A Proposed Biomedical Data Policy Framework to Reduce Fragmentation, Improve Quality, and Incentivize Sharing in Indian Healthcare in the era of Artificial Intelligence and Digital Health
Summary: arXiv:2604.11125v1 Announce Type: new
Abstract
India generates vast biomedical data through various sources, including postgraduate research, government hospital services, audits, government schemes, private hospitals and their electronic medical record (EMR) systems, insurance programs, and standalone clinics. However, these resources are often fragmented across institutional silos and vendor-locked EMR systems. The fundamental bottleneck is not technological but rather economic and academic in nature. There exists a systemic misalignment of incentives that makes data sharing a high-risk, low-reward activity for individual researchers and institutions.
Until India’s academic promotion criteria, institutional rankings, and funding mechanisms explicitly recognize and reward data curation as professional work, the nation’s ambitions in artificial intelligence (AI) will remain constrained by fragmented, non-interoperable datasets.
Proposed Multi-Layered Incentive Architecture
To address these challenges, we propose a comprehensive multi-layered incentive architecture that includes:
- Recognition of data papers in National Medical Commission (NMC) promotion criteria.
- Incorporation of open data metrics into the National Institutional Ranking Framework (NIRF).
- Adoption of Shapley Value-based revenue sharing in federated learning consortia.
- Establishment of institutional data stewardship as a mainstream professional role.
Addressing Barriers to Data Sharing
The proposed framework also tackles critical barriers to data sharing, which include:
- Fear of data quality scrutiny.
- Concerns about misinterpretation of data.
- Selective reporting bias.
To mitigate these issues, we recommend the implementation of:
- Mandatory data quality assessments.
- Structured peer review processes.
- Academic credit for roles involved in auditing data.
Regulatory Considerations
This proposed framework takes into account the regulatory constraints introduced by the Digital Personal Data Protection Act 2023 (DPDPA). It also aims to constructively engage with existing policies and guidelines, such as:
- The National Data Sharing and Accessibility Policy (NDSAP).
- Biotech-PRIDE Guidelines.
- The Anusandhan National Research Foundation (ANRF) guidelines.
Conclusion
In conclusion, the establishment of a well-structured biomedical data policy framework is crucial for mitigating fragmentation, improving data quality, and incentivizing sharing within the Indian healthcare sector. By aligning the incentives for researchers and institutions with national goals in AI and digital health, India can leverage its vast biomedical data resources more effectively, ultimately enhancing healthcare outcomes across the nation.