Quality outcomes of hospital supplemental nurse staffing.
Ontology highlight
ABSTRACT:
SUBMITTER: Xue Y
PROVIDER: S-EPMC5340260 | biostudies-literature | 2012 Dec
REPOSITORIES: biostudies-literature
Publications
Quality outcomes of hospital supplemental nurse staffing.
Xue Ying Y Aiken Linda H LH Freund Deborah A DA Noyes Katia K
The Journal of nursing administration 20121201 12
Use of supplemental RNs (SRNs) is common practice among US hospitals to fill gaps in nurse staffing. The objective of this study was to examine the relationship between use of SRNs and patient outcomes. Multilevel modeling was performed to analyze hospital administrative data from 19 hospital units in a large tertiary medical center for the years 2003 to 2006. Patient outcomes included in-hospital mortality, medication errors, falls, pressure ulcers, and patient satisfaction with nurses. Use of ...[more]
Similar Datasets
Project description:ObjectiveThe objective of this study was to addresses the basic question of whether alternative legislative approaches are effective in encouraging hospitals to increase nurse staffing.MethodsUsing 16 years of nationally representative hospital-level data from the American Hospital Association (AHA) annual survey, we employed a difference-in-difference design to compare changes in productive hours per patient day for registered nurses (RNs), licensed practical/vocational nurses (LPNs), and nursing assistive personnel (NAP) in the state that mandated staffing ratios, states that legislated staffing committees, and states that legislated public reporting, to changes in states that did not implement any nurse staffing legislation before and after the legislation was implemented. We constructed multivariate linear regression models to assess the effects with hospital and year fixed effects, controlling for hospital-level characteristics and state-level factors.ResultsCompared with states with no legislation, the state that legislated minimum staffing ratios had an 0.996 (P<0.01) increase in RN hours per patient day and 0.224 (P<0.01) increase in NAP hours after the legislation was implemented, but no statistically significant changes in RN or NAP hours were found in states that legislated a staffing committee or public reporting. The staffing committee approach had a negative effect on LPN hours (difference-in-difference=-0.076, P<0.01), while the public reporting approach had a positive effect on LPN hours (difference-in-difference=0.115, P<0.01). There was no statistically significant effect of staffing mandate on LPN hours.ConclusionsWhen we included California in the comparison, our model suggests that neither the staffing committee nor the public reporting approach alone are effective in increasing hospital RN staffing, although the public reporting approach appeared to have a positive effect on LPN staffing. When we excluded California form the model, public reporting also had a positive effect on RN staffing. Future research should examine patient outcomes associated with these policies, as well as potential cost savings for hospitals from reduced nurse turnover rates.
| S-EPMC8428863 | biostudies-literature
Project description:BackgroundCross-sectional studies of hospital-level administrative data have suggested that 4 nurse staffing practices-using adequate staffing levels, higher proportions of registered nurses (RNs) (skill mix), and more educated and experienced RNs-are each associated with reduced hospital mortality. To increase the validity of this evidence, patient-level longitudinal studies assessing the simultaneous associations of these staffing practices with mortality are required.MethodsA dynamic cohort of 146,349 adult medical, surgical, and intensive care patients admitted to a Canadian University Health Center was followed for 7 years (2010-2017). We used a multivariable Cox proportional hazards model to estimate the associations between patients' time-varying cumulative exposure to measures of RN understaffing, skill mix, education, and experience, each relative to nursing unit and shift means, and the hazard of in-hospital mortality, while adjusting for patient and nursing unit characteristics, and modeling the current nursing unit of hospitalization as a random effect.ResultsOverall, 4854 in-hospital deaths occurred during 3,478,603 patient-shifts of follow-up (13.95 deaths/10,000 patient-shifts). In multivariable analyses, every 5% increase in the cumulative proportion of understaffed shifts was associated with a 1.0% increase in mortality (hazard ratio: 1.010; 95% confidence interval: 1.002-1.017; P=0.009). Moreover, every 5% increase in the cumulative proportion of worked hours by baccalaureate-prepared RNs was associated with a 2.0% reduction of mortality (hazard ratio: 0.980; 95% confidence interval: 0.965-0.995, P=0.008). RN experience and skill mix were not significantly associated with mortality.ConclusionReducing the frequency of understaffed shifts and increasing the proportion of baccalaureate-prepared RNs are associated with reduced hospital mortality.
