Health care fraud: Are you prepared to absorb the costs?

Health care fraud: Are you prepared to absorb the costs?

January 27, 2015
From the January 2015 issue of HealthCare Business News magazine
Sareena M. Sawhney

In fiscal Year 2012 alone, various government teams involved in the Health Care Fraud and Abuse (“HCFAC”) Program recovered $4.2 billion from individuals and companies who attempted to defraud federal health programs.

Health care fraud is carried out by many segments of the health care system, including hospitals, physician practices and individuals. Some schemes include:

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1. Billing for services not rendered — no medical service was provided, the service was not provided as described in the claim for payment or the service was previously billed and the claim was paid.

2. Upcoding of services — submitting a bill using a procedure code that results in a higher payment than the code for the service actually provided. Example: 30-minute sessions being billed as 50-minute sessions.

3. Duplicate claims — billing for the same service (i.e., by using two different service dates) in an attempt to be paid twice.

4. Unbundling — separately billing for services that are usually included in a single service fee.

5. Excessive services — providing medical services or items which are more than a patient actually needs. Example: daily medical office visits billed when monthly office visits are adequate.

6. Kickbacks — offering, soliciting, paying or accepting money, or something of value in exchange for the referral of a patient for health care services that may be paid by Medicare or Medicaid. Example: a laboratory owner who pays a doctor $50 for each Medicare patient a doctor sends to the laboratory for testing.

Other health care schemes can involve billing, check tampering, expense reimbursement and/or payroll schemes.

Detecting such schemes can involve various forensic accounting techniques. Among them are analyzing documents and facts, conducting comprehensive individual and group interviews, and using data analysis technology to scrutinize data and identify transactions that indicate fraudulent activity or the heightened risk of fraud. Examples include the following:

  • Stratification of numbers — identifies excessively high or low amounts or excessively high billing by a single physician. Stratification can also help highlight “upcoding” of procedures by identifying outlying numbers.


  • Duplicate testing — identifies transactions such as duplicate claims, payments and expense report items, among others.


  • Joining different data sets — identifies matching values, social security numbers, names and addresses where they shouldn’t exist. Example: matching vendor names/ addresses to payroll records for employees.

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