HEALTHLINK-Enhancing Access to Medical Information and Securing It
Abstract
During critical emergencies, failure to access a patient’s medical history can lead to hazardous delays, redundant tests, and added healthcare expenses. These gaps in medical information make it difficult for healthcare providers to provide timely and accurate care, ultimately affecting patient outcomes. HealthLink is a blockchain platform designed to solve this problem by providing a secure and decentralized way of storing and sharing patient medical records. Using IPFS and Pinata for decentralized storage and employing sophisticated encryption methods, HealthLink keeps sensitive medical information confidential and only accessible to authorized staff. Authenticated hospitals, approved by a government-appointed administrator, can safely access and modify patient records using biometric scans, like fingerprint identification, or NFT-based identity cards. This enables hospitals to rapidly access a patient’s medical history in emergency situations, minimizing the requirement for repeated tests, accelerating diagnosis, and enhancing treatment outcomes. Moreover, HealthLink has an interactive map that allows users to simply find and book appointments at nearby verified hospitals and testing facilities. This feature makes it easier for patients who need urgent care to be connected with the right resources in a timely manner. Through the facilitation of accessibility, sharing, and security of medical information, HealthLink seeks to revolutionize healthcare systems. The platform not only enhances patient outcomes and care but also builds higher levels of trust between patients and healthcare professionals. With HealthLink, we envision a future when healthcare is more efficient, quicker, and personalized cases.
Keywords:
HealthLink, IPFS, Pinata, NFT-based identity cards, fingerprint identificationPublished
Issue
Section
License
Copyright (c) 2025 International Journal on Emerging Research Areas

This work is licensed under a Creative Commons Attribution 4.0 International License.
All published work in this journal is licensed under the Creative Commons Attribution 4.0 International License (CC BY 4.0). This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
How to Cite
Similar Articles
- Benjamin Francis Thottam, Angela Mary Anil, Annu Maria Thomas, Ann Maria, Mekha Jose, Review on Applications Utilizing Traditional Farming Practices , International Journal on Emerging Research Areas: Vol. 5 No. 1 (2025): IJERA
- Ansamol Varghese, Anandhu Anoj, Angel Thomas, Deepta K Sunny, Emil Thomas, TrueNews-AI Powered Detection of Manipulated Text and Images , International Journal on Emerging Research Areas: Vol. 5 No. 1 (2025): IJERA
- Betzy Babu Thoppil, Anugrah Premachandran, Annapoorna M, Ashwin Mathew Zachariah, Bala Susan Jacob, Advanced Sensor-Based Landslide and Earthquake Detection and Alert System Utilizing Machine Learning and Computer Vision Technologies , International Journal on Emerging Research Areas: Vol. 4 No. 2 (2024): IJERA
- Dr Anil A R, Amit Sankar Arun, Anandhu Anilkumar, Anandu S Sivan, Anoop Manoharan, DESIGNING OF A VOICE – BASED PROGRAMMING IDE FOR SOURCE CODE GENERATION , International Journal on Emerging Research Areas: Vol. 4 No. 1 (2024): IJERA
- Arya Raj S, R Gopika Krishnan, Drishya Das, Rohith R, Jocelyn Ann Joseph, Personality Profiling Using CV Analysis , International Journal on Emerging Research Areas: Vol. 4 No. 1 (2024): IJERA
- Anoop Joshy, Ajay Jacob Benny, Athul Sajeev, SD Anakha, FEEDO:AIoT based Automatic Fish Feeding System , International Journal on Emerging Research Areas: Vol. 5 No. 1 (2025): IJERA
- Jimmy Mathew, Jovin J George, Dr. Jacob John, Jaick T. Kurian, Karun Jidhish, ImmunoConnect: A Smarter Way to Manage Immunization , International Journal on Emerging Research Areas: Vol. 5 No. 1 (2025): IJERA
- Ansamol Varghese, Anoushkha Tresa, Athira John, Ignatious Ealias Roy, M S Gautham Sankar, A Machine Learning Approach to Fake News Detection , International Journal on Emerging Research Areas: Vol. 3 No. 1 (2023): IJERA
- Prof. Manoj T Joy, Noel Shaji, Sharon Sunil, Thomas Johanson, Ridhin Joseph, IoT-Based Smart Aquaponics System with Remote Monitoring and Actuator Control , International Journal on Emerging Research Areas: Vol. 4 No. 1 (2024): IJERA
- Sandra Raju, Dr S Sruthy, A Reliable Method for Detecting Brain Tumors in Magnetic Resonance Images Utilizing EfficientNet , International Journal on Emerging Research Areas: Vol. 3 No. 1 (2023): IJERA
You may also start an advanced similarity search for this article.
