Effects of nurse-to-patient ratio legislation on nurse staffing and patient mortality, readmissions, and length of stay: a prospective study in a panel of hospitals
Substantial evidence indicates that patient outcomes are more favourable in hospitals with better nurse staffing. One policy designed to achieve better staffing is minimum nurse-to-patient ratio mandates, but such policies have rarely been implemented or evaluated. In 2016, Queensland (Australia) im...
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| Published in: | The Lancet (British edition) Vol. 397; no. 10288; pp. 1905 - 1913 |
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| Main Authors: | , , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
England
Elsevier Ltd
22.05.2021
Elsevier B.V Elsevier Limited |
| Subjects: | |
| ISSN: | 0140-6736, 1474-547X, 1474-547X |
| Online Access: | Get full text |
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| Abstract | Substantial evidence indicates that patient outcomes are more favourable in hospitals with better nurse staffing. One policy designed to achieve better staffing is minimum nurse-to-patient ratio mandates, but such policies have rarely been implemented or evaluated. In 2016, Queensland (Australia) implemented minimum nurse-to-patient ratios in selected hospitals. We aimed to assess the effects of this policy on staffing levels and patient outcomes and whether both were associated.
For this prospective panel study, we compared Queensland hospitals subject to the ratio policy (27 intervention hospitals) and those that discharged similar patients but were not subject to ratios (28 comparison hospitals) at two timepoints: before implementation of ratios (baseline) and 2 years after implementation (post-implementation). We used standardised Queensland Hospital Admitted Patient Data, linked with death records, to obtain data on patient characteristics and outcomes (30-day mortality, 7-day readmissions, and length of stay [LOS]) for medical-surgical patients and survey data from 17 010 medical-surgical nurses in the study hospitals before and after policy implementation. Survey data from nurses were used to measure nurse staffing and, after linking with standardised patient data, to estimate the differential change in outcomes between patients in intervention and comparison hospitals, and determine whether nurse staffing changes were related to it.
We included 231 902 patients (142 986 in intervention hospitals and 88 916 in comparison hospitals) assessed at baseline (2016) and 257 253 patients (160 167 in intervention hospitals and 97 086 in comparison hospitals) assessed in the post-implementation period (2018). After implementation, mortality rates were not significantly higher than at baseline in comparison hospitals (adjusted odds ratio [OR] 1·07, 95% CI 0·97–1·17, p=0·18), but were significantly lower than at baseline in intervention hospitals (0·89, 0·84–0·95, p=0·0003). From baseline to post-implementation, readmissions increased in comparison hospitals (1·06, 1·01–1·12, p=0·015), but not in intervention hospitals (1·00, 0·95–1·04, p=0·92). Although LOS decreased in both groups post-implementation, the reduction was more pronounced in intervention hospitals than in comparison hospitals (adjusted incident rate ratio [IRR] 0·95, 95% CI 0·92–0·99, p=0·010). Staffing changed in hospitals from baseline to post-implementation: of the 36 hospitals with reliable staffing measures, 30 (83%) had more than 4·5 patients per nurse at baseline, with the number decreasing to 21 (58%) post-implementation. The majority of change was at intervention hospitals, and staffing improvements by one patient per nurse produced reductions in mortality (OR 0·93, 95% CI 0·86–0·99, p=0·045), readmissions (0·93, 0·89–0·97, p<0·0001), and LOS (IRR 0·97, 0·94–0·99, p=0·035). In addition to producing better outcomes, the costs avoided due to fewer readmissions and shorter LOS were more than twice the cost of the additional nurse staffing.
Minimum nurse-to-patient ratio policies are a feasible approach to improve nurse staffing and patient outcomes with good return on investment.
Queensland Health, National Institutes of Health, National Institute of Nursing Research. |
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| AbstractList | Substantial evidence indicates that patient outcomes are more favourable in hospitals with better nurse staffing. One policy designed to achieve better staffing is minimum nurse-to-patient ratio mandates, but such policies have rarely been implemented or evaluated. In 2016, Queensland (Australia) implemented minimum nurse-to-patient ratios in selected hospitals. We aimed to assess the effects of this policy on staffing levels and patient outcomes and whether both were associated.
For this prospective panel study, we compared Queensland hospitals subject to the ratio policy (27 intervention hospitals) and those that discharged similar patients but were not subject to ratios (28 comparison hospitals) at two timepoints: before implementation of ratios (baseline) and 2 years after implementation (post-implementation). We used standardised Queensland Hospital Admitted Patient Data, linked with death records, to obtain data on patient characteristics and outcomes (30-day mortality, 7-day readmissions, and length of stay [LOS]) for medical-surgical patients and survey data from 17 010 medical-surgical nurses in the study hospitals before and after policy implementation. Survey data from nurses were used to measure nurse staffing and, after linking with standardised patient data, to estimate the differential change in outcomes between patients in intervention and comparison hospitals, and determine whether nurse staffing changes were related to it.
