NTR Vaidya Seva Trust slaps Rs 34.39 cr penalties on 203 network hospitals

VIJAYAWADA: The NTR Vaidya Seva Trust has imposed Rs 34.39 crore penalties on 203 NTR Vaidya Seva network hospitals for committing irregularities in treatment, billing and compliance with prescribed standards from 2024-25 to 2026-27.

The Trust has initiated 44 disciplinary actions, including the suspension of 25 hospitals, stoppage of payments to 13 hospitals, removal of five hospitals from its network, and cancellation of recognition of one hospital.

Trust CEO Padmavathi submitted a report on the action taken against the network hospitals to Health Minister Satya Kumar Yadav. The Trust is deploying artificial intelligence (AI)-based technology, in coordination with the National Health Authority (NHA), to identify suspicious claims, and strengthen the scrutiny of hospital bills.

The Trust is investigating complaints against hospitals collecting money for treatment that should be provided free of cost under the NTR Vaidya Seva Scheme, denying cashless treatment to eligible patients, delaying treatment and failing to follow prescribed medical protocols. Allegations of medical negligence, excessive use of treatment packages, and poor patient care are also being examined.

Complaints received through the Trust’s helpline 104 services and online platforms are verified by district coordinators and Trust officials. Medical records, treatment details, diagnostic reports and explanations from hospitals are examined before disciplinary committees recommend action. Depending on the findings, the Trust can impose penalties, recover amount paid against ineligible claims, withhold payments, suspend hospitals or remove them from its network. The Trust has around 1,000 private empanelled hospitals.

AI-based system to speed up health claim checks

The Trust currently scrutinises around 6,000 pre-authorisation requests, and 5,600 treatment bills daily with its existing workforce. Pre-authorisation requests undergo two-stage verification, while bills are checked at four levels. The heavy workload has contributed to delays in scrutiny and clearance of pending bills.

The AI-based system is expected to speed up verification, standardise scrutiny and reduce the backlog. It analyses high-value and high-risk claims, unusual billing patterns, duplicate submissions and possible alterations in medical records. Bills previously reduced or rejected are also considered during scrutiny.

Padmavathi clarified that an AI-generated alert will not, by itself, establish fraud. Each suspicious claim will be examined against medical records and supporting evidence before taking a final decision, she explained.

She said the measures are aimed at ensuring cashless treatment for all eligible beneficiaries, preventing improper payments and safeguarding public funds. Of the 203 hospitals against which action has been initiated during the coalition government’s tenure, 114 cases were taken up in the last six months. Penalty recovery and disciplinary proceedings are at various stages.

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