Healthcare fraud detection market has been expanding due to the increasing incidence of healthcare fraud that has led to greater burdens for the healthcare industry as well as reimbursement infrastructure. The fraud essentially involves misrepresentation and intentional submission of false claims. For instance, a fraud physician, in alliance with a pharmacy can add more expensive medicines to a prescription without the knowledge of the patient. National Healthcare Anti-Fraud Association opines that most of such frauds are committed by a small number of healthcare providers and mostly by organized crime groups. Healthcare fraud detection market has found impetus in the fact that healthcare fraud results in higher costs for patients, reduces profit margins of payers, and causes havoc for taxpayer dollars that support public health insurance companies.
According to experts, though the size of the U.S. healthcare industry is nearly $2.7 trillion, much of the revenue is wasted through mismanagement and fraud. Some of the common fraudulent behaviors include illegal medical billing practices that falsify claims, claiming of multiple claims by different providers for the same patient, stealing of patient identities to gain reimbursement for medical services, patients and dishonest providers coming together to make false claims and sharing the monetary gains. Apparently, fraudulent billing leads to nearly 3%-10% of annual healthcare costs in the U.S. To restrain this increasing tendency for healthcare fraud, government as well as private agencies are resorting to solutions based on AI and predictive analysis that is expected to add impetus to healthcare fraud detection market. The global healthcare fraud detection market is expected to register a CAGR of 28.83% to reach USD 3,787.68 million by 2024.
Different segments of healthcare fraud detection market and growth implications:
The healthcare payment integrity market has been segmented into type, component, application, delivery model and end user.
Healthcare fraud detection market classification on the basis of descriptive analytics, prescriptive analytics and predictive analytics. These methods are used to mitigate various types of healthcare frauds. For instance, descriptive analytics analyzes historical data to scrutinize the changes. It reflects total revenue generated per patient, monthly sales growth and yearly pricing changes, thus precise maintenance of related records. Since the information can analyze the revenue cycle it is considered an efficient means of healthcare fraud.
Predictive analytics is yet another type of fraud detection technique that is built upon past data which includes fraud or non-fraud indicators as well as different elements such as bill amount, number of patients, treatment characteristics, years of experience of the doctor, reporting lags and the number of patient visits.
On the basis of component, the market has been bifurcated into services and software. By application healthcare fraud detection market is classified as payment integrity and insurance claims review. End-user classification of healthcare fraud detection market comprises public or government agencies, private insurance payers and third party service providers.
North America to hold a significant share in healthcare fraud detection market
Healthcare fraud detection market has been classified geographically as the Americas, Europe, Asia Pacific and the Middle East & Africa.
The Americas accounted for a market share of 49.97% in 2018. Healthcare fraud has been rampant in the U.S. and recently the nation’s federal authorities have reported on breaking up a $1.2 billion Medicare scam through which fraudsters were peddling orthodontic braces to senior patients irrespective of whether they needed it. Apparently the scam was spread over various continents. Officials had been able to crackdown on the ring of fraudsters with the use of techniques used by credit card companies. As a result, the healthcare fraud detection market in North America has been growing at a significant pace.
Competitive Landscape:
Some of the significant players in the healthcare fraud detection market include IBM, DXC Technology Company, FAIR ISAAC Corporation, UNITEDHEALTH group, WIPRO LIMITED, LEXISNEXIS, EXLSERVICE Holdings, McKesson Corporation, Inc., SAS Institute Inc., CGI INC. and COTIVITI INC.
Combating healthcare scams to receive increased priority among public and private organizations
Recently, Centers for Medicare and Medicaid Services or CMS has submitted a RFI (Request for Information) to analyze how AI can help in enhancement of services. CMS aims to identify and prevent fraud, waste, and abuse and hopes that AI as well as other technologies can be leveraged to that end. CMS wants to conduct program integrity activities, reduce provider burden and to ensure proper claims payment.
AI technology can be utilized to detect fraud much faster than other conventional methods. Studies indicate that nearly $20 to $ 30 billion can be saved by US health insurance companies by avoiding waste through fraud. CMS is endeavoring to stop fraud before payment is made rather than the traditional pay and chase method used by government bodies.
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