We included 231 902 patients (142 986 in intervention hospitals and 88 916 in comparison hospitals) assessed at baseline (2016) and 257 253 patients (160 167 in intervention hospitals and 97 086 in comparison hospitals) assessed in the post-implementation period (2018). After implementation, mortality rates were not significantly higher than at baseline in comparison hospitals (adjusted odds ratio [OR] 1·07, 95% CI 0·97-1·17, p=0·18), but were significantly lower than at baseline in intervention hospitals (0·89, 0·84-0·95, p=0·0003). From baseline to post-implementation, readmissions increased in comparison hospitals (1·06, 1·01-1·12, p=0·015), but not in intervention hospitals (1·00, 0·95-1·04, p=0·92). Although LOS decreased in both groups post-implementation, the reduction was more pronounced in intervention hospitals than in comparison hospitals (adjusted incident rate ratio [IRR] 0·95, 95% CI 0·92-0·99, p=0·010). Staffing changed in hospitals from baseline to post-implementation: of the 36 hospitals with reliable staffing measures, 30 (83%) had more than 4·5 patients per nurse at baseline, with the number decreasing to 21 (58%) post-implementation. The majority of change was at intervention hospitals, and staffing improvements by one patient per nurse produced reductions in mortality (OR 0·93, 95% CI 0·86-0·99, p=0·045), readmissions (0·93, 0·89-0·97, p<0·0001), and LOS (IRR 0·97, 0·94-0·99, p=0·035). In addition to producing better outcomes, the costs avoided due to fewer readmissions and shorter LOS were more than twice the cost of the additional nurse staffing.
Minimum nurse-to-patient ratio policies are a feasible approach to improve nurse staffing and patient outcomes with good return on investment.
Queensland Health, National Institutes of Health, National Institute of Nursing Research. Summary Background Substantial evidence indicates that patient outcomes are more favourable in hospitals with better nurse staffing. One policy designed to achieve better staffing is minimum nurse-to-patient ratio mandates, but such policies have rarely been implemented or evaluated. In 2016, Queensland (Australia) implemented minimum nurse-to-patient ratios in selected hospitals. We aimed to assess the effects of this policy on staffing levels and patient outcomes and whether both were associated. Methods For this prospective panel study, we compared Queensland hospitals subject to the ratio policy (27 intervention hospitals) and those that discharged similar patients but were not subject to ratios (28 comparison hospitals) at two timepoints: before implementation of ratios (baseline) and 2 years after implementation (post-implementation). We used standardised Queensland Hospital Admitted Patient Data, linked with death records, to obtain data on patient characteristics and outcomes (30-day mortality, 7-day readmissions, and length of stay [LOS]) for medical-surgical patients and survey data from 17 010 medical-surgical nurses in the study hospitals before and after policy implementation. Survey data from nurses were used to measure nurse staffing and, after linking with standardised patient data, to estimate the differential change in outcomes between patients in intervention and comparison hospitals, and determine whether nurse staffing changes were related to it. Findings We included 231 902 patients (142 986 in intervention hospitals and 88 916 in comparison hospitals) assessed at baseline (2016) and 257 253 patients (160 167 in intervention hospitals and 97 086 in comparison hospitals) assessed in the post-implementation period (2018). After implementation, mortality rates were not significantly higher than at baseline in comparison hospitals (adjusted odds ratio [OR] 1·07, 95% CI 0·97–1·17, p=0·18), but were significantly lower than at baseline in intervention hospitals (0·89, 0·84–0·95, p=0·0003). From baseline to post-implementation, readmissions increased in comparison hospitals (1·06, 1·01–1·12, p=0·015), but not in intervention hospitals (1·00, 0·95–1·04, p=0·92). Although LOS decreased in both groups post-implementation, the reduction was more pronounced in intervention hospitals than in comparison hospitals (adjusted incident rate ratio [IRR] 0·95, 95% CI 0·92–0·99, p=0·010). Staffing changed in hospitals from baseline to post-implementation: of the 36 hospitals with reliable staffing measures, 30 (83%) had more than 4·5 patients per nurse at baseline, with the number decreasing to 21 (58%) post-implementation. The majority of change was at intervention hospitals, and staffing improvements by one patient per nurse produced reductions in mortality (OR 0·93, 95% CI 0·86–0·99, p=0·045), readmissions (0·93, 0·89–0·97, p<0·0001), and LOS (IRR 0·97, 0·94–0·99, p=0·035). In addition to producing better outcomes, the costs avoided due to fewer readmissions and shorter LOS were more than twice the cost of the