A Research Framework for Modernizing Thalassemia Data Ecosystems under India’s Digital Health Mission

Abstract

India’s healthcare landscape is undergoing a significant transformation, yet the management of chronic diseases like Thalassemia remains encumbered by fragmented, insecure, and non-standardized patient data. This fragmentation hinders effective care coordination and prevents seamless integration with the nation’s ambitious digital health vision. This paper presents a novel research framework for a modern, interoperable Thalassemia data ecosystem designed to integrate with India’s Ayushman Bharat Digital Mission (ABDM). The framework leverages Health Level 7 (HL7) Fast Healthcare Interoperabil- ity Resources (FHIR) for data standardization, ensures robust privacy through compliance with the Digital Personal Data Protection (DPDP) Act, 2023, and proposes a multi-stakeholder architecture connecting patients, clinicians, blood banks, and donors. The primary contribution of this research lies in its disease-specific focus for ABDM integration, its privacy-centric design, and its patient-empowerment approach through a mobile- first strategy. By establishing a standardized and secure data exchange, this framework has the potential to significantly improve data accessibility, enhance patient safety, and enable superior care coordination for Thalassemia management across India, serving as a model for other chronic diseases.

Introduction

Thalassemia is a major chronic disease in India that requires lifelong management through regular blood transfusions and iron chelation therapy. However, the current health record management for Thalassemia patients is fragmented, largely paper-based, and siloed across hospitals and blood banks, making continuity of care difficult and compromising patient safety. To address these systemic issues, the Government of India introduced the Ayushman Bharat Digital Mission (ABDM)—a national initiative aimed at creating a unified, interoperable digital health ecosystem. Central to this mission is the ABHA (Ayushman Bharat Health Account), a unique digital health ID that enables secure sharing of patient records. The ABDM promotes open standards such as HL7 FHIR to ensure semantic interoperability across health systems.

Despite this national framework, a significant gap remains: there is no disease-specific, interoperable, secure data ecosystem tailored to the needs of Thalassemia patients. Existing Thalassemia platforms operate in isolation, lack integration with ABDM, and fail to meet modern standards for interoperability and privacy. Furthermore, the implementation of India’s DPDP Act (2023) requires robust mechanisms for consent and data security—something current systems do not adequately support.

To bridge these gaps, the paper proposes a comprehensive research framework and system architecture for a modern Thalassemia data ecosystem aligned with ABDM. The architecture includes four layers:

1. Data Layer – A federated database model using cloud-native technologies (e.g., Supabase/PostgreSQL) to store patient, clinical, and blood-bank data.

2. Standardization Layer – Creation of Thalassemia-specific HL7 FHIR profiles for transfusion history, chelation therapy, genetic data, and clinical summaries.

3. Interoperability Layer – Integration with the ABDM network using ABHA, Health Information Exchange & Consent Manager (HIE-CM), and Federated Health Records.

4. Application Layer – Web portals for clinicians and blood banks, and mobile apps for patients and donors to access records, track treatment, and coordinate blood donation.

All layers are governed by a strict Security and Privacy Layer ensuring RBAC, encryption, consent management, and audit trails in compliance with the DPDP Act.

The implementation strategy includes four phases: developing FHIR profiles, building core system components, integrating with the ABDM sandbox, and evaluating usability, interoperability, and system performance. The literature review highlights progress in digital health, Thalassemia management systems, and data privacy laws, but identifies the absence of a unified, ABDM-aligned, interoperable, and privacy-compliant Thalassemia framework—precisely the gap this research aims to fill.

Conclusion

This paper has presented a comprehensive research frame- work for modernizing Thalassemia data ecosystems in India, designed to integrate seamlessly with the Ayushman Bharat Digital Mission. The framework addresses a critical gap in the current healthcare landscape by proposing a disease-specific, interoperable, and privacy-preserving digital health solution. The primary contributions of this research are multifaceted. First, it provides a detailed architectural blueprint for a multi- stakeholder Thalassemia data ecosystem that connects patients, clinicians, blood banks, and donors. Second, it demonstrates the practical application of HL7 FHIR for creating disease- specific data profiles, thereby enabling semantic interoper- ability. Third, it offers a concrete model for implementing the requirements of the Digital Personal Data Protection Act, 2023, within a complex health information system. Fourth, it emphasizes a patient-centric approach through a mobile-first strategy, empowering patients to actively participate in their care. The novelty of this framework lies not only in its technical design but also in its holistic approach to addressing the chal- lenges of chronic disease management in a developing country context. By aligning with the national digital health vision (ABDM) while addressing the specific needs of Thalassemia care, this research provides a replicable model that can be adapted for other chronic diseases. The anticipated outcomes, including improved data accessibility, enhanced security, and better care coordination, have the potential to significantly improve the quality of life for Thalassemia patients across India. Future work will focus on several key areas. The completion of the pilot deployment and the collection of real-world data will provide valuable insights into the system’s performance and user acceptance. The integration of artificial intelligence and machine learning techniques for predictive analytics, such as forecasting transfusion schedules and identifying patients at risk of complications, represents a promising avenue for enhancing the system’s capabilities. Expanding the donor management module to create a more robust and responsive blood donation network is another important goal. Finally, conducting a large-scale, multi-center study to assess the clinical impact of the system on patient outcomes will be essential for demonstrating its value and informing policy decisions. In conclusion, this research framework represents a signif- icant step towards a more integrated, efficient, and patient- centered digital health ecosystem for Thalassemia manage- ment in India. By leveraging modern technologies, adhering to international standards, and prioritizing patient privacy, this framework has the potential to transform the landscape of chronic disease care and contribute to the broader goals of universal health coverage and equitable access to quality healthcare.

References

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Copyright

Copyright © 2025 Mehul Pradeep Pardeshi, Siddhesh Sambhaji Rajale, Divyesh Ravindra Mali, Simran Vinod Gade. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.