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 language | English (US) |
|---|---|
| Article number | 7137654 |
| Pages (from-to) | 2776-2786 |
| Number of pages | 11 |
| Journal | IEEE Transactions on Biomedical Engineering |
| Volume | 62 |
| Issue number | 12 |
| DOIs | |
| State | Published - Dec 1 2015 |
Keywords
- Clinical data warehouse
- cohort identification
- natural language processing (NLP)
- outcomes research
- readmission risk
- smartphone health app
ASJC Scopus subject areas
- Biomedical Engineering
Divisions
- General Internal Medicine
- Medical Oncology
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