additional nurse staffing. Interpretation Minimum nurse-to-patient ratio policies are a feasible approach to improve nurse staffing and patient outcomes with good return on investment. Funding Queensland Health, National Institutes of Health, National Institute of Nursing Research. Substantial evidence indicates that patient outcomes are more favourable in hospitals with better nurse staffing. One policy designed to achieve better staffing is minimum nurse-to-patient ratio mandates, but such policies have rarely been implemented or evaluated. In 2016, Queensland (Australia) implemented minimum nurse-to-patient ratios in selected hospitals. We aimed to assess the effects of this policy on staffing levels and patient outcomes and whether both were associated.BACKGROUNDSubstantial evidence indicates that patient outcomes are more favourable in hospitals with better nurse staffing. One policy designed to achieve better staffing is minimum nurse-to-patient ratio mandates, but such policies have rarely been implemented or evaluated. In 2016, Queensland (Australia) implemented minimum nurse-to-patient ratios in selected hospitals. We aimed to assess the effects of this policy on staffing levels and patient outcomes and whether both were associated.For this prospective panel study, we compared Queensland hospitals subject to the ratio policy (27 intervention hospitals) and those that discharged similar patients but were not subject to ratios (28 comparison hospitals) at two timepoints: before implementation of ratios (baseline) and 2 years after implementation (post-implementation). We used standardised Queensland Hospital Admitted Patient Data, linked with death records, to obtain data on patient characteristics and outcomes (30-day mortality, 7-day readmissions, and length of stay [LOS]) for medical-surgical patients and survey data from 17 010 medical-surgical nurses in the study hospitals before and after policy implementation. Survey data from nurses were used to measure nurse staffing and, after linking with standardised patient data, to estimate the differential change in outcomes between patients in intervention and comparison hospitals, and determine whether nurse staffing changes were related to it.METHODSFor this prospective panel study, we compared Queensland hospitals subject to the ratio policy (27 intervention hospitals) and those that discharged similar patients but were not subject to ratios (28 comparison hospitals) at two timepoints: before implementation of ratios (baseline) and 2 years after implementation (post-implementation). We used standardised Queensland Hospital Admitted Patient Data, linked with death records, to obtain data on patient characteristics and outcomes (30-day mortality, 7-day readmissions, and length of stay [LOS]) for medical-surgical patients and survey data from 17 010 medical-surgical nurses in the study hospitals before and after policy implementation. Survey data from nurses were used to measure nurse staffing and, after linking with standardised patient data, to estimate the differential change in outcomes between patients in intervention and comparison hospitals, and determine whether nurse staffing changes were related to it.We included 231 902 patients (142 986 in intervention hospitals and 88 916 in comparison hospitals) assessed at baseline (2016) and 257 253 patients (160 167 in intervention hospitals and 97 086 in comparison hospitals) assessed in the post-implementation period (2018). After implementation, mortality rates were not significantly higher than at baseline in comparison hospitals (adjusted odds ratio [OR] 1·07, 95% CI 0·97-1·17, p=0·18), but were significantly lower than at baseline in intervention hospitals (0·89, 0·84-0·95, p=0·0003). From baseline to post-implementation, readmissions increased in comparison hospitals (1·06, 1·01-1·12, p=0·015), but not in intervention hospitals (1·00, 0·95-1·04, p=0·92). Although LOS decreased in both groups post-implementation, the reduction was more pronounced in intervention hospitals than in comparison hospitals (adjusted incident rate ratio [IRR] 0·95, 95% CI 0·92-0·99, p=0·010). Staffing changed in hospitals from baseline to post-implementation: of the 36 hospitals with reliable staffing measures, 30 (83%) had more than 4·5 patients per nurse at baseline, with the number decreasing to 21 (58%) post-implementation. The majority of change was at intervention hospitals, and staffing improvements by one patient per nurse produced reductions in mortality (OR 0·93, 95% CI 0·86-0·99, p=0·045), readmissions (0·93, 0·89-0·97, p<0·0001), and LOS (IRR 0·97, 0·94-0·99, p=0·035). In addition to producing better outcomes, the costs avoided due to fewer readmissions and shorter LOS were more than twice the cost of the additional nurse staffing.FINDINGSWe included 231 902 patients (142 986 in intervention hospitals and 88 