. EWSolutions Testimonial | THE MAYO CLINIC

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Below is an excerpt from a scholarly article in the Journal of the American Medical Informatics Association (JAMIA), where the Mayo Clinic discusses the six systems and programs (Enterprise Data Trust, Enterprise Information Management Initiative, Data Governance, Enterprise Data Modeling, Enterprise Vocabulary System and Enterprise Managed Metadata Environment) which EWSolutions lead and implemented with the Mayo team.

“Mayo Clinic’s Enterprise Data Trust is a collection of data from patient care, education, research, and administrative transactional systems, organized to support information retrieval, business intelligence, and high-level decision making. Structurally it is a top-down, subject-oriented, integrated, time-variant, and non-volatile collection of data in support of Mayo Clinic’s analytic and decision making processes. It is an interconnected piece of Mayo Clinic’s Enterprise Information Management initiative, which also includes Data Governance, Enterprise Data Modeling, the Enterprise Vocabulary System, and Metadata Management. These resources enable unprecedented organization of enterprise information about patient, genomic, and research data. While facile access for cohort definition or aggregate retrieval is supported, a high level of security, retrieval audit, and user authentication ensures privacy, confidentiality, and respect for the trust imparted by our patients for the respectful use of information about their conditions… Mayo is already realizing palpable success from our cancer center projects, which is enabling analysis of clinical trial capture and accrual patterns, patient volumes, and clinical trial patient filtering, and will eventually optimize patient options for clinical trials. An infection analytics project has standardized the data definition and capture of infection and infection-related case data across the enterprise. The project has enabled a single standardized, enterprise-based reporting and analysis environment for infection data, and is currently seeking to further automate the identification of healthcare acquired infections. Other deliverables to data include referral analysis, balanced scorecard reporting, quality dashboards, and ad hoc reports across a wide spectrum of clinical practice, research, and administrative requests.”

Quoted from “Jamia”, a scholarly journal of informatics in health and biomedicine.


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