Blockchain-Driven Supply Chain Finance for Public Healthcare in India: Enhancing Financial Resilience in Public Health Systems
DOI:
https://doi.org/10.56294/saludcyt20251400Keywords:
Blockchain, Machine Learning, Healthcare, Supply Chain Finance, Public Health, IndiaAbstract
Introduction: Public healthcare systems in India face persistent inefficiencies, including delays in financial workflows, lack of transparency, and fraud, particularly in rural and underserved areas. Blockchain and machine learning (ML) technologies offer transformative potential to address these challenges by enhancing transparency, efficiency, and accountability in healthcare supply chains.
Methods: A mixed-methods approach was adopted, combining structured surveys, semi-structured interviews, and secondary data analysis. Quantitative data were analysed using techniques such as descriptive statistics, predictive modelling (Random Forest), clustering (K-means), and anomaly detection (Isolation Forest). Qualitative data from stakeholder interviews were analysed using Natural Language Processing (NLP) to identify recurring themes and sentiment trends.
Results: The analysis revealed significant inefficiencies and readiness disparities among stakeholders. Blockchain was identified as a critical tool for improving transparency, with readiness levels being the strongest predictor of adoption success. ML demonstrated robust capabilities in fraud detection, with 5% of transactions flagged as anomalies, and predictive modelling identified key factors influencing readiness. Clustering analysis revealed distinct groups of stakeholders, highlighting the need for tailored interventions to bridge readiness gaps. Sentiment analysis indicated 65% of stakeholders held positive views on blockchain and ML adoption.
Conclusion: Blockchain and ML technologies have the potential to transform public healthcare financing by addressing inefficiencies, enhancing transparency, and optimizing resource allocation. However, disparities in stakeholder readiness necessitate targeted capacity-building and phased implementation strategies. These findings provide a roadmap for integrating blockchain and ML into public healthcare systems, fostering financial resilience and improving service delivery in rural and underserved areas.
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