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How many nurses per patient? Measurements of nurse staffing in health services research.

ABSTRACT: OBJECTIVE: To compare alternative measures of nurse staffing and assess the relative strengths and limitations of each measure. DATA SOURCES/STUDY SETTING: Primary and secondary data from 2000 and 2002 on hospital nurse staffing from the American Hospital Association, California Office of Statewide Health Planning and Development, California Nursing Outcomes Coalition, and the California Workforce Initiative Survey. STUDY DESIGN: Hospital-level and unit-level data were compared using summary statistics, t-tests, and correlations. DATA COLLECTION/EXTRACTION METHODS: Data sources were matched for each hospital. When possible, hospital units or types of units were matched within each hospital. Productive nursing hours and direct patient care hours were converted to full-time equivalent employment and to nurse-to-patient ratios to compare nurse staffing as measured by different surveys. PRINCIPAL FINDINGS: The greatest differences in staffing measurement arise when unit-level data are compared with hospital-level aggregated data reported in large administrative databases. There is greater dispersion in the data obtained from publicly available, administrative data sources than in unit-level data; however, the unit-level data sources are limited to a select set of hospitals and are not available to many researchers. CONCLUSIONS: Unit-level data collection may be more precise. Differences between databases may account for differences in research findings.

SUBMITTER: Spetz J

PROVIDER: S-EPMC2653880 | biostudies-other | 2008 Oct

REPOSITORIES: biostudies-other

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How many nurses per patient? Measurements of nurse staffing in health services research.

Spetz Joanne J Donaldson Nancy N Aydin Carolyn C Brown Diane S DS

Health services research 20080505 5 Pt 1

<h4>Objective</h4>To compare alternative measures of nurse staffing and assess the relative strengths and limitations of each measure.<h4>Data sources/study setting</h4>Primary and secondary data from 2000 and 2002 on hospital nurse staffing from the American Hospital Association, California Office of Statewide Health Planning and Development, California Nursing Outcomes Coalition, and the California Workforce Initiative Survey.<h4>Study design</h4>Hospital-level and unit-level data were compare ...[more]

PMID: 18459953

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Project description:ObjectiveTo estimate and contrast the relationships between nurse staffing and health outcomes in nursing homes with low and high dementia census, to understand the association of staffing hours with dementia care quality.Data sources and study settingA national sample of nursing homes during 2017-2019 (pre-COVID). Data included the Payroll-Based Journal, Medicare Claims, Nursing Home Care Compare, and Long-Term Care Focus.Study designRetrospective, regression analyses. We estimated separate linear models predicting six long-term facility-level outcomes. Independent variables included staffing hours per resident-day (HPRD) interacted with the facility percentage of dementia residents, controlling for other resident and facility characteristics.Data collection/extraction methodsHospital-based nursing homes, those with fewer than 30% dementia residents, and missing data were excluded.Principal findingsWe found that registered nurses and certified nurse assistants HPRDs were likely to exhibit positive returns in terms of outcomes throughout most of the range of HPRD for both high and low-census dementia facilities, although, high- and low-dementia facilities differed in most outcome rates at all staffing levels. Average predicted antipsychotics and activities of daily living as functions of HPRD were worse in higher dementia facilities, independent movement, and hospitalizations did not differ significantly, and Emergency Rooms and pressure sores were worse in lower dementia facilities. Average marginal effects were not statistically different [CI included zero] between the high and low dementia facilities for any outcome.ConclusionsThese findings suggest that increasing staffing will improve outcomes by similar increments in both low- and high-dementia facilities for all outcomes. However, at any given level of staffing, absolute differences in outcomes between low- and high-dementia facilities remain, suggesting that additional staffing alone will not suffice to close these gaps. Further studies are required to identify opportunities for improvement in performance for both low- and high-dementia census facilities.

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.

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.

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How many nurses per patient? Measurements of nurse staffing in health services research.

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How many nurses per patient? Measurements of nurse staffing in health services research.

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