Dataset Information

A computational application for multi-skill nurse staffing in hospital units.

ABSTRACT:

Background

Approaches 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.

Methods

We 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.

Results

Experiments 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.

Conclusions

The 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.

SUBMITTER: Respicio A

PROVIDER: S-EPMC6025742 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature

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Publications

A computational application for multi-skill nurse staffing in hospital units.

Respicio Ana A Moz Margarida M Pato Margarida Vaz MV Somensi Rute R Dias Flores Cecília C

BMC medical informatics and decision making 20180628 1

<h4>Background</h4>Approaches 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.<h4>Methods</h4>We developed a method to determine the nu ...[more]

PMID: 29954378

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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.

Project description:INTRODUCTION:Postoperative cardiac events are frequent complications of surgery, and their occurrence could be associated with suboptimal nurse staffing practices, but the existing evidence remains scattered. We systematically reviewed studies linking nurse staffing practices to postoperative cardiac events and two related outcomes, all-cause mortality and failure-to-rescue. METHODS:A systematic search of the English/French literature was undertaken in the CINAHL, PsychInfo, and Medline databases. Studies were included if they: a) were published between 1996 and 2018; b) used a quantitative design; c) examined the association between at least one of seven staffing practices of interest (i.e., staffing levels, skill mix, work environment characteristics, levels of education and experience of the registered nurses, and overtime or temporary staff use) and postoperative cardiac events, mortality or failure-to-rescue; and d) were conducted among surgical patients. Data extraction, analysis, and synthesis, along with study methodological quality appraisal, were performed by two authors. High methodological heterogeneity precluded a formal meta-analysis. RESULTS:Among 3,375 retrieved articles, 44 studies were included (39 cross-sectional, 3 longitudinal, 1 case-control, 1 interrupted time series). Existing evidence shows that higher nurse staffing levels, a higher proportion of registered nurses with an education at the baccalaureate degree level, and more supportive work environments are related to lower rates of both 30-day mortality and failure-to-rescue. Other staffing practices were less often studied and showed inconsistent associations with mortality or failure-to-rescue. Similarly, few studies (n = 10) examined the associations between nurse staffing practices and postoperative cardiac events and showed inconsistent results. CONCLUSION:Higher nurse staffing levels, higher registered nurse education (baccalaureate degree level) and more supportive work environments were cross-sectionally associated with lower 30-day mortality and failure-to-rescue rates among surgical patients, but longitudinal studies are required to corroborate these associations. The existing evidence regarding postoperative cardiac events is limited, which warrants further investigation.

Dataset Information

A computational application for multi-skill nurse staffing in hospital units.

Background

Methods

Results

Conclusions

Publications

A computational application for multi-skill nurse staffing in hospital units.

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