Let’s look at a possible fraud incident as it unfolds. A patient injures his leg and sees a doctor for one 15-minute appointment. The doctor never sees or treats the patient again, but he bills the patient’s insurance company for five 15-minute appointments over the course of a month. The doctor is betting that the insurance company will never notice the relatively small bills producing a simple way to make some more money for the doctor and his practice.
The scenario above is played out every day in the United States costing the Insurance industry and ultimately the patients that pay insurance premiums billions of dollars. Billing for services not rendered is one of the most common fraud issues in the US healthcare industry. It can take different forms, from a health care provider billing insurance payer for services that are different than the services actually rendered to billing for services they did not provide at all.
It seems that this type of fraud should be easy to detect. While at first glance this seems to be an obvious type of fraud that should be spotted immediately, providers still perceive some billing for services not rendered as so low risk and so easy to get away with that many scheming providers will give it a shot. The avalanche of claims and prompt payment laws and regulations mean that the vast majority of these fraudulent claims slip through standard insurance payment systems and are never detected. Complex paperwork for even simple medical procedures makes checking every claim for authenticity too time consuming and too expensive.
The only way to effectively attack this complex problem is through the use of medical fraud detection software. The detection systems must go beyond traditional software platforms, utilizing advanced pattern detection and recognition as well as complex machine learning and artificial intelligence to not only detect but to anticipate potential fraudulent behavior and bring it to the attention of the proper authorities.