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Related Experiment Video

Updated: Jul 2, 2026

A Point-of-Care Method with Integrated Decision Support Tool to Estimate Anemia at Population Level

A Point-of-Care Method with Integrated Decision Support Tool to Estimate Anemia at Population Level

Published on: January 19, 2024

Database design and implementation for a PDA-based decision support system for screening and tailored care planning.

Nam-Ju Lee¹, Elizabeth Chen, Eneida A Mendonca

¹School of Nursing, Columbia University, USA.

AMIA ... Annual Symposium Proceedings. AMIA Symposium

|August 13, 2008

Summary

This study details the database architecture for the Mobile Decision Support for Advanced Practice Nursing (MODS-APN) system. It uses 6 Microsoft Access databases for data management and user interfaces on personal digital assistants (PDAs).

Related Experiment Videos

Last Updated: Jul 2, 2026

A Point-of-Care Method with Integrated Decision Support Tool to Estimate Anemia at Population Level

A Point-of-Care Method with Integrated Decision Support Tool to Estimate Anemia at Population Level

Published on: January 19, 2024

Area of Science:

Nursing Informatics
Health Information Technology
Database Architecture

Background:

Advanced Practice Nursing (APN) students require effective tools for patient screening and care planning.
Personal Digital Assistant (PDA)-based Decision Support Systems (DSS) offer potential for mobile health solutions.
Efficient data management is crucial for the functionality of mobile health applications.

Purpose of the Study:

To describe the database architecture of the Mobile Decision Support for Advanced Practice Nursing (MODS-APN) system.
To outline the components and functions of the MODS-APN database for APN student use.
To detail the data storage, synchronization, and reporting capabilities within the system.

Main Methods:

Development of a database architecture comprising 6 Microsoft Access databases.
Implementation of data storage mechanisms for patient information and care plans.
Integration of synchronization protocols for data consistency across devices.
Design of reporting functionalities for user and system performance analysis.
Creation of PDA user interfaces for seamless interaction with the DSS.

Main Results:

A robust database architecture was established for the MODS-APN system.
The system effectively supports data storage, synchronization, and reporting functions.
PDA user interfaces were successfully integrated for student use.
The architecture facilitates screening and tailored care planning for APN students.

Conclusions:

The described database architecture provides a foundation for the MODS-APN DSS.
The system's design supports the educational and clinical needs of APN students.
This architecture is scalable and adaptable for future enhancements in mobile health decision support.