Literature DB >> 18194718

The development of health care data warehouses to support data mining.

Jason A Lyman1, Kenneth Scully, James H Harrison.   

Abstract

Clinical data warehouses offer tremendous benefits as a foundation for data mining. By serving as a source for comprehensive clinical and demographic information on large patient populations, they streamline knowledge discovery efforts by providing standard and efficient mechanisms to replace time-consuming and expensive original data collection, organization, and processing. Building effective data warehouses requires knowledge of and attention to key issues in database design, data acquisition and processing, and data access and security. In this article, the authors provide an operational and technical definition of data warehouses, present examples of data mining projects enabled by existing data warehouses, and describe key issues and challenges related to warehouse development and implementation.

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Year:  2008        PMID: 18194718     DOI: 10.1016/j.cll.2007.10.003

Source DB:  PubMed          Journal:  Clin Lab Med        ISSN: 0272-2712            Impact factor:   1.935


  14 in total

1.  Toward a fully de-identified biomedical information warehouse.

Authors:  Jianhua Liu; Selnur Erdal; Scott A Silvey; Jing Ding; John D Riedel; Clay B Marsh; Jyoti Kamal
Journal:  AMIA Annu Symp Proc       Date:  2009-11-14

2.  What Is Asked in Clinical Data Request Forms? A Multi-site Thematic Analysis of Forms Towards Better Data Access Support.

Authors:  David A Hanauer; Gregory W Hruby; Daniel G Fort; Luke V Rasmussen; Eneida A Mendonça; Chunhua Weng
Journal:  AMIA Annu Symp Proc       Date:  2014-11-14

3.  Building bridges across electronic health record systems through inferred phenotypic topics.

Authors:  You Chen; Joydeep Ghosh; Cosmin Adrian Bejan; Carl A Gunter; Siddharth Gupta; Abel Kho; David Liebovitz; Jimeng Sun; Joshua Denny; Bradley Malin
Journal:  J Biomed Inform       Date:  2015-04-01       Impact factor: 6.317

4.  Evaluation of Healthcare Interventions and Big Data: Review of Associated Data Issues.

Authors:  Carl V Asche; Brian Seal; Kristijan H Kahler; Elisabeth M Oehrlein; Meredith Greer Baumgartner
Journal:  Pharmacoeconomics       Date:  2017-08       Impact factor: 4.981

5.  Architecting the Data Loading Process for an i2b2 Research Data Warehouse: Full Reload versus Incremental Updating.

Authors:  Andrew R Post; Miao Ai; Akshatha Kalsanka Pai; Marc Overcash; David S Stephens
Journal:  AMIA Annu Symp Proc       Date:  2018-04-16

6.  Using EHRs to advance epilepsy care.

Authors:  Juma S Mbwana; Zachary M Grinspan; Russell Bailey; Madison Berl; Jeffrey Buchhalter; Adrian Bumbut; Zach Danner; Tracy Glauser; Angie Glotstein; Howard Goodkin; Brian Jacobs; Lisa Jones; Barbara Kroner; Gardiner Lapham; Tobias Loddenkemper; Demetrius M Maraganore; Doug Nordli; William D Gaillard
Journal:  Neurol Clin Pract       Date:  2019-02

7.  Efficient Execution Methods of Pivoting for Bulk Extraction of Entity-Attribute-Value-Modeled Data.

Authors:  Gang Luo; Lewis J Frey
Journal:  IEEE J Biomed Health Inform       Date:  2015-01-15       Impact factor: 5.772

8.  The Analytic Information Warehouse (AIW): a platform for analytics using electronic health record data.

Authors:  Andrew R Post; Tahsin Kurc; Sharath Cholleti; Jingjing Gao; Xia Lin; William Bornstein; Dedra Cantrell; David Levine; Sam Hohmann; Joel H Saltz
Journal:  J Biomed Inform       Date:  2013-02-09       Impact factor: 6.317

9.  Cohort Identification for Translational Bioinformatics Studies.

Authors:  Tiffany A Lin; Zeynep Eroglu; Rodrigo Carvajal; Joseph Markowitz
Journal:  Methods Mol Biol       Date:  2021

10.  A Roadmap for Automating Lineage Tracing to Aid Automatically Explaining Machine Learning Predictions for Clinical Decision Support.

Authors:  Gang Luo
Journal:  JMIR Med Inform       Date:  2021-05-27
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