Information warehouse - a comprehensive informatics platform for business, clinical, and research applications.

Since its inception in 1997, the IW (Information Warehouse) at the Ohio State University Medical Center (OSUMC) has gradually transformed itself from a single purpose business decision support system to a comprehensive informatics platform supporting basic, clinical, and translational research. The IW today is the combination of four integrated components: a clinical data repository containing over a million patients; a research data repository housing various research specific data; an application development platform for building business and research enabling applications; a business intelligence environment assisting in reporting in all function areas. The IW is structured and encoded using standard terminologies such as SNOMED-CT, ICD, and CPT. The IW is an important component of OSUMC's Clinical and Translational Science Award (CTSA) informatics program.

Implementation of a metadata architecture and knowledge collection to support semantic interoperability in an enterprise data warehouse.

In order to enhance interoperability between enterprise systems, and improve data validity and reliability throughout The Ohio State University Medical Center (OSUMC), we have initiated the development of an ontology-anchored metadata architecture and knowledge collection for our enterprise data warehouse. The metadata and corresponding semantic relationships stored in the OSUMC knowledge collection are intended to promote consistency and interoperability across the heterogeneous clinical, research, business and education information managed within the data warehouse.

Data delivery workflow in an academic information warehouse.

The Ohio State University Medical Center (OSUMC) Information Warehouse (IW) collects data from many systems throughout the OSUMC on load cycles ranging from real-time to on-demand. The data then is prepared for delivery to diversity of customers across the clinical, education, and research sectors of the OSUMC. Some of the data collected at the IW include patient management, billing and finance, procedures, medications, lab results, clinical reports, physician order entry, outcomes, demographics, and so on. This data is made available to the users of the IW in variety of formats and methods.

Innovative applications of an enterprise-wide information warehouse.

The Information Warehouse at The Ohio State University Medical Center is a comprehensive effort integrating data from over 70 sources throughout the enterprise. The IW serves a broad diversity of customers in all mission areas of the medical center, from clinical operations and administration to education, to research. This comprehensiveness has facilitated an innovative application of cross-disciplinary technologies and methodologies to problem domains beyond the roles traditionally envisioned for data warehousing.

Improving daily workflow to improve insurance rejection handling by leveraging an existing data warehouse.

The Ohio State University Medical Center (OSUMC) has developed a comprehensive Information Warehouse (IW), comprising data from all aspects of the academic medical center. By leveraging this data source, OSUMC was able to create an application combining Business Intelligence (BI) reporting, advanced worklisting, and distributed data management techniques. OSUMC was able to use this application to substantially improve the throughput of rejection handling, allowing more timely resolution without an increase in staff.

Managing data quality in an existing medical data warehouse using business intelligence technologies.

The Ohio State University Medical Center (OSUMC) Information Warehouse (IW) is a comprehensive data warehousing facility that provides providing data integration, management, mining, training, and development services to a diversity of customers across the clinical, education, and research sectors of the OSUMC. Providing accurate and complete data is a must for these purposes. In order to monitor the data quality of targeted data sets, an online scorecard has been developed to allow visualization of the critical measures of data quality in the Information Warehouse.