Date: 2026-05-08Category: Press ReleaseState: Union GovernmentCountry: India
National Health Authority convenes Day 1 of AB PM-JAY Auto-Adjudication Hackathon Showcase 2026; AI-driven innovations in claims adjudication take centre stage
**Executive Summary**
The Ministry of Health and Family Welfare, in collaboration with the NHA, IndiaAI Mission, and IISc Bengaluru, inaugurated the two-day AB PM-JAY Auto-Adjudication Hackathon Showcase 2026 on May 8, 2026. The event aims to leverage artificial intelligence to enhance the efficiency, transparency, and integrity of health claims management under the Ayushman Bharat PM-JAY scheme. Key objectives include the demonstration of AI-driven solutions for automated document classification, radiological correlation, and fraud detection to build a future-ready adjudication framework.
**Key Points / Main Content**
**Event Purpose and Strategic Vision**
* The showcase focuses on integrating AI-enabled solutions into the AB PM-JAY infrastructure to reduce manual effort and accelerate claims processing.
* India is highlighted as one of the first countries in the Global South to establish a Health AI benchmarking platform.
* The initiative utilizes "BODH," an Open Benchmarking and Data Platform for Health AI at IIT Kanpur, for validating AI solutions against India-specific datasets.
**AI Solutions for Claims Adjudication**
* **Clinical Document Classification:** Systems demonstrate automated classification of healthcare documents using multilingual OCR to extract structured clinical and billing data from low-quality scans.
* **Compliance Verification:** AI tools identify mandatory visual markers, such as institutional stamps and signatures, ensuring alignment with Standard Treatment Guidelines (STGs).
* **Radiological Image Correlation:** Assistive AI tools interpret X-rays, CT scans, and MRIs to correlate findings with clinical reports and validate diagnoses and treatment timelines.
* **Fraud and Forgery Detection:** AI/ML-driven systems detect anomalies including tampered discharge summaries, manipulated billing records, ghost beneficiaries, and deepfake-altered medical reports.
**Technical and Policy Deliberations**
* Discussions prioritized the use of Small Language Models (SLMs), Large Language Models (LLMs), and multimodal AI for low-resource and local language settings.
* Key focus areas for scaling AI include workflow integration, privacy safeguards, quality datasets, and edge deployment.
**Impact Analysis**
**National Health Authority (NHA)**
**Impact**
The NHA benefits from a strengthened health system with improved programme integrity and a scalable framework for digital claims adjudication.
**Action Required**
The NHA must continue to promote AI in healthcare and integrate the demonstrated innovative digital solutions into the existing AB PM-JAY infrastructure.
**Empanelled Hospitals**
**Impact**
Hospitals stand to benefit from more transparent adjudication processes and timely settlements of claims.
**Action Required**
Hospitals must ensure that clinical documentation and billing records are accurate and comply with Standard Treatment Guidelines to facilitate AI-driven validation.
**AI Startups and Innovators**
**Impact**
These stakeholders gain a platform to showcase cutting-edge solutions and collaborate with policymakers to solve complex healthcare challenges.
**Action Required**
Innovators need to focus on developing scalable, explainable AI outputs that align with policy compliance frameworks and privacy safeguards.
**Insurers and Third Party Administrators (TPAs)**
**Impact**
They receive advanced tools to enhance decision-making speed and accuracy while safeguarding against fraudulent claims.
**Action Required**
These entities must adopt and integrate AI/ML-driven systems into their workflows to identify anomalies and fraudulent patterns in medical documentation.
Key Entities Referenced
Ayushman Bharat Pradhan Mantri Jan Arogya Yojana (AB PM-JAY): India's flagship public health insurance scheme which is the primary focus for AI-driven health claims management and auto-adjudication innovations.
National Health Authority (NHA): The nodal agency responsible for implementing AB PM-JAY and the primary organizer of the hackathon to integrate AI into health systems.
AB PM-JAY Auto-Adjudication Hackathon Showcase 2026: A national initiative and event focused on leveraging artificial intelligence and machine learning to automate and strengthen health claims adjudication.
BODH (Open Benchmarking and Data Platform for Health AI): A digital public good platform developed at IIT Kanpur for validating AI solutions against India-specific datasets.
Standard Treatment Guidelines (STGs): The established clinical frameworks and policy compliance documents used to validate claimed diagnoses and treatment timelines during adjudication.
Ministry of Health and Family Welfare
National Health Authority convenes Day 1 of AB
PM-JAY Auto-Adjudication Hackathon Showcase
2026; AI-driven innovations in claims
adjudication take centre stage
India among first in Global South to develop Health AI
benchmarking platform: Dr. Sunil Kumar Barnwal, CEO, NHA
“Robust AI-enabled adjudication to enhance transparency,
efficiency and programme integrity under AB PM-JAY”
From OCR to deepfake detection: AI innovations showcased
to strengthen claims management under AB PM-JAY
Posted On: 08 MAY 2026 3:53PM by PIB Delhi
The Ministry of Health and Family Welfare (MoHFW), in collaboration with the National Health
Authority (NHA), IndiaAI Mission, and the Indian Institute of Science (IISc), Bengaluru, today
inaugurated the AB PM-JAY Auto-Adjudication Hackathon Showcase 2026, marking the commencement
of a two-day national event focused on leveraging artificial intelligence (AI) to strengthen health claims
management under Ayushman Bharat Pradhan Mantri Jan Arogya Yojana (AB PM-JAY).
