The impact of understaffed shifts on nurse-sensitive outcomes

Aim To explore the relationship between exposure to understaffed shifts and nurse‐sensitive outcomes at the patient level. Background Nurse‐sensitive outcomes are adverse patient outcomes that can be used as indicators of the quality of nursing care. Design This study was conducted in 2014 and was a...

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Veröffentlicht in:Journal of advanced nursing 2015-07, Vol.71 (7), p.1564-1572
Hauptverfasser: Twigg, Diane E., Gelder, Lucy, Myers, Helen
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container_title Journal of advanced nursing
container_volume 71
creator Twigg, Diane E.
Gelder, Lucy
Myers, Helen
description Aim To explore the relationship between exposure to understaffed shifts and nurse‐sensitive outcomes at the patient level. Background Nurse‐sensitive outcomes are adverse patient outcomes that can be used as indicators of the quality of nursing care. Design This study was conducted in 2014 and was a secondary analysis of administrative data from a large acute care hospital in Western Australia. The sample included 36,529 patient admissions over a two‐year period from October 2004–November 2006. Methods An understaffed indicator variable was created from nurse staffing data and used to examine patient data to create a variable indicating the total number of understaffed shifts each patient had been exposed to during their hospital stay. Logistic regression was used to determine the odds of acquiring a nurse‐sensitive outcome for those exposed to understaffed shifts. Results The prevalence ratio showed that for each of the nurse‐sensitive outcomes there was an increase in prevalence for those who were exposed to an understaffed shift, with all ratios being greater than one. After adjusting for patient characteristics, nurse‐sensitive outcomes found to have the understaffed variable significant in the logistic regression model were surgical wound infection, urinary tract infection, pressure injury, pneumonia, deep vein thrombosis, upper gastrointestinal bleed, sepsis and physiological metabolic derangement. All odds ratios were small effects. Conclusion Preventing understaffing is a consideration for improving the quality of care for patients. Attributing the understaffing variable at the patient level enables exposure to be captured across ward changes increasing the sensitivity with which this variable can be measured.
doi_str_mv 10.1111/jan.12616
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Background Nurse‐sensitive outcomes are adverse patient outcomes that can be used as indicators of the quality of nursing care. Design This study was conducted in 2014 and was a secondary analysis of administrative data from a large acute care hospital in Western Australia. The sample included 36,529 patient admissions over a two‐year period from October 2004–November 2006. Methods An understaffed indicator variable was created from nurse staffing data and used to examine patient data to create a variable indicating the total number of understaffed shifts each patient had been exposed to during their hospital stay. Logistic regression was used to determine the odds of acquiring a nurse‐sensitive outcome for those exposed to understaffed shifts. Results The prevalence ratio showed that for each of the nurse‐sensitive outcomes there was an increase in prevalence for those who were exposed to an understaffed shift, with all ratios being greater than one. After adjusting for patient characteristics, nurse‐sensitive outcomes found to have the understaffed variable significant in the logistic regression model were surgical wound infection, urinary tract infection, pressure injury, pneumonia, deep vein thrombosis, upper gastrointestinal bleed, sepsis and physiological metabolic derangement. All odds ratios were small effects. Conclusion Preventing understaffing is a consideration for improving the quality of care for patients. Attributing the understaffing variable at the patient level enables exposure to be captured across ward changes increasing the sensitivity with which this variable can be measured.</description><identifier>ISSN: 0309-2402</identifier><identifier>EISSN: 1365-2648</identifier><identifier>DOI: 10.1111/jan.12616</identifier><identifier>PMID: 25572877</identifier><language>eng</language><publisher>England: Blackwell Publishing Ltd</publisher><subject>acute care ; Humans ; Length of Stay ; Middle Aged ; nurse staffing ; Nurse-Patient Relations ; nurse-sensitive outcomes ; Nurses ; Nursing ; Nursing care ; Nursing Staff, Hospital ; Patient admissions ; patient outcomes ; Personnel Staffing and Scheduling ; Quality of care ; Regression analysis ; Western Australia</subject><ispartof>Journal of advanced nursing, 2015-07, Vol.71 (7), p.1564-1572</ispartof><rights>2015 John Wiley &amp; Sons Ltd</rights><rights>2015 John Wiley &amp; Sons Ltd.</rights><rights>Copyright Wiley Subscription Services, Inc. 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Background Nurse‐sensitive outcomes are adverse patient outcomes that can be used as indicators of the quality of nursing care. Design This study was conducted in 2014 and was a secondary analysis of administrative data from a large acute care hospital in Western Australia. The sample included 36,529 patient admissions over a two‐year period from October 2004–November 2006. Methods An understaffed indicator variable was created from nurse staffing data and used to examine patient data to create a variable indicating the total number of understaffed shifts each patient had been exposed to during their hospital stay. Logistic regression was used to determine the odds of acquiring a nurse‐sensitive outcome for those exposed to understaffed shifts. Results The prevalence ratio showed that for each of the nurse‐sensitive outcomes there was an increase in prevalence for those who were exposed to an understaffed shift, with all ratios being greater than one. After adjusting for patient characteristics, nurse‐sensitive outcomes found to have the understaffed variable significant in the logistic regression model were surgical wound infection, urinary tract infection, pressure injury, pneumonia, deep vein thrombosis, upper gastrointestinal bleed, sepsis and physiological metabolic derangement. All odds ratios were small effects. Conclusion Preventing understaffing is a consideration for improving the quality of care for patients. 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After adjusting for patient characteristics, nurse‐sensitive outcomes found to have the understaffed variable significant in the logistic regression model were surgical wound infection, urinary tract infection, pressure injury, pneumonia, deep vein thrombosis, upper gastrointestinal bleed, sepsis and physiological metabolic derangement. All odds ratios were small effects. Conclusion Preventing understaffing is a consideration for improving the quality of care for patients. Attributing the understaffing variable at the patient level enables exposure to be captured across ward changes increasing the sensitivity with which this variable can be measured.</abstract><cop>England</cop><pub>Blackwell Publishing Ltd</pub><pmid>25572877</pmid><doi>10.1111/jan.12616</doi><tpages>9</tpages></addata></record>
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source Applied Social Sciences Index & Abstracts (ASSIA); MEDLINE; Wiley Online Library Journals Frontfile Complete
subjects acute care
Humans
Length of Stay
Middle Aged
nurse staffing
Nurse-Patient Relations
nurse-sensitive outcomes
Nurses
Nursing
Nursing care
Nursing Staff, Hospital
Patient admissions
patient outcomes
Personnel Staffing and Scheduling
Quality of care
Regression analysis
Western Australia
title The impact of understaffed shifts on nurse-sensitive outcomes
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