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Determining the Relationship between...
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Clemens, Sara Lynn.
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Determining the Relationship between Quality and Staffing Characteristics in Ontario Long-Term Care Homes.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Determining the Relationship between Quality and Staffing Characteristics in Ontario Long-Term Care Homes./
作者:
Clemens, Sara Lynn.
出版者:
Ann Arbor : ProQuest Dissertations & Theses, : 2020,
面頁冊數:
204 p.
附註:
Source: Dissertations Abstracts International, Volume: 81-12, Section: B.
Contained By:
Dissertations Abstracts International81-12B.
標題:
Health care management. -
電子資源:
https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=27959750
ISBN:
9798645499075
Determining the Relationship between Quality and Staffing Characteristics in Ontario Long-Term Care Homes.
Clemens, Sara Lynn.
Determining the Relationship between Quality and Staffing Characteristics in Ontario Long-Term Care Homes.
- Ann Arbor : ProQuest Dissertations & Theses, 2020 - 204 p.
Source: Dissertations Abstracts International, Volume: 81-12, Section: B.
Thesis (Ph.D.)--University of Toronto (Canada), 2020.
This item must not be sold to any third party vendors.
Research exploring the relationship between nurse staffing characteristics and quality in Long-Term Care (LTC) settings is needed to inform how staffing relates to quality. The present thesis addresses this research gap using a systematic review and two Ontario-based empirical studies exploring the relationship between LTC quality of care outcomes and nursing and personal care (NPC) staffing characteristics in LTC. The systematic review was conducted using OVID databases (Medline, CINAHL and Ageline) and several Cochrane databases to retrieve studies published between 2008 and 2017, and using the STROBE checklist to evaluate study quality and risk of bias. 31 studies were included in the systematic review. Findings align with previous literature reviews, with mixed results but mainly positive findings for registered nurses (RNs) and personal care (PC) providers (e.g., nursing assistants), and a mix of both positive and negative findings for registered practical nurses (RPNs). The two empirical cross-sectional studies examined the entire population of Ontario LTC residents in 2012 and used risk-adjusted multi-level multivariate regression to relate staffing characteristics to resident outcomes. In the empirical studies, four resident-level NPC-sensitive quality indicators from the Ontario Resident Assessment Instrument Minimum Data Set (prevalence of pain and incidence of falls, worsening continence and pressure ulcers) were regressed on four home-level NPC staffing characteristics (staffing level, skill mix, skills and competencies as well as roles and responsibilities). The studies also tested whether the observed relationships between staffing and outcomes varied according to the profit status of the LTC operator. Both empirical studies found similar mixed results, and few significant relationships in the full sample of residents. However, subgroup analyses, comparing residents with lower disablement, revealed RN staffing levels were generally associated with better outcomes, while RPNs had both protective and worsening effects on different indicators. Profit status had an inconsistent influence on relationships. Although many effects were substantial and supported hypotheses, many more were not significant or did not support hypotheses. Other factors influencing resident outcomes should be considered to develop new theory on what drives the differences in risk-adjusted quality measures. Longitudinal studies with more nuanced measurement of staff characteristics will also be useful.
ISBN: 9798645499075Subjects--Topical Terms:
2122906
Health care management.
Subjects--Index Terms:
Multi-level model
Determining the Relationship between Quality and Staffing Characteristics in Ontario Long-Term Care Homes.
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Research exploring the relationship between nurse staffing characteristics and quality in Long-Term Care (LTC) settings is needed to inform how staffing relates to quality. The present thesis addresses this research gap using a systematic review and two Ontario-based empirical studies exploring the relationship between LTC quality of care outcomes and nursing and personal care (NPC) staffing characteristics in LTC. The systematic review was conducted using OVID databases (Medline, CINAHL and Ageline) and several Cochrane databases to retrieve studies published between 2008 and 2017, and using the STROBE checklist to evaluate study quality and risk of bias. 31 studies were included in the systematic review. Findings align with previous literature reviews, with mixed results but mainly positive findings for registered nurses (RNs) and personal care (PC) providers (e.g., nursing assistants), and a mix of both positive and negative findings for registered practical nurses (RPNs). The two empirical cross-sectional studies examined the entire population of Ontario LTC residents in 2012 and used risk-adjusted multi-level multivariate regression to relate staffing characteristics to resident outcomes. In the empirical studies, four resident-level NPC-sensitive quality indicators from the Ontario Resident Assessment Instrument Minimum Data Set (prevalence of pain and incidence of falls, worsening continence and pressure ulcers) were regressed on four home-level NPC staffing characteristics (staffing level, skill mix, skills and competencies as well as roles and responsibilities). The studies also tested whether the observed relationships between staffing and outcomes varied according to the profit status of the LTC operator. Both empirical studies found similar mixed results, and few significant relationships in the full sample of residents. However, subgroup analyses, comparing residents with lower disablement, revealed RN staffing levels were generally associated with better outcomes, while RPNs had both protective and worsening effects on different indicators. Profit status had an inconsistent influence on relationships. Although many effects were substantial and supported hypotheses, many more were not significant or did not support hypotheses. Other factors influencing resident outcomes should be considered to develop new theory on what drives the differences in risk-adjusted quality measures. Longitudinal studies with more nuanced measurement of staff characteristics will also be useful.
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