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Updated: Jun 28, 2026

Digital Home-Monitoring of Patients after Kidney Transplantation: The MACCS Platform

Digital Home-Monitoring of Patients after Kidney Transplantation: The MACCS Platform

Published on: April 12, 2021

Autonomous nursing professional development framework using blockchain technology.

Chia-Chen Lin¹, Yen-Heng Lin², I-Chieh Hsu³

¹Department of Computer Science and Information Engineering, National Chin-Yi University of Technology, Taichung, Taiwan. ally.cclin@ncut.edu.tw.

Scientific Reports

|March 3, 2026

Summary

This summary is machine-generated.

This study introduces a blockchain framework for nursing professional development, enhancing credential management security and autonomy. It ensures data integrity and efficient workforce management for healthcare institutions.

Keywords:

Adaptive healthcare institution Autonomous professional development Blockchain technology Nursing resource management Smart contract

Related Experiment Videos

Last Updated: Jun 28, 2026

Digital Home-Monitoring of Patients after Kidney Transplantation: The MACCS Platform

Digital Home-Monitoring of Patients after Kidney Transplantation: The MACCS Platform

Published on: April 12, 2021

Area of Science:

Healthcare Informatics
Blockchain Technology
Human Resource Management

Background:

Nursing credential management traditionally faces challenges in transparency and administrative efficiency.
Competency-based human resource management principles are crucial for professional development.
Existing systems may lack robust security and autonomy for managing nursing credentials.

Purpose of the Study:

To present a blockchain-based framework, BCeANPDF, for autonomous nursing professional development.
To enhance transparency, security, and professional autonomy in nursing credential management.
To integrate blockchain and smart contracts for independent credential verification and management.

Main Methods:

Development of a three-layer architecture (controller, service, repository) for BCeANPDF.
Implementation of seven smart contracts to automate credential verification, updates, and compliance.
Deployment of a prototype in a private blockchain environment for performance evaluation.

Main Results:

The BCeANPDF framework demonstrated stable and efficient operation in a private blockchain environment.
Average on-chain processing time per credential was 12.3 seconds; median query latency ranged from 5 to 9 ms.
The system achieved scalability and responsiveness comparable to Ethereum, ensuring data privacy and immutability.

Conclusions:

The BCeANPDF framework provides a practical approach to autonomous nursing professional development and flexible workforce management.
Decentralized trust mechanisms combined with credential management practices enhance data integrity and reduce administrative workload.
The framework supports the development of transparent, competency-oriented healthcare institutions without increasing operational complexity.