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How to prevent fraud and abuse in healthcare insurance

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Soma Tah
New Update
Healthcare

Prashanth Sarpamale

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Fraud and abuse in healthcare insurance costs the industry crores every year. Often under-reported and discounted, it increases the total cost of insurance. For consumers it results in higher premiums, out-of-pocket expenses, reduced benefits and negatively impacts the availability of health insurance.

Impact of potential claims fraud on Ayushman Bharat

The health insurance industry in India loses approximately Rs 600-800 crores annually to fraudulent claims. As the country embarks on a mission to cover 40% of the country’s population, benefitting 10 crore families with state-sponsored health insurance under the proposed scheme of Ayushman Bharat – Pradhan Mantri Jan Aarogya Yojana, there is a rising concern regarding escalating instances of fraud, which can potentially exhaust an estimated 7-10% of the total budget of the program.

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Various initiatives undertaken by insurance providers

In order to combat the problem of healthcare claims fraud, insurance providers in the country have been taking various steps over the last few years. Leading insurance providers are putting stricter verification and approval processes in place, and leveraging technology to better identify potential cases of fraud. In some instances, they are also identifying regions that have a high concentration of fraud claims and blacklisting corresponding pin codes. Regulatory bodies, on the other hand, are attempting to institute centralized databases to promote sharing of information within the industry. However, for any of these measures to be significantly impactful on a national scale, insurance providers would need to implement a fraud-detection strategy that is integral to the foundational framework of the industry.

Key fraud prevention challenges in India

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To prevent fraud, insurance providers must understand and account for all possible instances that can happen when a consumer buys a healthcare policy or raises a claim. Even though staged accidents, fake disability claims, fabricated documents, inflated bills, and concealed pre-existing conditions are a few common instances of fraud in India, it can also be the result of claims for uncovered members, error on the part of the billing professional, or identity theft. Healthcare providers in the country are also known to contribute towards insurance fraud by overcharging, billing for services not provided, doing unwarranted procedures and excessive investigations, or extending the length of the patient’s hospital stay, among other ways. While absence of regulatory framework is one reason, lack of standardized operating procedures like a defined reimbursement method, CPT code system etc. for organized healthcare delivery and financing also become a cause of health insurance fraud in India.

In addition to a multitude of possible instances of fraud, health plans also face the challenge of a manual claims adjudication process, requiring a significant part of the processing to be done manually. This multiplies the effort and cost, and still leaves room for errors that cannot be detected by human processing. The age-old Fraud, Waste, and Abuse (FWA) systems used to identify suspicious claims are turning obsolete in the today’s times wherein technology can as easily be leveraged by fraudsters as by the providers themselves. Not only are they faced with fraudulent claims that are hard to differentiate from real ones, they are witnessing instances of fraud that have never been seen before.

Battling fraud prevention challenges: Leveraging technological advancement and data analytics

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Fraud and abuse come in various disguises. While various process improvements and modifications can be made to raise triggers, one thing that has repeatedly proven effective in detecting fraud is data analytics. Insurance providers can extract actionable intelligence with the help of advanced data analytics tools, form predictive models, and flag those likely to commit fraud.

Health insurance providers around the world are spawning the development of new and more sophisticated tools to predict fraud and mitigate risks. Going beyond the use of traditional data points, alternative sources of information are being harnessed, that are made available by the widespread adoption of digital technology over the last few years. Information from social media and data from mobile and wearable devices can be used to build real-time monitoring and to identify when a policyholder’s claims are not consistent with his behavior. Not only are these methods and tools transforming fraud detection and abuse, they are offering various optimization opportunities for the health care insurance industry to tap into.

Moving from a reactive to a proactive approach

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Claims fraud poses a considerable challenge for the healthcare insurance industry. Yet, a comprehensive and integrated approach to fraud risk management continues to be absent. An increasing number of fraud cases, rising costs, and growing risk necessitates that health care insurance providers’ work to build in more robust checks, and leverage advanced technologies to mitigate risk.

Moving from a reactive stance to a proactive stance, insurance companies must establish a technology framework to tap into advanced automation and analytics. Implementing processes that identify fraud early and provide the ability to move quickly can be helpful. In today’s digital age, technology and big data can enable companies to predict fraud and take precautionary measures well ahead of time. Addressing challenges for stakeholders across the industry value chain, this robust approach can be integral to a healthcare insurance provider’s competitive edge in today’s rapidly evolving market.

With evolving fraud detection techniques, fraud schemes are taking new forms in healthcare. The only way insurance companies can guard themselves against these fraudulent practices is through keeping a tab on data patterns and refining validation rules.

The authos is Vice President- Analytics, Optum Global Solutions

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