Event-driven integration of electronic medical records with blockchain and InterPlanetary file system

The integrity, security, and accessibility of electronic medical record (EMR) are often compromised by traditional systems, which struggle to ensure data integrity, transparent audit trails, and secure long-term storage. This research addresses these challenges by integrating EMR with a private blockchain and InterPlanetary file system (IPFS) cluster, using change data capture (CDC) for real-time updates and integrate with existing EMR systems, avoiding the need for building new EMR software. Implemented in the OpenEMR framework, the system's performance is evaluated across various processes, including document uploading, sharing, access, deletion, and integrity verification. Testing with anonymized medical records in PDF formats ranging from 1 MB to 100 MB shows that uploading to IPFS takes 0.7 seconds per MB, blockchain transaction processing averages 4.2 seconds, CDC time is 1.1 seconds per MB, and OpenEMR uploads average 0.98 seconds per MB. These results demonstrate significant improvements in data security, integrity, and availability, following the CIA triad principles. The system provides a traceable and secure solution for EMR management.

Authors

Publication Details

Journal
Bulletin of Electrical Engineering and Informatics
Published
2025-05-02
DOI
https://doi.org/10.11591/eei.v14i3.9355
Primary Topic
Scientific Computing and Data Management
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Event-driven integration of electronic medical records with blockchain and InterPlanetary file system

Sritrusta Sukaridhoto, Rizqi Putri Nourma Budiarti, Idris Winarno, Cahyo Arissabarno
Bulletin of Electrical Engineering and Informatics
Scientific Computing and Data Management
article

Event-driven integration of electronic medical records with blockchain and InterPlanetary file system

Sritrusta Sukaridhoto, Rizqi Putri Nourma Budiarti, Idris Winarno, Cahyo Arissabarno
article en

Abstract

The integrity, security, and accessibility of electronic medical record (EMR) are often compromised by traditional systems, which struggle to ensure data integrity, transparent audit trails, and secure long-term storage. This research addresses these challenges by integrating EMR with a private blockchain and InterPlanetary file system (IPFS) cluster, using change data capture (CDC) for real-time updates and integrate with existing EMR systems, avoiding the need for building new EMR software. Implemented in the OpenEMR framework, the system's performance is evaluated across various processes, including document uploading, sharing, access, deletion, and integrity verification. Testing with anonymized medical records in PDF formats ranging from 1 MB to 100 MB shows that uploading to IPFS takes 0.7 seconds per MB, blockchain transaction processing averages 4.2 seconds, CDC time is 1.1 seconds per MB, and OpenEMR uploads average 0.98 seconds per MB. These results demonstrate significant improvements in data security, integrity, and availability, following the CIA triad principles. The system provides a traceable and secure solution for EMR management.

Bulletin of Electrical Engineering and InformaticsVol. 14(3)
Openalex Percentile: Top 90%
Scientific Computing and Data Management
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Event-driven integration of electronic medical records with blockchain and InterPlanetary file system — Sritrusta Sukaridhoto, Rizqi Putri Nourma Budiarti, et al. · Bulletin of Electrical Engineering and Informatics (2025) | TGRS Research Map | TGRS