Healthcare Data Integration

The increasing ability to electronically maintain healthcare data carries with it the enormous potential to also improve overall healthcare. Collecting and analyzing data opens possibilities to further share knowledge, improve patient outcomes, optimise coordinated care processes and support evidence-based medicine. This is accomplished by comparing the effectiveness of treatments and by detecting treatment trends. A data-driven solution is a key component in providing this necessary knowledge for better care, lower cost and improved efficiency. MGRID offers such a solution for data-integration, reporting and analytics.

To drive healthcare reporting and analytics through data compiled from multiple operational data sources, it is necessary to translate source data into a common information model. Instead of developing a proprietary model, MGRID adopts the standardised and normalised models from HL7v2, HL7v3 RIM and HL7 FHIR for the Healthcare Data Model.

Benefits of using the HL7 standards for a datamodel include:

  • No additional mapping is required, besides mapping to the HL7 exchange standard, since the database data model is aligned with the healthcare exchange data model.
  • De-coupling of operational data sources and systems for reporting and analytics, resulting in smaller components and less inter-dependencies within the overall system.
  • HL7 data models track the full context and history of data, which can be used in order to check that data from multiple sources over many years are commensurate, a requirement for longitudinal and epidemiological studies.
The MGRID Healthcare Data Model offers best-in-class database support and performance for all HL7 standards.

MGRID has developed applications that aid message transformation, dataset creation and dataset exploration. The modules and applications of MGRID follow the HL7 and SQL standards; they are well-suited and intended to be used as components in software stacks for the medical vertical. MGRID software makes the process of preparing data for healthcare reporting and analytics more efficient, taking the next step toward improved data analysis, and consequently, overall healthcare.

Data Integration