2.50
Hdl Handle:
http://hdl.handle.net/10755/157783
Type:
Presentation
Title:
A Technique for "Streamlining" Data Collection
Abstract:
A Technique for "Streamlining" Data Collection
Conference Sponsor:Western Institute of Nursing
Conference Year:2009
Author:Lim, Kyung Hee, PhD, RN
P.I. Institution Name:The University of Arizona, College of Nursing
Title:Postdoctoral Fellow
Contact Address:1305 N. Martin, Tucson, AZ, 85721-0203, USA
Contact Telephone:520-970-0494
Co-Authors:Joyce A. Verran, PhD, RN, FAAN, Professor Emeritus
Purpose: The purpose of this presentation is to describe and provide an example of criteria used to "streamline" data collection in health care agencies. "Streamlining" is done to reduce subject burden while retaining significant factors associated with study outcome measures. Two aspects of streamlining are identified: (1) reducing data elements by eliminating scales and items within scales and (2) comparing the remaining data to information already collected in the institution that could be used instead of primary data collection. This presentation deals only with the first aspect of "streamlining. Background: The goal of the DyNADS research project is to develop a dynamic network analysis tool that will allow managers to use a computational modeling to experiment with changes to the virtual unit. In previous research, extensive data collection of most factors shown to impact the workgroup environment was conducted. The first aim of DyNADS was to systematically reduce the needed data. Setting and Sample: Data were collected from 292 nursing staff and 416 patients on 11 nursing unit in three hospitals. Of the 11 units, seven achieved a sufficient response rate to be included in further substudies. Methods: Data were collected on eleven workgroup variables and 9 patient outcomes. To "streamline data," a 5-point procedure was developed. A scale or item would be considered for elimination if: (1) the scale had a minor impact on other relevant workgroup variables, (2) the scale had a minor impact on relevant patient outcomes, (3) the item had a minor impact on the total scale score, (4) the item had a minor impact on workgroup variables, or (5) the item had a minor impact on patient outcomes. A minor impact was defined by the size of correlations (p>.10), influence in regression equations (Beta p>.10), and ability to discriminate high and low groups. Results: We will present the results of utilizing the streamlining procedure and criteria using as an example, The Control Over Nursing Practice Scale (CONP). Since CONP is a workgroup culture variable, it was compared to 4 other culture variables and all 9 patient outcomes. The total CONP correlated with four of the 9 patient outcomes and the workgroup measure of Job Satisfaction. Three items did not correlate at .80 or greater with the total scale or with any of the five variables associated with the total score. Five of the items correlated at similar levels with the same variables. Three items correlated with four of the variables. The remaining 2 items had varying significant correlations. Based on this, we concluded that the CONP scale should be retained but potentially reduced from 13 to 5-8 items. Further analysis will be done to refine the "streamlining" procedure. Implications: Results of nursing systems research have found many factors to be significant in improving staff and patient outcomes. A number of national organizations do repeated collection of data in volunteer hospitals. Individual agencies routinely collect information on scales from staff. These processes result in an ongoing burden to staff that are already dealing with increased workload and unit turbulence. Because data collection is necessary to expand our science, it is critical that nurse researchers do everything possible to reduce the data collection burden while retaining significant data.
