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. 2017:2017:9519321.
doi: 10.1155/2017/9519321. Epub 2017 May 16.

A Granular Ontology Model for Maternal and Child Health Information System

Saadia Ismail  1 , Majed Alshmari  2 , Khalid Latif  3 , Hafiz Farooq Ahmad  2
Affiliations

A Granular Ontology Model for Maternal and Child Health Information System

Saadia Ismail et al. J Healthc Eng. 2017.

Abstract

In several developing countries, maternal and child health indicators trail behind the international targets set by the UN as Millennium or Sustainable Development Goals. One of the reasons is poor and nonstandardized maternal health record keeping that affects data quality. Effective decision making to improve public healthcare depends essentially on the availability of reliable data. Therefore, the aim of this research is the design and development of the standard compliant data access model for maintaining maternal and child health data to enable the effective exchange of healthcare data. The proposed model is very granular and comprehensive in contrast with existing systems. To evaluate the effectiveness of the model, a web application was implemented and was reviewed by healthcare providers and expectant mothers. User feedback highlights the usefulness of the proposed approach as compared to traditional record-keeping techniques. It is anticipated that the proposed model will lay a foundation for a comprehensive maternal and child healthcare information system. This shall enable trend analysis for policy making to help accelerate the efforts for meeting global maternal and child health targets.

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Figures

Figure 1
Figure 1
Patient resource model from HL7 FHIR.
Figure 2
Figure 2
Proposed maternal and child health record system architecture.
Figure 3
Figure 3
MongoDB physical data model.
Figure 4
Figure 4
A patient resource as JSON document.
See this image and copyright information in PMC

References

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