A Granular Ontology Model for Maternal and Child Health Information System

Area of Science:

• Public Health
• Health Informatics
• Data Management

Background:

• Maternal and child health indicators in developing countries lag behind global targets.
• Poor and nonstandardized health record keeping compromises data quality, impacting effective healthcare decision-making.
• Reliable data is essential for improving public healthcare services.

Purpose of the Study:

• To design and develop a standard-compliant data access model for maternal and child health data.
• To enable effective exchange of healthcare data for improved public health.
• To lay the foundation for a comprehensive maternal and child healthcare information system.

Main Methods:

• Development of a granular and comprehensive data access model.
• Implementation of a web application to demonstrate the model's functionality.
• Evaluation of the model through reviews by healthcare providers and expectant mothers.

Main Results:

• User feedback indicated the proposed model is more useful than traditional record-keeping methods.
• The model facilitates a more granular and comprehensive approach to maintaining maternal and child health data.
• The implemented web application successfully showcased the model's potential.

Conclusions:

• The proposed data model enhances maternal and child health data quality and exchange.
• This approach can support trend analysis for policy-making to meet global health targets.
• The model provides a foundation for a robust maternal and child healthcare information system.