Literature DB >> 16249300

Development of a data warehouse at an academic health system: knowing a place for the first time.

Jocelyn G Dewitt1, Philip M Hampton.   

Abstract

In 1998, the University of Michigan Health System embarked upon the design, development, and implementation of an enterprise-wide data warehouse, intending to use prioritized business questions to drive its design and implementation. Because of the decentralized nature of the academic health system and the development team's inability to identify and prioritize those institutional business questions, however, a bottom-up approach was used to develop the enterprise-wide data warehouse. Specific important data sets were identified for inclusion, and the technical team designed the system with an enterprise view and architecture rather than as a series of data marts. Using this incremental approach of adding data sets, institutional leaders were able to experience and then further define successful use of the integrated data made available to them. Even as requests for the use and expansion of the data warehouse outstrip the resources assigned for support, the data warehouse has become an integral component of the institution's information management strategy. The authors discuss the approach, process, current status, and successes and failures of the data warehouse.

Mesh:

Year:  2005        PMID: 16249300     DOI: 10.1097/00001888-200511000-00009

Source DB:  PubMed          Journal:  Acad Med        ISSN: 1040-2446            Impact factor:   6.893


  10 in total

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2.  Designing a Clinical Data Warehouse Architecture to Support Quality Improvement Initiatives.

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Review 3.  Biomedical informatics and outcomes research: enabling knowledge-driven health care.

Authors:  Peter J Embi; Stanley E Kaufman; Philip R O Payne
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4.  Exploring the ethical and regulatory issues in pragmatic clinical trials.

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5.  Practice-Based Knowledge Discovery for Comparative Effectiveness Research: An Organizing Framework.

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6.  Clinical use of an enterprise data warehouse.

Authors:  R Scott Evans; James F Lloyd; Lee A Pierce
Journal:  AMIA Annu Symp Proc       Date:  2012-11-03

7.  Analysis of Relationship between Levofloxacin and Corrected QT Prolongation Using a Clinical Data Warehouse.

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Journal:  Healthc Inform Res       Date:  2011-03-31

8.  Value Driven Outcomes (VDO): a pragmatic, modular, and extensible software framework for understanding and improving health care costs and outcomes.

Authors:  Kensaku Kawamoto; Cary J Martin; Kip Williams; Ming-Chieh Tu; Charlton G Park; Cheri Hunter; Catherine J Staes; Bruce E Bray; Vikrant G Deshmukh; Reid A Holbrook; Scott J Morris; Matthew B Fedderson; Amy Sletta; James Turnbull; Sean J Mulvihill; Gordon L Crabtree; David E Entwistle; Quinn L McKenna; Michael B Strong; Robert C Pendleton; Vivian S Lee
Journal:  J Am Med Inform Assoc       Date:  2014-10-16       Impact factor: 4.497

9.  Chapter 1: Biomedical knowledge integration.

Authors:  Philip R O Payne
Journal:  PLoS Comput Biol       Date:  2012-12-27       Impact factor: 4.475

10.  Characteristics desired in clinical data warehouse for biomedical research.

Authors:  Soo-Yong Shin; Woo Sung Kim; Jae-Ho Lee
Journal:  Healthc Inform Res       Date:  2014-04-30
  10 in total

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