2.50
Hdl Handle:
http://hdl.handle.net/10755/156161
Type:
Presentation
Title:
Tracking the evidence: Databases Made Easy
Abstract:
Tracking the evidence: Databases Made Easy
Conference Sponsor:Sigma Theta Tau International
Conference Year:2007
Author:West, Katharine, MPH, MSN, RN, CNS
P.I. Institution Name:Kaiser Permanente
Title:Clinical Systems Analyst
[Research Presentation] Establishing "evidence" in nursing practice requires the collection and analysis of data. Yet a gap exists between obtaining the evidence (by formal research or informal data collection) and practice. This has been termed the "research-practice gap" (Bostrom et al., 1993). Another barrier for nursing to establish ôevidenceö lies in the lack of access to patient data for data mining purposes. This is often because technology support departments do not have the time or personnel and cannot create the necessary databases or write the programs that generate data reports for nurses to use. However, nurses can collect practice data themselves using standard computer technology and standard office software to create a modest database for collecting information about the issue under investigation. Once data is stored electronically, the process of finding patterns in the data can be automated or at least augmented by the computer (Witten & Frank 2000). Data can be further analyzed for information (generating "queries"), which then supports obtaining knowledge from the data, and finally applying that knowledge to patient care (van Bemmel & Musen, 1997). This data-information-knowledge-application cycle is repeated when outcomes data is collected and re-analyzed. This PowerPoint presentation will provide a brief introduction to data mining and focus on simple database design and analysis. Screenshots of standard Microsoft Office software will be shown in the creation of a database, how to formulate a query for information, gain knowledge from the identified patterns, and then apply the evidence to improve patient outcomes. Analysis of the same dataset using both MS Excel (a flat database) and MS Access (a relational database) will allow the participant to compare and contrast the strengths of both approaches to data mining for evidence-based nursing practice. Computer skill level: intermediate user - no programming experience required.
Repository Posting Date:
26-Oct-2011
Date of Publication:
17-Oct-2011
Sponsors:
Sigma Theta Tau International

Full metadata record

DC FieldValue Language
dc.typePresentationen_GB
dc.titleTracking the evidence: Databases Made Easyen_GB
dc.identifier.urihttp://hdl.handle.net/10755/156161-
dc.description.abstract<table><tr><td colspan="2" class="item-title">Tracking the evidence: Databases Made Easy</td></tr><tr class="item-sponsor"><td class="label">Conference Sponsor:</td><td class="value">Sigma Theta Tau International</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">West, Katharine, MPH, MSN, RN, CNS</td></tr><tr class="item-institute"><td class="label">P.I. Institution Name:</td><td class="value">Kaiser Permanente</td></tr><tr class="item-author-title"><td class="label">Title:</td><td class="value">Clinical Systems Analyst</td></tr><tr class="item-email"><td class="label">Email:</td><td class="value">kwestrn@earthlink.net</td></tr><tr><td colspan="2" class="item-abstract">[Research Presentation] Establishing &quot;evidence&quot; in nursing practice requires the collection and analysis of data. Yet a gap exists between obtaining the evidence (by formal research or informal data collection) and practice. This has been termed the &quot;research-practice gap&quot; (Bostrom et al., 1993). Another barrier for nursing to establish &ocirc;evidence&ouml; lies in the lack of access to patient data for data mining purposes. This is often because technology support departments do not have the time or personnel and cannot create the necessary databases or write the programs that generate data reports for nurses to use. However, nurses can collect practice data themselves using standard computer technology and standard office software to create a modest database for collecting information about the issue under investigation. Once data is stored electronically, the process of finding patterns in the data can be automated or at least augmented by the computer (Witten &amp; Frank 2000). Data can be further analyzed for information (generating &quot;queries&quot;), which then supports obtaining knowledge from the data, and finally applying that knowledge to patient care (van Bemmel &amp; Musen, 1997). This data-information-knowledge-application cycle is repeated when outcomes data is collected and re-analyzed. This PowerPoint presentation will provide a brief introduction to data mining and focus on simple database design and analysis. Screenshots of standard Microsoft Office software will be shown in the creation of a database, how to formulate a query for information, gain knowledge from the identified patterns, and then apply the evidence to improve patient outcomes. Analysis of the same dataset using both MS Excel (a flat database) and MS Access (a relational database) will allow the participant to compare and contrast the strengths of both approaches to data mining for evidence-based nursing practice. Computer skill level: intermediate user - no programming experience required.</td></tr></table>en_GB
dc.date.available2011-10-26T14:30:49Z-
dc.date.issued2011-10-17en_GB
dc.date.accessioned2011-10-26T14:30:49Z-
dc.description.sponsorshipSigma Theta Tau Internationalen_GB
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