Knowledge and Data Science Research Centre (KDRC)
A centre of excellence in digital research.
HL7 and its members provide a framework (and related standards) for the exchange, integration, sharing, and retrieval of electronic health information. These standards define how information is packaged and communicated from one party to another, setting the language, structure and data types required for seamless integration between systems. HL7 standards are recognized as the most commonly used in the world.
Effective decision-making to improve healthcare for people depends essentially upon availability of reliable health data. Several developing countries have maternal health indicators lagging behind as compared to international targets set by UN Millennium Development Goals, that now build the UN Sustainable Development Goals. One of the major reasons is poor and non-standardized maternal health record keeping techniques that affect data quality and undermine evidence based decision making. The aim of this research is the design and development of HL7 FHIR compliant data access model for maintaining maternal health data as FHIR resources. The HL7 FHIR standards are followed to enable effective exchange and manipulation of health data. The proposed architecture employs restful web services for system flexibility and interoperability. MongoDB, a NoSQL database is used as backend storage system for efficient manipulation of data. To determine the effectiveness of the system, it was reviewed by healthcare providers and expectant women. Their feedback highlights the usefulness of the proposed system as compared to traditional record keeping techniques. It is anticipated that the proposed system will lay the foundation of a comprehensive maternal healthcare information system. This shall enable trend analysis for policymaking to help accelerate the efforts for meeting global maternal health targets.