916 in comparison hospitals) assessed at baseline (2016) and 257 253 patients (160 167 in intervention hospitals and 97 086 in comparison hospitals) assessed in the post-implementation period (2018). After implementation, mortality rates were not significantly higher than at baseline in comparison hospitals (adjusted odds ratio [OR] 1·07, 95% CI 0·97-1·17, p=0·18), but were significantly lower than at baseline in intervention hospitals (0·89, 0·84-0·95, p=0·0003). From baseline to post-implementation, readmissions increased in comparison hospitals (1·06, 1·01-1·12, p=0·015), but not in intervention hospitals (1·00, 0·95-1·04, p=0·92). Although LOS decreased in both groups post-implementation, the reduction was more pronounced in intervention hospitals than in comparison hospitals (adjusted incident rate ratio [IRR] 0·95, 95% CI 0·92-0·99, p=0·010). Staffing changed in hospitals from baseline to post-implementation: of the 36 hospitals with reliable staffing measures, 30 (83%) had more than 4·5 patients per nurse at baseline, with the number decreasing to 21 (58%) post-implementation. The majority of change was at intervention hospitals, and staffing improvements by one patient per nurse produced reductions in mortality (OR 0·93, 95% CI 0·86-0·99, p=0·045), readmissions (0·93, 0·89-0·97, p<0·0001), and LOS (IRR 0·97, 0·94-0·99, p=0·035). In addition to producing better outcomes, the costs avoided due to fewer readmissions and shorter LOS were more than twice the cost of the additional nurse staffing.Minimum nurse-to-patient ratio policies are a feasible approach to improve nurse staffing and patient outcomes with good return on investment.INTERPRETATIONMinimum nurse-to-patient ratio policies are a feasible approach to improve nurse staffing and patient outcomes with good return on investment.Queensland Health, National Institutes of Health, National Institute of Nursing Research.FUNDINGQueensland Health, National Institutes of Health, National Institute of Nursing Research. |
| Audience | Academic |
| Author | Yates, Patsy McHugh, Matthew D Sloane, Douglas M Windsor, Carol Aiken, Linda H Douglas, Clint |
| Author_xml | – sequence: 1 givenname: Matthew D surname: McHugh fullname: McHugh, Matthew D email: mchughm@nursing.upenn.edu organization: School of Nursing, Center for Health Outcomes and Policy Research, University of Pennsylvania, Philadelphia, PA, USA – sequence: 2 givenname: Linda H surname: Aiken fullname: Aiken, Linda H organization: School of Nursing, Center for Health Outcomes and Policy Research, University of Pennsylvania, Philadelphia, PA, USA – sequence: 3 givenname: Douglas M surname: Sloane fullname: Sloane, Douglas M organization: School of Nursing, Center for Health Outcomes and Policy Research, University of Pennsylvania, Philadelphia, PA, USA – sequence: 4 givenname: Carol surname: Windsor fullname: Windsor, Carol organization: School of Nursing, Queensland University of Technology, Kelvin Grove, QLD, Australia – sequence: 5 givenname: Clint surname: Douglas fullname: Douglas, Clint organization: School of Nursing, Queensland University of Technology, Kelvin Grove, QLD, Australia – sequence: 6 givenname: Patsy surname: Yates fullname: Yates, Patsy organization: School of Nursing, Queensland University of Technology, Kelvin Grove, QLD, Australia |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/33989553$$D View this record in MEDLINE/PubMed |
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| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 All authors contributed to the interpretation of the data and preparation of the manuscript. All authors had full access to all the data in the study and had final responsibility for the decision to submit for publication. All authors contributed to the conception and design of the study. MDM, LHA, CW, CD, and PY contributed to the collection of data. MDM and DMS accessed, verified, and oversaw analysis of the data. All authors approved the final manuscript. Contributors |
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| SubjectTerms | Aged Analysis Australia Cause of Death Female Health Policy Hospitals Humans Intervention Legislation Length of Stay - statistics & numerical data Male Medical personnel Medical research Medicine, Experimental Middle Aged Mortality Nurses Nursing Nursing services Nursing Staff, Hospital - supply & distribution Patient Readmission - statistics & numerical data Patient satisfaction Patients Personnel Staffing and Scheduling - statistics & numerical data Policies Polls & surveys Prospective Studies Quality of Health Care - statistics & numerical data Ratios Return on investment |
| Title | Effects of nurse-to-patient ratio legislation on nurse staffing and patient mortality, readmissions, and length of stay: a prospective study in a panel of hospitals |
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