Fraudulent Health Insurance Claims - How to Detect Fraud?

How to Detect Fraud?

Fraudulent Claim Triggers

It has been observed that frauds pertaining to health insurance usually possess some sort of common trends or patterns. There are certain parameters that can be employed as a trigger to detect false claims or practices which have been enlisted below:

• Treatment expenses are usually on the higher side as compared to the etiology or routine healthcare expenses from that particular hospital.
• Unnecessary and costly investigations are being carried out.
• Diagnosis of the ailment and the investigations done are not in-sync with each other.
• Duration of stay in the hospital is for an extended period, with no positive outcome.
• Increased hospitalization admissions during a particular period.
• Post-operative histopathology reports are not available (surgical cases).
• X-Ray films and reports are not available.
• In most fraudulent claims, the treating doctor, agents, and ailments are the same.

• Medical bills are in serial order.
• Patient residence and the hospital, chemist address, are not geographically same.
• Fraud claimers usually purchase short-term policy with sum insured being low.
• Increase in per-patient cost.
• Higher number of per-patient average visits.
• Higher number of per-patient average medical investigations.
• Fluctuating monthly claims of the healthcare providers.

Measuring Fraud Data

Measurement of fraudulent data is an elusive target. No single method used for fraud detection is considered as wholesome or holistic.

Collection of fraudulent data is mostly done by a group in unison. It is never done individually. It is a gradual process done on piecemeal basis. In short, it is an ongoing process.

Different insurance companies gather data regarding insurance frauds in methods that vary considerably from each other. There is lack of agreement regarding a uniform method to be devised for detecting fraud committed by a policyholder or by a healthcare provider. The quality, volume of data, data specimens and their scope compiled in the database varies considerably in their features.

In addition, there are numerous independent agencies, fraud detection agencies, investigation agencies, legal agencies, insurance industry squads, watchdogs that conduct research on fraudulent data.

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