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Related Experiment Video

Updated: May 14, 2026

Executing Complexity-Increasing Queries in Relational (MySQL) and NoSQL (MongoDB and EXist) Size-Growing ISO/EN 13606 Standardized EHR Databases

Executing Complexity-Increasing Queries in Relational (MySQL) and NoSQL (MongoDB and EXist) Size-Growing ISO/EN 13606 Standardized EHR Databases

Published on: March 19, 2018

An architecture model for multiple disease management information systems.

Lichin Chen¹, Hui-Chu Yu, Hao-Chun Li

¹Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, No. 1, Sec. 4, Roosevelt Road, Taipei, 10617, Taiwan, d98945012@ntu.edu.tw.

Journal of Medical Systems

|February 21, 2013

Summary

This study introduces a reusable information system architecture to improve disease management workflows. The new model significantly reduces development time and enhances case manager efficiency and decision-making.

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Last Updated: May 14, 2026

Executing Complexity-Increasing Queries in Relational (MySQL) and NoSQL (MongoDB and EXist) Size-Growing ISO/EN 13606 Standardized EHR Databases

Executing Complexity-Increasing Queries in Relational (MySQL) and NoSQL (MongoDB and EXist) Size-Growing ISO/EN 13606 Standardized EHR Databases

Published on: March 19, 2018

Area of Science:

Health Informatics
Healthcare Management
Software Engineering

Background:

Disease management programs aim to improve healthcare quality but face challenges with system fragmentation.
Case managers spend excessive time on documentation and care team coordination, highlighting the need for efficient tools.
Current information systems are often disease-specific, leading to inefficiencies in development and deployment.

Purpose of the Study:

To propose a reusable information system architecture model for disease management.
To optimize inefficient workflows and support case managers in their daily practice.
To enhance reusability and save time in information system development for disease management.

Main Methods:

Developed and implemented a novel architecture model for disease management information systems.
Evaluated the model through reusability analysis, time consumption analysis, and workflow analysis.
Assessed user satisfaction and system supportiveness via a questionnaire survey.

Main Results:

The proposed architecture model demonstrated high reusability.
Information system development time was reduced by over 50%.
Workflow analysis showed significant improvements, with positive user feedback on system support and decision-making empowerment.

Conclusions:

The reusable architecture model effectively addresses inefficiencies in disease management information system development.
The system empowers case managers, leading to improved daily workflows and better decision-making.
This approach offers a scalable and time-saving solution for developing disease management information systems.