt to review for fraud while processing policy claims. The following are some important data attributes for detecting potential fraud claims:

  • Duration of illness

  • Net amount cost

  • Illness (disease)

  • Claimant sex

  • Claimant age

  • Claim cost

  • Hospital

Using these variables, analyses can be performed to identify outliers for each, such as test costs, hospital charges, illness duration, and doctor charges. These are some temporal parameters for analyzing insurance claims. Table 9.1 illustrates the various methods of insurance fraud detection, along with some advantages and disadvantages of each. The chart is not all-inclusive but simply provides an overview of trends in the industry.

Table 9.1: Methods of Insurance Fraud Detection

Method

Advantages

Disadvantages

On-line red-flag review by fraud specialist

Provides immediate feedback to claim handler

Is limited to current claim

Limited number of red flags can be reviewed

Must still evaluate the significance of the set of red flags detected

Behind-the-scenes red-flag review by fraud specialist

Can scan for a larger number of red flags

Does not provide immediate feedback to claim handler

Can detect ring activity or repeat fraudulent behavior by the same individuals

Must still evaluate the significance of the set of red flags detected

Doesn't interfere with the claim handling process

Interactive expert systems (this is a rule-based system)

Can detect qualitative red flags as well as quantitative

Is time-consuming for claim handler

Data mining or statistical modeling

Weighs the relative importance of claim information in predicting fraud

Requires that data mining skills be developed

Provides consistent fraud evaluation for all claims

Requires periodic revision of model as the nature of fraud changes

Outlier clustering detection

Is self-adjusting to different types of populations

Need specialized skills to develop

Needs large amounts of transaction data

Link analysis

Provides easy-to-understand graph or map of patterns of fraud

Needs specialized software to display results

Links can detect and uncover fraud rings

Needs some proactive fraud-detection preliminary work to reduce the amount of claim data to represent pictorially

Has limited effectiveness at determining whether an individual claim is fraudulent

Detecting insurance fraud, as in the case of financial crimes, also requires the combined efforts of human experts—investigators, fraud specialists, claim reviewers and forensic auditors—along with the use of data mining tools, such as link analysis, SOMs, neural-network models, decision trees, and rule generators.




Investigative Data Mining for Security and Criminal Detection
Investigative Data Mining for Security and Criminal Detection
ISBN: 0750676132
EAN: 2147483647
Year: 2005
Pages: 232
Authors: Jesus Mena

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