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India: AI/ML to Mitigate Healthcare Fraud

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A report from the Comptroller and Auditor General of India (CAG) indicated that a significant number of patients who had previously been listed as deceased continued to avail of treatment under the Ayushman Bharat-Pradhan Mantri Jan Aarogya Yojana (AB-PMJAY). The Ministry of State of Health and Family Welfare has informed the Rajya Sabha that artificial intelligence and machine learning technologies are being deployed to identify suspicious transactions and potentially fraudulent activities within the framework of the AB-PMJAY scheme.

AB-PMJAY is a government initiative designed to offer free health insurance coverage to individuals with low income, ensuring their access to essential medical services. As of 1 August 2023, 233 million Ayushman cards were created under the scheme.

AI/ML technologies are being used to effectively identify and preempt instances of healthcare fraud throughout the implementation of the scheme. This strategic employment not only serves to counter fraudulent activities but also plays a crucial role in guaranteeing that eligible beneficiaries receive the appropriate medical treatment they are entitled to.

The implementation of these technologies involves collaborating with technology partners who are actively engaged in developing and implementing robust anti-fraud measures. By leveraging the capabilities of AI and ML, these partnerships focus on creating advanced systems that can identify irregularities, anomalies, and potentially fraudulent patterns within healthcare claims.

The states of Chhattisgarh, Haryana, Jharkhand, Kerala, and Madhya Pradesh documented the highest instances of such fraudulent cases. According to the report, data analysis of mortality cases in TMS revealed that 88,760 patients died while undergoing treatment covered by the scheme. A total of 214,923 claims are shown as paid in the system, related to fresh treatment for these patients. The audit further commented that 3,903 of the above claims amounting to IN₹ 69.7 million (US$ 838,689) pertaining to 3,446 patients were paid to hospitals.

Further data analysis showed that the same patient could be admitted to multiple hospitals during the same period of hospitalisation. Moreover, the report noted there was no mechanism to prevent patients from gaining admission to different hospitals during their hospitalisation period.

In July 2020, the National Health Authority (NHA) had already recognised this situation and explained that these issues also arise when a newborn was delivered in one hospital and then transferred to another hospital for neonatal care, using the mother’s PMJAY ID.

In contrast to the NHA’s explanation, the data analysis conducted by the CAG contradicted this reasoning. The analysis revealed that within the database, a total of 78,396 claims involving 48,387 patients were initiated. Notably, the date of discharge of these patients for earlier treatment was later than the admission date for another treatment of the same patient.

Among these patients, 23,670 were male. These cases were more prevalent in Chhattisgarh, Gujarat, Kerala, Madhya Pradesh, and Punjab. The report noted that the successful payment of such claims suggests lapses on the part of state health agencies (SHAs) in processing the claims without carrying out the necessary verifications.

The NHA attributed the problem to several factors, including discrepancies in computer date and time synchronisation, instances involving neo-natal babies, and the recording of pre-authorisation after the date of admission.


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