How Artificial Intelligence in enhancing maternal healthcare delivery in India?

 

Q. Discuss the role of Artificial Intelligence in enhancing maternal healthcare delivery in India. How can it be integrated into the public health system responsibly?

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Introduction

Artificial Intelligence (AI) has emerged as a transformative force in healthcare. In maternal health, AI can play a pivotal role in early diagnosis, personalised care, real-time monitoring, and better risk prediction—critical factors in a country like India where maternal mortality remains a significant concern despite progress under schemes like Janani Suraksha Yojana and LaQshya.

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Role of AI in Enhancing Maternal Healthcare

1. Early Risk Prediction and Screening

   • AI models can analyse antenatal data to predict complications such as pre-eclampsia, gestational diabetes, and postpartum haemorrhage.

   • Algorithms can alert ASHA workers or doctors about high-risk pregnancies well in advance.

2. Ultrasound and Imaging Assistance

   • Tools like SonoCNS can automatically capture fetal heart/brain images and offer precise biometrics, aiding diagnosis even in remote settings.

   • AI supports foetal anomaly detection with higher accuracy and speed.

3. Real-time Foetal Monitoring

   • AI-powered monitoring during labour can reduce stillbirths by promptly identifying abnormal foetal heart patterns.

4. Optimising Fertility Treatments

   • In IVF, AI helps identify the most viable oocytes/embryos and improve implantation success rates.

5. Health Records and Data Integration

   • AI can unify fragmented Electronic Medical Records (EMRs) to provide a seamless patient history across public health systems.

6. Decision Support Systems

   • AI chatbots or tools can assist rural health workers in triaging maternal cases or interpreting symptoms.

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Challenges to Responsible Integration

1. Data Privacy and Consent

   • Maternal health data is sensitive. Robust data protection laws and informed consent protocols are essential.

2. Algorithmic Bias

   • AI trained on non-representative data can lead to inequitable outcomes for certain communities (e.g., tribal women).

3. Infrastructure Gaps

   • Many PHCs lack electricity or internet, posing challenges for AI-based interventions.

4. Human-AI Collaboration

   • Over-reliance on AI can lead to errors. AI should augment, not replace, human decision-making.

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Steps for Responsible Integration into Public Health

1. National AI Framework for Health

   • Develop a policy framework under the National Health Mission (NHM) to regulate AI deployment in maternal care.

2. Public-Private Partnerships

   • Collaborate with startups and hospitals to pilot AI tools in high-burden districts before scale-up.

3. Training and Capacity Building

   • Equip ANMs, ASHA workers, and rural doctors with skills to use AI tools effectively and responsibly.

4. Data Localisation and Protection

   • Ensure data collected remains within Indian servers and is de-identified for AI training purposes.

5. Customised AI Models

   • Train AI systems on Indian population datasets, reflecting diversity in health parameters and outcomes.

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Conclusion

AI in maternal healthcare has the potential to accelerate India's journey towards achieving SDG 3.1 (Reduce maternal mortality) and Ayushman Bharat’s goals. However, for AI to deliver ethical and equitable outcomes, it must be human-centred, privacy-respecting, and grounded in public health realities. Responsible integration, especially in rural and marginalised areas, can be the next big leap for maternal healthcare in India.