Repository Posting Date:
26-Oct-2011
Date of Publication:
17-Oct-2011
Sponsors:
Western Institute of Nursing

Full metadata record

DC FieldValue Language
dc.typePresentationen_GB
dc.titleA Technique for "Streamlining" Data Collectionen_GB
dc.identifier.urihttp://hdl.handle.net/10755/157783-
dc.description.abstract<table><tr><td colspan="2" class="item-title">A Technique for &quot;Streamlining&quot; Data Collection</td></tr><tr class="item-sponsor"><td class="label">Conference Sponsor:</td><td class="value">Western Institute of Nursing</td></tr><tr class="item-year"><td class="label">Conference Year:</td><td class="value">2009</td></tr><tr class="item-author"><td class="label">Author:</td><td class="value">Lim, Kyung Hee, PhD, RN</td></tr><tr class="item-institute"><td class="label">P.I. Institution Name:</td><td class="value">The University of Arizona, College of Nursing</td></tr><tr class="item-author-title"><td class="label">Title:</td><td class="value">Postdoctoral Fellow</td></tr><tr class="item-address"><td class="label">Contact Address:</td><td class="value">1305 N. Martin, Tucson, AZ, 85721-0203, USA</td></tr><tr class="item-phone"><td class="label">Contact Telephone:</td><td class="value">520-970-0494</td></tr><tr class="item-email"><td class="label">Email:</td><td class="value">klim@nursing.arizona.edu</td></tr><tr class="item-co-authors"><td class="label">Co-Authors:</td><td class="value">Joyce A. Verran, PhD, RN, FAAN, Professor Emeritus</td></tr><tr><td colspan="2" class="item-abstract">Purpose: The purpose of this presentation is to describe and provide an example of criteria used to &quot;streamline&quot; data collection in health care agencies. &quot;Streamlining&quot; is done to reduce subject burden while retaining significant factors associated with study outcome measures. Two aspects of streamlining are identified: (1) reducing data elements by eliminating scales and items within scales and (2) comparing the remaining data to information already collected in the institution that could be used instead of primary data collection. This presentation deals only with the first aspect of &quot;streamlining. Background: The goal of the DyNADS research project is to develop a dynamic network analysis tool that will allow managers to use a computational modeling to experiment with changes to the virtual unit. In previous research, extensive data collection of most factors shown to impact the workgroup environment was conducted. The first aim of DyNADS was to systematically reduce the needed data. Setting and Sample: Data were collected from 292 nursing staff and 416 patients on 11 nursing unit in three hospitals. Of the 11 units, seven achieved a sufficient response rate to be included in further substudies. Methods: Data were collected on eleven workgroup variables and 9 patient outcomes. To &quot;streamline data,&quot; a 5-point procedure was developed. A scale or item would be considered for elimination if: (1) the scale had a minor impact on other relevant workgroup variables, (2) the scale had a minor impact on relevant patient outcomes, (3) the item had a minor impact on the total scale score, (4) the item had a minor impact on workgroup variables, or (5) the item had a minor impact on patient outcomes. A minor impact was defined by the size of correlations (p&gt;.10), influence in regression equations (Beta p&gt;.10), and ability to discriminate high and low groups. Results: We will present the results of utilizing the streamlining procedure and criteria using as an example, The Control Over Nursing Practice Scale (CONP). Since CONP is a workgroup culture variable, it was compared to 4 other culture variables and all 9 patient outcomes. The total CONP correlated with four of the 9 patient outcomes and the workgroup measure of Job Satisfaction. Three items did not correlate at .80 or greater with the total scale or with any of the five variables associated with the total score. Five of the items correlated at similar levels with the same variables. Three items correlated with four of the variables. The remaining 2 items had varying significant correlations. Based on this, we concluded that the CONP scale should be retained but potentially reduced from 13 to 5-8 items. Further analysis will be done to refine the &quot;streamlining&quot; procedure. Implications: Results of nursing systems research have found many factors to be significant in improving staff and patient outcomes. A number of national organizations do repeated collection of data in volunteer hospitals. Individual agencies routinely collect information on scales from staff. These processes result in an ongoing burden to staff that are already dealing with increased workload and unit turbulence. Because data collection is necessary to expand our science, it is critical that nurse researchers do everything possible to reduce the data collection burden while retaining significant data.</td></tr></table>en_GB
dc.date.available2011-10-26T20:12:01Z-
dc.date.issued2011-10-17en_GB
dc.date.accessioned2011-10-26T20:12:01Z-
dc.description.sponsorshipWestern Institute of Nursingen_GB
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