Literature DB >> 11452574

Toward best practice: leveraging the electronic patient record as a clinical data warehouse.

C S Ledbetter1, M W Morgan.   

Abstract

Automating clinical and administrative processes via an electronic patient record (EPR) gives clinicians the point-of-care tools they need to deliver better patient care. However, to improve clinical practice as a whole and then evaluate it, healthcare must go beyond basic automation and convert EPR data into aggregated, multidimensional information. Unfortunately, few EPR systems have the established, powerful analytical clinical data warehouses (CDWs) required for this conversion. This article describes how an organization can support best practice by leveraging a CDW that is fully integrated into its EPR and clinical decision support (CDS) system. The article (1) discusses the requirements for comprehensive CDS, including on-line analytical processing (OLAP) of data at both transactional and aggregate levels, (2) suggests that the transactional data acquired by an OLTP EPR system must be remodeled to support retrospective, population-based, aggregate analysis of those data, and (3) concludes that this aggregate analysis is best provided by a separate CDW system.

Entities:  

Mesh:

Year:  2001        PMID: 11452574

Source DB:  PubMed          Journal:  J Healthc Inf Manag        ISSN: 1099-811X


  7 in total

1.  Comparison of manual versus automated data collection method for an evidence-based nursing practice study.

Authors:  M D Byrne; T R Jordan; T Welle
Journal:  Appl Clin Inform       Date:  2013-02-13       Impact factor: 2.342

2.  Building a diabetes screening population data repository using electronic medical records.

Authors:  Wen-Jan Tuan; Ann M Sheehy; Maureen A Smith
Journal:  J Diabetes Sci Technol       Date:  2011-05-01

3.  A Multidimensional Data Warehouse for Community Health Centers.

Authors:  Kislaya Kunjan; Tammy Toscos; Ayten Turkcan; Brad N Doebbeling
Journal:  AMIA Annu Symp Proc       Date:  2015-11-05

Review 4.  Biomedical informatics and translational medicine.

Authors:  Indra Neil Sarkar
Journal:  J Transl Med       Date:  2010-02-26       Impact factor: 5.531

5.  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

6.  Unsupervised machine learning for the discovery of latent disease clusters and patient subgroups using electronic health records.

Authors:  Yanshan Wang; Yiqing Zhao; Terry M Therneau; Elizabeth J Atkinson; Ahmad P Tafti; Nan Zhang; Shreyasee Amin; Andrew H Limper; Sundeep Khosla; Hongfang Liu
Journal:  J Biomed Inform       Date:  2019-12-28       Impact factor: 6.317

7.  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
  7 in total

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