Use of artificial intelligence and machine learning is made for a comprehensive fraud analytics solution to detect fraud pro-actively, develop algorithms that can be used on large volume of data to identify suspect transactions and entities and risk scoring of hospitals and claims, Lok Sabha was informed on Friday.
Ayushman Bharat-Pradhan Mantri Jan Arogya Yojana (AB-PMJAY) is governed on a zero-tolerance approach to any kind of fraud such as suspect or non-genuine medical treatment claims, impersonation and up-coding of treatment packages and procedures etc, Minister of State for Health Bharati Pravin Pawar said in a written reply.
Responding to a question on whether it is a fact that around 23,000 fraudulent transaction were recorded at empanelled hospitals under the AB-PMJAY in 2021-22, she said the National Health Authority - the implementing agency of AB-PMJAY has issued a comprehensive set of anti-fraud guidelines. Anti-fraud advisories are issued to states and Union territories. National Anti-Fraud Unit is created at NHA for overall monitoring and implementation of anti-fraud framework supported by state anti-fraud units at state level.
All claims require mandatory supporting documents along-with on-bed patient photo before approval and payment. The feature of Aadhaar-based biometric verification of beneficiary at the time of admission and discharge is launched at all private hospitals.
"Use of artificial intelligence and machine learning is made for a comprehensive fraud analytics solution to detect fraud pro-actively, develop algorithms that can be used on large volume of data to identify suspect transactions and entities and risk scoring of hospitals and claims," Mr Pawar stated.
Providing details of action taken by state health agencies, she said Chhattisgarh accounts for the highest number of claims in which which penal actions were taken for fraudulent hospital transactions under the AB-PMJAY followed by Madhya Pradesh, Punjab, Kerala and Jharkhand.
(Except for the headline, this story has not been edited by NDTV staff and is published from a syndicated feed.)
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