A startling number of healthcare fraud cases using false billings to Medicare and Medicaid are coming to the fore. A large number of these fraudulent activities entailed false bills of services which were never rendered. This situation can definitely be negated with the advent of AI. Advanced AI algorithms can be used in cases of financial fraud, insurance fraud and transaction fraud. Several trials have found that automated fraud detection systems using AI can negate financial losses, reduce auditors’ workloads and help generate greater resources for the patients. Here the machine learning program is fed with two subsets of billing data, one which is a bill generated by the physician and the other, some data of established fraudulent cases. The machine then draws out patterns and common inferences to detect fraud. Thus AI could present itself as a first line of defense and revolutionize the healthcare fraud detection market.
Big data and data analytics is another way by which a medical institution might compile data about what constitutes ‘normal’ patient buying behavior. If a patient is using services in a way that is atypical, hospitals can create blacklists. Fraud clusters of data can be ascertained using unsupervised machine learning. Highly advanced data mining techniques can then be used on fraud tactics that are found to be perfidious. The analysis done is highly impactful and is a powerful tool giving traction to the healthcare fraud detection market.
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Healthcare is an integral part of people’s lives and therefore it must be affordable. The healthcare industry is a highly complex system expanding at an expeditious pace with a wide range of moving components. Fraud in healthcare industry has become a critical problem in recent time, with misuse of medical insurance systems being the prime concern. As manual healthcare fraud detection is a strenuous task, healthcare firms are increasingly adopting healthcare fraud detection software equipped with machine learning and data mining techniques. The ability of healthcare fraud detection software to automatically identify healthcare frauds has been helping technology behind healthcare fraud detection gain immense traction.
Healthcare Fraud Detection Market- Notable Highlights
Some of the leading firms operating in healthcare fraud detection market include Optum, Verscend Technologies, Inc., DXC, Northrop Grumman, Fair Isaac Corporation, HCL Technologies Limited, LexisNexis, SAS Institute Inc., Pondera, Conduent, Inc., SCIOInspire, Corp., CGI Group Inc., Wipro Limited, IBM Corporation, McKesson Corporation, and others.
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Healthcare Fraud Detection Market- Market Dynamics
Burgeoning Fraud Cases in Healthcare Industry Creating Opportunities
The proliferating fraudulent activities in healthcare industry in tandem with growing number of patients eying healthcare insurance, have been propelling adoption of healthcare fraud detection software and services. The healthcare fraud detection market is likely to expand on the back of factors such as increasing pressure of fraud, waste, and abuse on healthcare spending, and high returns on investments. For instance, in 2017, government agencies said that their yearly healthcare fraud takedown included 400 charged individuals in healthcare fraud schemes, which accounted to USD 1.3BN in fake billings to Medicaid and Medicare.
Prepayment Review Model
The prepayment review model has transformed the healthcare industry for the better, even Medicare claims are examined by prepayment reviews. With this model, the Center for Medicare and Medicaid Services (CMS) can save money, while alleviating burden on hospitals. This model not just triggers system-wide process improvements, but also has a considerable positive impact on the cash flow of hospitals. With this model, government hold money until the claim confirmation becomes valid.
Though this variant of healthcare fraud detection model adds some burden on hospitals as the number of claims under review will dramatically increase with time, hospitals no longer need to worry about audits after getting payment as cash flow is stopped until claims get verified. Owing to myriad benefits of prepayment review model, hospitals are increasingly making system-wide operations enhancements for error free documentation and are deploying predictive modeling techniques.
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Healthcare Fraud Detection Market – Segmentation
The healthcare fraud detection market can be bifurcated on the basis of:
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