The inaugural day brought together policymakers, technology innovators, insurers, Third Party
Administrators (TPAs), healthcare providers, academia, and AI startups to deliberate and demonstrate
cutting-edge AI-enabled solutions aimed at enhancing efficiency, transparency, and integrity in claims
adjudication.Speaking at the Inaugural Session, Dr. Sunil Kumar Barnwal, Chief Executive Officer, National Health
Authority, stated that the initiative presents a significant opportunity not only to strengthen healthcare
delivery under Ayushman Bharat PM-JAY, but also to enhance the overall efficiency and effectiveness of
the healthcare ecosystem through technology.
He emphasized that innovation is distributed across society—spanning institutions, academia, startups,
and industry—and initiatives such as hackathons help harness this collective potential to solve complex
healthcare challenges.
Dr. Barnwal highlighted that NHA has been actively promoting AI in healthcare, including the
development of BODH, an Open Benchmarking and Data Platform for Health AI at IIT Kanpur, launched
during the IndiaAI Impact Summit. He noted that India is among the first countries in the Global South to
establish such a platform for validating AI solutions against India-specific datasets, as a digital public
good.
He further highlighted that robust and transparent claims adjudication is central to building trust among
empanelled hospitals, ensuring timely settlements, and improving programme integrity. He added that the
vast and diverse data generated under AB PM-JAY offers immense potential for leveraging AI to further
strengthen efficiency, transparency, and outcomes.
A major highlight of the showcase was the presentation of advanced AI/ML-based solutions developed
under the hackathon across three critical problem statements, each addressing core challenges in claims
adjudication and programme integrity under AB PM-JAY.
The first problem statement focused on Clinical Document Classification and Compliance with Standard
Treatment Guidelines (STGs). Winning teams demonstrated sophisticated solutions capable of automated
classification of diverse healthcare documents, coupled with multilingual Optical Character Recognition
(OCR) applied to low-quality and heterogeneous scans. These systems were able to extract structured
clinical and billing data with associated confidence scores and provenance tracking. Additionally, the
solutions exhibited the ability to identify mandatory visual markers such as institutional stamps and
authorised signatures, while generating explainable adjudication outputs aligned with Standard Treatment
Guidelines and policy compliance frameworks.The second problem statement addressed Radiological Image-Based Condition Detection and Report
Correlation. The winning teams showcased assistive AI tools capable of interpreting complex radiological
data, including X-rays, CT scans, and MRIs. These solutions enable adjudicators to better understand
imaging outputs, correlate radiological findings with hospital-submitted clinical reports, and validate
claimed diagnoses, disease staging, and treatment timelines in accordance with established Standard
Treatment Guidelines, thereby enhancing both speed and accuracy in decision-making.
The third problem statement focused on Document Forgery and Deepfake Detection. Participating teams
presented robust AI/ML-driven systems designed to detect anomalies and fraudulent patterns in medical
documentation submitted during claims processing. These included identification of tampered discharge
summaries, manipulated billing records, ghost beneficiaries, and synthetically generated or altered
medical reports. Such solutions are expected to significantly strengthen digital claims adjudication
frameworks and safeguard programme integrity under AB PM-JAY.
The programme also featured a high-level panel discussion on “Building AI for Indian Healthcare”,
chaired by Shri S. Krishnan, Secretary, Ministry of Electronics and Information Technology. The panel
brought together distinguished representatives from government, healthcare technology enterprises,
academia, and the broader AI ecosystem to deliberate on practical pathways, policy considerations, and
operational strategies for the adoption and scaling of AI solutions within India’s healthcare system.
Discussions focused on the role of Small Language Models (SLMs), Large Language Models (LLMs) and
multimodal AI systems in addressing diverse healthcare use cases, particularly in low resource and local
language settings. Panellists also highlighted the importance of workflow integration, validation
frameworks, quality datasets, edge deployment, privacy safeguards and scalable implementation pathways
for AI solutions in healthcare delivery.
Shri S. Krishnan, Secretary, Ministry of Electronics and Information Technology, Ms. Jyoti Yadav, Joint
Secretary (PMJAY), National Health Authority; Prof. Govindan Rangarajan, Director, IISc Bengaluru
along with healthcare professionals, Academia, students and Innovators were present at the occasion.The AB PMJAY Auto-Adjudication Hackathon aims to drive innovative digital solutions that seamlessly
integrate with existing AB-PMJAY infrastructure, reduce manual effort, speed up processing, and build a
scalable, future-ready adjudication framework for the entire ecosystem.
Through this initiative, the National Health Authority reaffirms its commitment to harnessing responsible
Artificial Intelligence to strengthen health systems, improve efficiency in claims management and support
transparent and technology-driven healthcare delivery under AB PM-JAY.
*****
SR
HFW- AB PM-JAY Auto-Adjudication Hackathon Showcase 2026 commenced /8th May 2026/2
(Release ID: 2259047) Visitor Counter : 304
Read this release in: Urdu , Marathi , ही , Tamil , Kannada