Discovering the Links Between Quality Measures, Staffing, and Administrator Turnover in Missouri Nursing Homes

2.50
Hdl Handle:
http://hdl.handle.net/10755/159300
Type:
Presentation
Title:
Discovering the Links Between Quality Measures, Staffing, and Administrator Turnover in Missouri Nursing Homes
Abstract:
Discovering the Links Between Quality Measures, Staffing, and Administrator Turnover in Missouri Nursing Homes
Conference Sponsor:Midwest Nursing Research Society
Conference Year:2005
Author:Alexander, Gregory
P.I. Institution Name:University of Missouri-Columbia
Title:Pre-doctoral Fellow
Contact Address:Sinclair School of Nursing, 324 Clark Hall, Columbia, MO, 65211, USA
Contact Telephone:573-882-2803
Co-Authors:Marcia Flesner, Clinical Nurse Researcher; Timothy Patrick, Assistant Professor; and Marilyn Rantz, PhD, RN, FAAN, Professor
The Institute of Medicine, in a report from the Committee on Improving Quality in Long Term Care (2001), indicated the continued use of standardized assessment data was essential for improving quality of resident care in long term care. This study utilized staffing measures, hours/resident/day, for Registered Nurses (RN), Licensed Vocational Nurses (LVN), and Certified Nurses Aides (CNA) to determine if there were significant differences in quality measure scores (QMs), obtained from Nursing Home Compare (NHC) in Feb 2004, across different staffing levels. In addition, this study used facility level data, collected from the Missouri Department of Health and Senior Services, to evaluate differences in QMs associated with frequency of administrative turnover ten years prior to this evaluation. Staffing measures were calculated for each group with a high (RN>.44, LVN>.73, CNA>2.59), medium (RN>.30, LVN>.53, CNA>2.14) and low (RN<.30, LVN<.53, CNA<2.14) number of staffing hours/resident/day. Frequency of administrative turnover was calculated for the number of times each facility had an administrator change since 1994. Analysis of variance was used to determine mean differences in QMs using three staffing levels. Post hoc Bonferroni analyses were tabulated for each QM indicating a significant difference. Statistical analysis revealed significant differences in three QMs for staffing measures including: 1) Percentage of residents need for help with daily activities has increased, 2) Percentage of low-risk residents who lose control of the bowels or bladder, and 3) Percentage of short stay residents who have moderate to severe pain. Currently we are carrying out similar statistical analyses for the administrator turnover data. Different staffing levels can significantly affect QMs in nursing homes. Furthermore, administrative turnover in nursing home facilities, while required by HCFA and reported to states, is not part of NHC. Understanding how these variables affect nursing home quality is essential to providing good nursing home care. (Poster Presentation)
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.titleDiscovering the Links Between Quality Measures, Staffing, and Administrator Turnover in Missouri Nursing Homesen_GB
dc.identifier.urihttp://hdl.handle.net/10755/159300-
dc.description.abstract<table><tr><td colspan="2" class="item-title">Discovering the Links Between Quality Measures, Staffing, and Administrator Turnover in Missouri Nursing Homes</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">2005</td></tr><tr class="item-author"><td class="label">Author:</td><td class="value">Alexander, Gregory</td></tr><tr class="item-institute"><td class="label">P.I. Institution Name:</td><td class="value">University of Missouri-Columbia</td></tr><tr class="item-author-title"><td class="label">Title:</td><td class="value">Pre-doctoral Fellow</td></tr><tr class="item-address"><td class="label">Contact Address:</td><td class="value">Sinclair School of Nursing, 324 Clark Hall, Columbia, MO, 65211, USA</td></tr><tr class="item-phone"><td class="label">Contact Telephone:</td><td class="value">573-882-2803</td></tr><tr class="item-email"><td class="label">Email:</td><td class="value">gla1d7@mizzou.edu</td></tr><tr class="item-co-authors"><td class="label">Co-Authors:</td><td class="value">Marcia Flesner, Clinical Nurse Researcher; Timothy Patrick, Assistant Professor; and Marilyn Rantz, PhD, RN, FAAN, Professor</td></tr><tr><td colspan="2" class="item-abstract">The Institute of Medicine, in a report from the Committee on Improving Quality in Long Term Care (2001), indicated the continued use of standardized assessment data was essential for improving quality of resident care in long term care. This study utilized staffing measures, hours/resident/day, for Registered Nurses (RN), Licensed Vocational Nurses (LVN), and Certified Nurses Aides (CNA) to determine if there were significant differences in quality measure scores (QMs), obtained from Nursing Home Compare (NHC) in Feb 2004, across different staffing levels. In addition, this study used facility level data, collected from the Missouri Department of Health and Senior Services, to evaluate differences in QMs associated with frequency of administrative turnover ten years prior to this evaluation. Staffing measures were calculated for each group with a high (RN&gt;.44, LVN&gt;.73, CNA&gt;2.59), medium (RN&gt;.30, LVN&gt;.53, CNA&gt;2.14) and low (RN&lt;.30, LVN&lt;.53, CNA&lt;2.14) number of staffing hours/resident/day. Frequency of administrative turnover was calculated for the number of times each facility had an administrator change since 1994. Analysis of variance was used to determine mean differences in QMs using three staffing levels. Post hoc Bonferroni analyses were tabulated for each QM indicating a significant difference. Statistical analysis revealed significant differences in three QMs for staffing measures including: 1) Percentage of residents need for help with daily activities has increased, 2) Percentage of low-risk residents who lose control of the bowels or bladder, and 3) Percentage of short stay residents who have moderate to severe pain. Currently we are carrying out similar statistical analyses for the administrator turnover data. Different staffing levels can significantly affect QMs in nursing homes. Furthermore, administrative turnover in nursing home facilities, while required by HCFA and reported to states, is not part of NHC. Understanding how these variables affect nursing home quality is essential to providing good nursing home care. (Poster Presentation)</td></tr></table>en_GB
dc.date.available2011-10-26T21:53:18Z-
dc.date.issued2011-10-17en_GB
dc.date.accessioned2011-10-26T21:53:18Z-
dc.description.sponsorshipMidwest Nursing Research Societyen_GB
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