By using the Portavita Integrated Care System, a large amount of structured and unstructured data can be gathered about a patient, such as documents, laboratory values, genetic, social and sensor data. Analysis of this data can be used for several purposes, including support for care coordination, scientific research, Personal Health Records, financial processes, and to acquire insights on patient level, practice level and regional level.

To facilitate access to this valuable data, Portavita’s sister company MGRID has developed a healthcare data platform.

By unlocking the data that is stored in all kinds of sources, the MGRID clinical data platform makes this data available for use in business intelligence applications, translational medicine and data mining projects.

The MGRID clinical data platform is scalable and secure, and the only data store that is truly aware of the semantics of medical information.

 

The Portavita Care Management Modules all have reporting functionality. Apart from offering numerous predefined reports, we also offer the possibility to interactively query medical data by making use of Portavita Explorer.

Portavita Explorer, developed by Portavita’s sister company MGRID, is a data browsing tool that enables you to retrieve data from the system. With a simple, easy-to-use menu, you can decide on your selection criteria and columns, and apply aggregations. You even have the possibility to show the output in a pivot table. This enables you to create quick and easy surveys of patients who meet a certain profile, for example all patients older than 75 years with a HBA1c > 50 who not have been seen in your practice for over a year.

You can also generate surveys on an aggregated level about the patient population of a general practice or in a whole region.

Analytics of Big Data in Healthcare will definitely make healthcare smarter.

However, it also places high demands on the data management tool. It is necessary to use a data-driven solution that translates source data into a standardised and normalised model.

Based on the MGRID healthcare data platform, all information that has been recorded can be analysed for various purposes. Management reporting and Analytics Tools like SAS, SPSS, and Orange can function through the use of this data warehouse.

 

 

Together with leading European universities and enterprises, Portavita also participates in the European research project AXLE.

AXLE focuses on automatic scaling of complex analytics, while addressing the full requirements of real data sets.

The predictive value resulting from the analysis of extremely large quantities of data will have a tremendous impact on improving the quality of healthcare as well as reducing its costs. By focusing on the illnesses of individual patients from collective information, it will also make a substantial contribution to the further development of the Individual Care Plan.

 

MGRID offers a next-generation healthcare data warehouse architecture by making use of the HL7 v3 RIM data model.

MGRID includes the message transformation tools necessary to ingest, validate, load and store large numbers of medical documents (e.g. CDA). Storing these documents programmatically without loss of medical context enables healthcare organizations to perform cross-patient analysis and research on all patient data. This data can be unlocked from several different sources which will be consolidated by MGRID.

The built-in support for code systems such as SNOMED CT and LOINC enables integration on a semantic level, ensuring correctness of results and facilitating reasoning on patient data.

MGRID runs on PostgreSQL, including EMC Pivotal’s Greenplum, HAWQ and Hadoop data persistence services. As a consequence, MGRID can scale horizontally to meet performance and capacity requirements as the healthcare data warehouse grows. In addition, integration with Hadoop allows organizations to store unstructured data, such as images and hand-written physician notes, in the common medical data lake.

Unlocking the data that is currently stored in documents makes it available for use in business intelligence applications, translational medicine and data mining projects. Machine learning tools such as MADlib, Graphlab and open source Mahout, Pig, Hive and Map Reduce are integrated within the data warehouse and HDFS.

More information on MGRID can be found on: www.mgrid.net.