| S-EPMC7641184 | biostudies-literature
Project description:BackgroundApproaches to nurse staffing are commonly concerned with determining the minimum number of care hours according to the illness severity of patients. However, there is a gap in the literature considering multi-skill and multi-shift nurse staffing. This study addresses nurse staffing per skill category, at a strategical decision level, by considering the organization of work in shifts and coping with variability in demand.MethodsWe developed a method to determine the nursing staff levels in a hospital, given the required patient assistance. This method relies on a new mathematical model for complying with the legislation and guidelines while minimizing salary costs. A spreadsheet-based tool was developed to embed the model and to allow simulating different scenarios and evaluating the impact of demand fluctuations, thus supporting decision-making on staff dimensioning.ResultsExperiments were carried out considering real data from a Brazilian hospital unit. The results obtained by the model support the current total staff level in the unit under study. However, the distribution of staff among different skill categories revealed that the current real situation can be improved.ConclusionsThe method allows the determining of staff level per shift and skill depending on the mix of patients' illness severity. Hospital management is offered the possibility of optimizing the staff level using a spreadsheet, a tool most managers are familiar with. In addition, it is possible to evaluate the implications of decisions on workforce dimensioning by simulating different demand scenarios. This tool can be easily adapted to other hospitals, using local rules and legislation.
| S-EPMC6025742 | biostudies-literature
Project description:ObjectiveTo examine the associations between Medicaid expansion and nurse staffing ratios and hospital-wide readmission rates.Data sourcesSecondary data from the 2011-2016 Healthcare Cost Report Information System, the American Hospital Association Annual Survey, and the Hospital Compare data.Study designDifference-in-difference models are used to compare outcomes in hospitals located in states that expanded Medicaid with those located in nonexpansion states. The changes in nurse staffing ratios and hospital-wide readmission rates are calculated in each one of the postexpansion years (2014, 2015, and 2016), compared to pre-expansion.Principal findingsResults indicate that nurse staffing ratios increased, whereas hospital-wide readmission rates declined in expansion states relative to nonexpansion states. Nurse staffing ratios increased by 0.33, 0.42, and 0.46 registered nurses hours per adjusted patient days in 2014, 2015, and 2016 in hospitals located in expansion states, compared with hospitals in nonexpansion states after expansion. This increase was statistically significant (P < .001) in 2015 and 2016, but marginally significant (P = .016) in 2014. Hospital-wide readmission rates statistically significantly decreased by 9, 16, and 18 per 10 000 patients (P < .001) in 2014, 2015, and 2016, respectively, in expansion vs nonexpansion states hospitals after expansion.ConclusionsMedicaid expansion was associated with gradually improved hospitals' nurse staffing ratios and hospital-wide readmission rates from 2014 through 2016. The continued monitoring of quality measures of hospitals can help assess the impact of Medicaid expansion over a longer period of time.
| S-EPMC7240770 | biostudies-literature
Project description:AimAim of this study is to systematically review and synthesize available evidence to identify the association between nurse staffing methodologies and nurse and patient outcomes.DesignSystematic review and narrative synthesis.Data sourcesA search of MEDLINE (EBSCO), CINAHL (EBSCO) and Web of Science was conducted for studies published in English between January 2000 and January 2020.Review methodsThe reporting of this review and narrative synthesis was guided by the preferred reporting items for systematic and meta-analysis guidelines (PRISMA) statement and data synthesis guided by the Synthesis Without Meta-analysis (SWiM) guideline. The quality of each article was assessed using the Mixed Methods Appraisal Tool.ResultsTwenty-two studies met the inclusion criteria. Twenty-one used the mandated minimum nurse-to-patient ratio methodology and one study assessed the number of nurse hours per patient day staffing methodology. Both methodologies were mandated. All studies that reported on nurse outcomes demonstrated an improvement associated with the implementation of mandated minimum nurse-to-patient ratio, but findings related to patient outcomes were inconclusive.ConclusionsEvidence on the impact of specific nurse staffing methodologies and patient and nurse outcomes remains highly limited. Future studies that examine the impact of specific staffing methodologies on outcomes are required to inform this fundamental area of management and practice.
