View source for METEOR: An Enterprise Health Informatics Environment to Support Evidence - based Medicine


===Introduction===
METEOR is the Methodist Environment for Translational Enhancement and Outcomes Research.  It is a data warehouse that handles any type of data query and has the ability to process text within the database via [[Natural language processing (NLP)|natural language processing]].  As data is collected from all locations within the Houston Methodist Hospital system, METEOR, an enterprise [[Data warehouse|data warehouse]] and a software intelligence and analytics system, enables a wide range of clinical decision support.  Currently, METEOR provides data access for over 2 million records and 10 million unique patient encounters.  .<ref name = ‘Enterprise Data’>Puppala, M., He, T., Chen, S., Ojunti, R., Yu, X., et al. (2014) METEOR: An enterprise health informatics environment to support evidence-based medicine.  IEEE Transactions on Biomedical Engineering. http://www.ncbi.nlm.nih.gov/pubmed/26126271/</ref>

===Materials and Methods===
*[[Data warehouse|Data Warehouse]].  The data warehouse required obtaining information about each separate database structure, architecture and data dictionary, documentation about relationships of database tables and understanding the data for relevant variables.
*CDS Applications at the Software Intelligent and Analytics (SIA) Layer.  This allows effective integration and management of multiple data types to apply learning for CDDS.  Two applications are illustrated:
**Category 1: Information Retrieval
**Category 2: Prediction Models

===Results===
Tow examples were noted from a usability analysis.  A patient outcomes research study was supported as well as other hospital quality improvement efforts.  Within this study, the researchers were able to query the EDW for those at risk for breast cancer from biopsy reports and to check a patient’s risk for readmission based on four readmission risk criteria.

===Discussion===
Enterprise Data Warehousing is an important component of health informatics.  It provides researchers and clinicians with access to clinical data to enable study design and cohort selection.  This also reduces patient privacy risks.  Through the development of METEOR several modules and applications were developed for natural language processing for improved data retrieval for physicians and researchers.  Creating a readmission reductions strategy is top priority among organizations today.  The right applications can help to turn the right data into a source of wisdom that can measure quality. 

===Conclusions===
METEOR is designed to help clinicians, investigators and researchers across the healthcare enterprise.  With the many demands and opportunities of the big data era, the efficiency and ability to provide cost-effective care is crucial.  This also could lead to a higher level of patient satisfactions.  The powerful data gathering and analytics can improve clinical operations.  METEOR EDW and informatics applications were shown to improve outcomes, enable coordinated care, and analytics and research.  

====Area of interest and comments====
EDW and SIA on top of EDW as a strategic tool in healthcare institutions to help with cost containment and prioritization of the meaningful use of electronic medical records.  


== Reference ==
<references/>

[[Category:CIS]]
[[Category:CDS]]
[[Category:Databases, Big Data, and Data Quality]]
[[Category: Meaningful Use]]
[[Category: HI5313-2015-FALL]]