title: METEOR: An Enterprise Health Informatics Environment to Support Evidence-Based Medicine.
abstract: OBJECTIVE
  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.
  
  
  CONCLUSIONS
  METEOR EDW and informatics applications improved outcomes, enabled coordinated care, and support health analytics and clinical research at HMH.
  
  
  CONCLUSIONS
  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.
authors.forename: Mamta
authors.initials: M
authors.lastname: Puppala
authors.forename: Tiancheng
authors.initials: T
authors.lastname: He
authors.forename: Shenyi
authors.initials: S
authors.lastname: Chen
authors.forename: Richard
authors.initials: R
authors.lastname: Ogunti
authors.forename: Xiaohui
authors.initials: X
authors.lastname: Yu
authors.forename: Fuhai
authors.initials: F
authors.lastname: Li
authors.forename: Robert
authors.initials: R
authors.lastname: Jackson
authors.forename: Stephen T C
authors.initials: ST
authors.lastname: Wong
mesh_terms: D000328:Adult; D000368:Aged; D057225:Data Mining; D003628:Database Management Systems; D020000:Decision Support Systems, Clinical; D019317:Evidence-Based Medicine; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D063731:Mobile Applications; D009323:Natural Language Processing; D018570:Risk Assessment; D057170:Translational Research, Biomedical