| S-EPMC9291075 | biostudies-literature
Project description:OBJECTIVES:To assess whether Massachusetts legislation directed at ICU nurse staffing was associated with improvements in patient outcomes. DESIGN:Retrospective cohort study; difference-in-difference design to compare outcomes in Massachusetts with outcomes of other states (before and after the March 31, 2016, compliance deadline). SETTING:Administrative claims data collected from medical centers across the United States (Vizient). PATIENTS:Adults between 18 and 99 years old who were admitted to ICUs for greater than or equal to 1 day. INTERVENTIONS:Massachusetts General Law c. 111, § 231, which established 1) maximum patient-to-nurse assignments of 2:1 in the ICU and 2) that this determination should be based on a patient acuity tool and by the staff nurses in the unit. MEASUREMENTS AND MAIN RESULTS:Nurse staffing increased similarly in Massachusetts (n = 11 ICUs, Baseline patient-to-nurse ratio 1.38?±?0.16 to Post-mandate 1.28?±?0.15; p = 0.006) and other states (n = 88 ICUs, Baseline 1.35?±?0.19 to Post-mandate 1.31?±?0.17; p = 0.002; difference-in-difference p = 0.20). Massachusetts ICU nurse staffing regulations were not associated with changes in hospital mortality within Massachusetts (Baseline n = 29,754, standardized mortality ratio 1.20?±?0.04 to Post-mandate n = 30,058, 1.15?±?0.04; p = 0.11) or when compared with changes in hospital mortality in other states (Baseline n = 572,952, 1.15?±?0.01 to Post-mandate n = 567,608, 1.09?±?0.01; difference-in-difference p = 0.69). Complications (Massachusetts: Baseline 0.68% to Post-mandate 0.67%; other states: Baseline 0.72% to Post-mandate 0.72%; difference-in-difference p = 0.92) and do-not-resuscitate orders (Massachusetts: Baseline 13.5% to Post-mandate 15.4%; other states: Baseline 12.3% to Post-mandate 14.5%; difference-in-difference p = 0.07) also remained unchanged relative to secular trends. Results were similar in interrupted time series analysis, as well as in subgroups of community hospitals and workload intensive patients receiving mechanical ventilation. CONCLUSIONS:State regulation of patient-to-nurse staffing with the aid of patient complexity scores in intensive care was not associated with either increased nurse staffing or changes in patient outcomes.
| S-EPMC6138549 | biostudies-literature
Project description:Although nurses are the most likely first responders to witness an in-hospital cardiac arrest (IHCA) and provide treatment, little research has been undertaken to determine what features of nursing are related to cardiac arrest outcomes.To determine the association between nurse staffing, nurse work environments, and IHCA survival.Cross-sectional study of data from: (1) the American Heart Association's Get With The Guidelines-Resuscitation database; (2) the University of Pennsylvania Multi-State Nursing Care and and Patient Safety; and (3) the American Hospital Association annual survey. Logistic regression models were used to determine the association of the features of nursing and IHCA survival to discharge after adjusting for hospital and patient characteristics.A total of 11,160 adult patients aged 18 and older between 2005 and 2007 in 75 hospitals in 4 states (Pennsylvania, Florida, California, and New Jersey).Each additional patient per nurse on medical-surgical units was associated with a 5% lower likelihood of surviving IHCA to discharge (odds ratio=0.95; 95% confidence interval, 0.91-0.99). Further, patients cared for in hospitals with poor work environments had a 16% lower likelihood of IHCA survival (odds ratio=0.84; 95% confidence interval, 0.71-0.99) than patients cared for in hospitals with better work environments.Better work environments and decreased patient-to-nurse ratios on medical-surgical units are associated with higher odds of patient survival after an IHCA. These results add to a large body of literature suggesting that outcomes are better when nurses have a more reasonable workload and work in good hospital work environments. Improving nurse working conditions holds promise for improving survival following IHCA.
