Fraud Analytics is the New ‘Sherlock Holmes’ in the Healthcare Industry

Nov 14, 2017

fraud analytics

The growth of the healthcare industry in terms of technological advancements and wealth has skyrocketed in the past decade. Today, healthcare is grabbing more eyeballs than ever before due to new and unique innovations that are taking the healthcare industry by storm.  Apart from medical inventions, the healthcare industry is also identifying more ways to increase their operational efficiency, making them one of the most advanced and competitive industries. However, there are bigger issues in healthcare that are becoming are major sources of concern – such as health care fraud. The healthcare providers are resorting to advanced fraud analytics techniques to combat fraudulent practices in healthcare.

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Common Practices of Healthcare Fraud

Some of the common practices of health care fraud that can be overcome by fraud analytics are:

  • Illegal medical billing practices and false claims
  • Multiple claims filed by different providers for the same patient
  • Stolen patient identities, which are used to gain reimbursement for unused medical services
  • Benefits of fraudulent claims shared between fraudulent providers and the patients

How Does Fraud Analytics Help?

Before the inception of fraud analytics, traditional analytics methods were used to identify fraud in the healthcare industry. But this technique takes months to identify fraud and gather evidence against such practices and put the offenders behind bars. Therefore, the need of the hour in the healthcare industry is to ‘close the doors of the barn before the horse escapes’ i.e., to identify such fraudulent practices before the real culprits escape.

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This is where fraud analytics comes into the picture. Fraud analytics identifies potentially fraudulent practices and flags certain claims based on a pre-determined set of rules that helps medical operators look into the situation immediately. Fraud analytics in healthcare will help combat fraudulent practices in the following manner:

  • Track and identify inconsistencies and suspicious/rule-breaking behavior
  • Potentially improper payments are detected and prevented by flagging them for review
  • Mine data continuously to identify new fraudulent patterns and develop new sets of rules accordingly

Benefits of Fraud Analysis

  • Saves cost of unnecessary payments made for fraudulent transactions
  • Fraud analysis continuously identifies new patterns of fraudulent behavior, which keeps the system up-to-date
  • Speedy real-time solutions are provided using fraud analytics, which reduces the amount of manual effort and review time needed for each suspect claim

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