2.50
Hdl Handle:
http://hdl.handle.net/10755/161024
Type:
Presentation
Title:
A Data Modeling Process for Decomposing Healthcare Patient Data Sets
Abstract:
A Data Modeling Process for Decomposing Healthcare Patient Data Sets
Conference Sponsor:Midwest Nursing Research Society
Conference Year:2007
Author:Lu, Der-Fa, PhD
P.I. Institution Name:University of Iowa
Contact Address:College of Nursing, 426 NB, Iowa City, IA, 52242, USA
Co-Authors:W.N. Street, Henry B. Tippie College of Business, University of Iowa, Iowa City, IA and C.W. Delaney, School of Nursing, University of Minnesota, Miniapplics, MN
Healthcare sectors must use archived data effectively in order to reduce the ever increasing cost of patient care as well as to improve the quality of that care. Clinicians, however, often find that the retrieval of archived data needed for decision support is fraught with barriers. A clear and repeatable data modeling process using relational database principles is one solution to this problem. The purpose of this paper is to present an example of a data modeling process using normalization principles to decompose datasets, with an entity-relational (E-R) diagram to illustrate the database model for a large healthcare data set. Queries for nursing diagnosis "Impaired Physical Mobility" are used to discuss the utilities of the model. Project results can be used as a foundation for the construction of a large clinical data warehouse. Clinicians can use this model to manage large volumes of clinical data for decision support and quality control at the point of patient care.
Repository Posting Date:
26-Oct-2011
Date of Publication:
17-Oct-2011
Sponsors:
Midwest Nursing Research Society

Full metadata record

DC FieldValue Language
dc.typePresentationen_GB
dc.titleA Data Modeling Process for Decomposing Healthcare Patient Data Setsen_GB
dc.identifier.urihttp://hdl.handle.net/10755/161024-
dc.description.abstract<table><tr><td colspan="2" class="item-title">A Data Modeling Process for Decomposing Healthcare Patient Data Sets</td></tr><tr class="item-sponsor"><td class="label">Conference Sponsor:</td><td class="value">Midwest Nursing Research Society</td></tr><tr class="item-year"><td class="label">Conference Year:</td><td class="value">2007</td></tr><tr class="item-author"><td class="label">Author:</td><td class="value">Lu, Der-Fa, PhD</td></tr><tr class="item-institute"><td class="label">P.I. Institution Name:</td><td class="value">University of Iowa</td></tr><tr class="item-address"><td class="label">Contact Address:</td><td class="value">College of Nursing, 426 NB, Iowa City, IA, 52242, USA</td></tr><tr class="item-email"><td class="label">Email:</td><td class="value">der-fa-lu@uiowa.edu</td></tr><tr class="item-co-authors"><td class="label">Co-Authors:</td><td class="value">W.N. Street, Henry B. Tippie College of Business, University of Iowa, Iowa City, IA and C.W. Delaney, School of Nursing, University of Minnesota, Miniapplics, MN</td></tr><tr><td colspan="2" class="item-abstract">Healthcare sectors must use archived data effectively in order to reduce the ever increasing cost of patient care as well as to improve the quality of that care. Clinicians, however, often find that the retrieval of archived data needed for decision support is fraught with barriers. A clear and repeatable data modeling process using relational database principles is one solution to this problem. The purpose of this paper is to present an example of a data modeling process using normalization principles to decompose datasets, with an entity-relational (E-R) diagram to illustrate the database model for a large healthcare data set. Queries for nursing diagnosis &quot;Impaired Physical Mobility&quot; are used to discuss the utilities of the model. Project results can be used as a foundation for the construction of a large clinical data warehouse. Clinicians can use this model to manage large volumes of clinical data for decision support and quality control at the point of patient care.</td></tr></table>en_GB
dc.date.available2011-10-26T23:14:40Z-
dc.date.issued2011-10-17en_GB
dc.date.accessioned2011-10-26T23:14:40Z-
dc.description.sponsorshipMidwest Nursing Research Societyen_GB
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