| S-EPMC4841621 | biostudies-literature
Project description:To determine if sufficient nurse staffing reduced in-hospital fractures in acute care hospitals.The Japanese Diagnosis Procedure Combination inpatient (DPC) database from July 2010 to March 2014 linked with the Surveys for Medical Institutions.We conducted a retrospective cohort study to examine the association of inpatient nurse-to-occupied bed ratio (NBR) with in-hospital fractures. Multivariable logistic regression with generalized estimating equations was performed, adjusting for patient characteristics and hospital characteristics.We identified 770,373 patients aged 50 years or older who underwent planned major surgery for some forms of cancer or cardiovascular diseases. We used ICD-10 codes and postoperative procedure codes to identify patients with in-hospital fractures. Hospital characteristics were obtained from the "Survey of Medical Institutions and Hospital Report" and "Annual Report for Functions of Medical Institutions."Overall, 662 (0.09 percent) in-hospital fractures were identified. Logistic regression analysis showed that the proportion of in-hospital fractures in the group with the highest NBR was significantly lower than that in the group with the lowest NBR (adjusted odd ratios, 0.67; 95 percent confidence interval, 0.44-0.99; p = .048).Sufficient nurse staffing may be important to reduce postsurgical in-hospital fractures in acute care hospitals.
| S-EPMC5441478 | biostudies-other
Project description:ObjectiveTo estimate the effects of electronic medical records (EMR) implementation on medical-surgical acute unit costs, length of stay, nurse staffing levels, nursing skill mix, nurse cost per hour, and nurse-sensitive patient outcomes.Data sourcesData on EMR implementation came from the 1998-2007 HIMSS Analytics Databases. Data on nurse staffing and patient outcomes came from the 1998-2007 Annual Financial Disclosure Reports and Patient Discharge Databases of the California Office of Statewide Health Planning and Development (OSHPD).MethodsLongitudinal analysis of an unbalanced panel of 326 short-term, general acute care hospitals in California. Marginal effects estimated using fixed effects (within-hospital) OLS regression.Principal findingsEMR implementation was associated with 6-10 percent higher cost per discharge in medical-surgical acute units. EMR stage 2 increased registered nurse hours per patient day by 15-26 percent and reduced licensed vocational nurse cost per hour by 2-4 percent. EMR stage 3 was associated with 3-4 percent lower rates of in-hospital mortality for conditions.ConclusionsOur results suggest that advanced EMR applications may increase hospital costs and nurse staffing levels, as well as increase complications and decrease mortality for some conditions. Contrary to expectation, we found no support for the proposition that EMR reduced length of stay or decreased the demand for nurses.
| S-EPMC2910563 | biostudies-literature
Project description:ObjectivesTo determine the impact of unit-level nurse staffing on quality of discharge teaching, patient perception of discharge readiness, and postdischarge readmission and emergency department (ED) visits, and cost-benefit of adjustments to unit nurse staffing.Data sourcesPatient questionnaires, electronic medical records, and administrative data for 1,892 medical-surgical patients from 16 nursing units within four acute care hospitals between January and July 2008.DesignNested panel data with hospital and unit-level fixed effects and patient and unit-level control variables.Data collection/extractionRegistered nurse (RN) staffing was recorded monthly in hours-per-patient-day. Patient questionnaires were completed before discharge. Thirty-day readmission and ED use with reimbursement data were obtained by cross-hospital electronic searches.Principal findingsHigher RN nonovertime staffing decreased odds of readmission (OR=0.56); higher RN overtime staffing increased odds of ED visit (OR=1.70). RN nonovertime staffing reduced ED visits indirectly, via a sequential path through discharge teaching quality and discharge readiness. Cost analysis projected total savings from 1 SD increase in RN nonovertime staffing and decrease in RN overtime of U.S.$11.64 million and U.S.$544,000 annually for the 16 study units.ConclusionsPostdischarge utilization costs could potentially be reduced by investment in nursing care hours to better prepare patients before hospital discharge.
| S-EPMC3207188 | biostudies-literature