Emerging Trends in Healthcare Fraud Detection Market by Types, Revenue, Industry

Posted by Kriti on January 16th, 2020

The growth of the market is attributed to a large number of fraudulent activities in healthcare; increasing number of patients seeking health insurance; the prepayment review model; growing pressure of fraud, waste, and abuse on healthcare spending; and high returns on investment.

The overall healthcare fraud detection market is expected to grow from 2,242.7 million by 2022 from USD 504.4 million in 2016, at a CAGR of 28.9% from 2017 to 2022.

+ Market Dynamics 

+ Drivers

+ Large Number of Fraudulent Activities in Healthcare
+ Increasing Number of Patients Seeking Health Insurance
+ Prepayment Review Model
+ Growing Pressure of Fraud, Waste, and Abuse on Healthcare Spending
+ High Returns on Investment

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“The descriptive analytics segment is expected to dominate the market in 2017”
Thehealthcare fraud detection market is segmented descriptive, predictive, and prescriptive analytics. In 2017, the descriptive analytics segment is expected to account for the largest share of the healthcare fraud detection market. Descriptive analytics forms the base for the effective application of predictive or prescriptive analytics. Thus, descriptive analytics is expected to continue to dominate the healthcare fraud detection market during the forecast period.

“The insurance claims review segment is expected to dominate the market in 2017”

The healthcare fraud detection market is segmented into insurance claims review, payment integrity, and other applications. The insurance claims review segment is expected to dominate the healthcare fraud detection market with a share in 2017. This segment is also expected to register the highest growth rate during the forecast period, primarily due to the increasing number of patients seeking health insurance, rising number of fraudulent claims, and growing adoption of the prepayment review model.

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https://www.marketsandmarkets.com/PressReleases/healthcare-fraud-detection.asp