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

Mamta Puppala, Tiancheng He, Shenyi Chen, Richard Ogunti, Xiaohui Yu, Fuhai Li, Robert Jackson, Stephen T.C. Wong

Research output: Contribution to journalArticle

23 Scopus citations

Abstract

The aim of this paper is to propose the design and implementation of next-generation enterprise analytics platform developed at the Houston Methodist Hospital (HMH) system to meet the market and regulatory needs of the healthcare industry. Methods: For this goal, we developed an integrated clinical informatics environment, i.e., Methodist environment for translational enhancement and outcomes research (METEOR). The framework of METEOR consists of two components: the enterprise data warehouse (EDW) and a software intelligence and analytics (SIA) layer for enabling a wide range of clinical decision support systems that can be used directly by outcomes researchers and clinical investigators to facilitate data access for the purposes of hypothesis testing, cohort identification, data mining, risk prediction, and clinical research training. Results: Data and usability analysis were performed on METEOR components as a preliminary evaluation, which successfully demonstrated that METEOR addresses significant niches in the clinical informatics area, and provides a powerful means for data integration and efficient access in supporting clinical and translational research. Conclusion: METEOR EDW and informatics applications improved outcomes, enabled coordinated care, and support health analytics and clinical research at HMH. Significance: The twin pressures of cost containment in the healthcare market and new federal regulations and policies have led to the prioritization of the meaningful use of electronic health records in the United States. EDW and SIA layers on top of EDW are becoming an essential strategic tool to healthcare institutions and integrated delivery networks in order to support evidence-based medicine at the enterprise level.

Original languageEnglish
Article number7137654
Pages (from-to)2776-2786
Number of pages11
JournalIEEE Transactions on Biomedical Engineering
Volume62
Issue number12
DOIs
StatePublished - Dec 2015
Externally publishedYes

Keywords

  • Clinical data warehouse
  • cohort identification
  • natural language processing (NLP)
  • outcomes research
  • readmission risk
  • smartphone health app

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    Puppala, M., He, T., Chen, S., Ogunti, R., Yu, X., Li, F., Jackson, R., & Wong, S. T. C. (2015). METEOR: An Enterprise Health Informatics Environment to Support Evidence-Based Medicine. IEEE Transactions on Biomedical Engineering, 62(12), 2776-2786. [7137654]. https://doi.org/10.1109/TBME.2015.2450181