METEOR: An Enterprise Health Informatics Environment to Support Evidence-Based Medicine

METEOR: An Enterprise Health Informatics Environment to Support Evidence-Based Medicine 170 177 IEEE Transactions on Biomedical Engineering (TBME)


Mamta Puppala, Tiancheng He, Shenyi Chen, Richard Ogunti, Xiaohui Yu, Fuhai Li, Robert Jackson, Stephen T.C. Wong, Houston Methodist Hospital Research Institute, USA

Better management and analytics of health data would lead to unprecedented opportunities in improving patient care delivery, operational efficiencies, and clinical outcomes and interventions. Integrating massive amounts of health data into a central archive for offline/online analytics and reporting is not a new concept. However, recent, widespread implementation of electronic medical record and advances made in biological sciences generate a great deal of contemporary data that present new challenges and business opportunities.  Much of the contemporary data such as genomics, sensory, free text, and imaging, are in unstructured formats and involve constant data flow that requires analytics methods more from machine learning and artificial intelligence than conventional biostatistics or hypothesis-based analysis. The primary purpose of analytics is also expanding from descriptive (reporting on the past), to be more predictive (using past data to predict the future) and prescriptive (using models to specify optimal protocols and procedures). Next generation healthcare information systems, application services, and organization structures are required to realize the new opportunities in the era of big data for health.
The Houston Methodist Environment for Translational Enhancement and Outcomes Research (METEOR) project at Houston Methodist Hospital aims to fill this gap from the perspective of an integrated care delivery system.  The design and implementation of METEOR is iterative, modular, and service-oriented. METEOR has two components: Enterprise Data Warehouse (EDW) consisting of organized, enterprise-wide longitudinal clinical, administrative and research data; and a Software Intelligence and Analytics (SIA) layer with embedded functional modules supporting evidence based medicine across the healthcare enterprise. Customized software applications and analytics services are created on top of METEOR to meet user-specific needs. METEOR transforms clinical workflow, integrates contemporary health data, and enables evidence-based methods to improve outcomes and increase values. Technical design of the METEOR EDW and examples of app services are presented in the article.