The Safer Nursing Care Tool as a guide to nurse staffing requirements on hospital wards: observational and modelling study

Costs and cost-effectiveness of improved nurse staffing levels and skill mix in acute hospitals: A systematic review

BACKGROUND

Extensive research shows associations between increased nurse staffing levels, skill mix and patient outcomes. However, showing that improved staffing levels are linked to improved outcomes is not sufficient to provide a case for increasing them. This review of economic studies in acute hospitals aims to identify costs and consequences associated with different nurse staffing configurations in hospitals.

METHODS

We included economic studies exploring the effect of variation in nurse staffing. We searched PubMed, CINAHL, Embase Econlit, Cochrane library, DARE, NHS EED and the INAHTA website. Risk of bias was assessed using a framework based on the NICE guidance for public health reviews and Henrikson's framework for economic evaluations. Inclusion, data extraction and critical appraisal were undertaken by pairs of reviewers with disagreements resolved by the entire review team. Results were synthesised using a hierarchical matrix to summarise findings of economic evaluations.

RESULTS

We found 23 observational studies conducted in the United States of America (16), Australia, Belgium, China, South Korea, and the United Kingdom (3). Fourteen had high risk of bias and nine moderate. Most studies addressed levels of staffing by RNs and/or licensed practical nurses. Six studies found that increased nurse staffing levels were associated with improved outcomes and reduced or unchanged net costs, but most showed increased costs and outcomes. Studies undertaken outside the USA showed that increased nurse staffing was likely to be cost-effective at a per capita gross domestic product (GDP) threshold or lower. Four studies found that increased skill mix was associated with improved outcomes but increased staff costs. Three studies considering net costs found increased registered nurse skill mix associated with net savings and similar or improved outcomes.

CONCLUSION

Although more evidence on cost-effectiveness is still needed, increases in absolute or relative numbers of registered nurses in general medical and surgical wards have the potential to be highly cost-effective. The preponderance of the evidence suggests that increasing the proportion of registered nurses is associated with improved outcomes and, potentially, reduced net cost. Conversely, policies that lead to a reduction in the proportion of registered nurses in nursing teams could give worse outcomes at increased costs and there is no evidence that such approaches are cost-effective. In an era of registered nurse scarcity, these results favour investment in registered nurse supply as opposed to using lesser qualified staff as substitutes, especially where baseline nurse staffing and skill mix are low.

REGISTRATION

PROSPERO (CRD42021281202).

TWEETABLE ABSTRACT

Increasing registered nurse staffing and skill mix can be a net cost-saving solution to nurse shortages. Contrary to the strong policy push towards a dilution of nursing skill mix, investment in supply of RNs should become the priority.

Measuring patient acuity and nursing care needs in South Korea: application of a new patient classification system

BACKGROUND

An accurate and reliable patient classification system (PCS) can help inform decisions regarding adequate assignments for nurse staffing. This study aimed to evaluate the criterion validity of the Asan Patient Classification System (APCS), a new tertiary hospital-specific PCS, by comparing its rating and total scores with those of KPCS-1 and KPCS-GW for measuring patient activity and nursing needs.

METHODS

We performed a retrospective analysis of the medical records of 50,314 inpatients admitted to the general wards of a tertiary teaching hospital in Seoul, South Korea in March, June, September, and December 2019. Spearman's correlation and Kappa statistics according to quartiles were calculated to examine the criterion validity of the APCS compared with the KPCS-1 and KPCS-GW.

RESULTS

The average patient classification score was 28.3 points for APCS, 25.7 points for KPCS-1, and 21.6 points for KPCS-GW. The kappa value between APCS and KPCS-1 was 0.91 (95% CI:0.9072, 0.9119) and that between APCS and KPCS-GW was 0.88 (95% CI:0.8757, 0.8810). Additionally, Spearman's correlation coefficients among APCS, KPCS-1, and KPCS-GW showed a very strong correlation. However, 10.8% of the participants' results were inconsistent, and KPCS-1 tended to classify patients into groups with lower nursing needs compared to APCS.

CONCLUSION

This study showed that electronic health record-generated APCS can provide useful information on patients' severity and nursing activities to measure workload estimation. Additional research is needed to develop and implement a real-world EHR-based PCS system to accommodate for direct and indirect nursing care while considering diverse population and dynamic healthcare system.

Assessment of level of care recommendations and nursing acuity scores following an appropriateness of care intervention

BACKGROUND

As part of a multiprong intervention to eliminate waste in cost of hospital accommodations, the InterQual Level of Care (LOC) criteria was deployed by our institution to assign patients to one of three LOCs: acute care, intermediate intensive care unit (IICU) or intensive care unit (ICU). In that intervention, which sought to decrease the number of patients in a higher LOC than what was clinically necessary, patient safety balancing metrics were stable. However, nursing workload, a key balancing metric, has yet to be examined. In this study, we examine nursing workload before and after the intervention using a proprietary nursing acuity score.

METHODS

A retrospective study was conducted analysing admissions at the study institution. Patient's LOC recommendation (as determined by InterQual), assigned (actual) LOC and nursing acuity scores were collected and analysed. Average nursing acuity scores were compared across patients whose InterQual recommendation aligned with actual LOC ('Acute Match' or 'IICU Match') versus patients who were recommended to be in acute care but were receiving IICU care ('Mismatch').

RESULTS

Following the intervention, the per cent of patients in the Mismatch cohort decreased from 13% to 7%. Prior to the intervention, average nursing acuity score for the Mismatch cohort was less than the IICU Match cohort and greater than Acute Match cohort in all departments analysed. After the intervention period, average acuity score in the Mismatch cohort exceeded that of the Acute Match cohort in all eight departments, but the Mismatch cohort's scores differed from the IICU Match cohort in only one department.

CONCLUSION

Collectively, this study demonstrates that our intervention successfully decreased inappropriate use of the IICU LOC, and that the residual Mismatch cohort is a distinct entity, with nursing needs that exceed that of the Acute Match cohort. Thus, a higher LOC can be justified. This demonstrates that a nursing workload metric such as the nursing acuity score can be a valuable complement to clinical criteria such as the InterQual LOC criteria to objectively determine patient's true, necessary LOC and ensure that nursing staff feels adequately staffed to care for patients.

Consensus Development Project (CDP): An overview of staffing for safe and effective nursing care

We present an overview of the research evidence on nurse staffing levels in acute hospitals, and how it has been applied to policy and practice, focussing primarily on the UK. Drawing on research reviews and examples of specific studies, we outline the current state of knowledge. Much of the evidence comes from cross-sectional studies. More recently, longitudinal studies allow a causal link between staffing and outcomes to be inferred. Lack of specificity on staffing levels has hindered application of research findings to practice; research rarely specifies how many nurses are needed for safe and effective care. The most significant impediment to achieving safe staffing has been an underestimation of the number of RNs needed and overestimation of the potential for substitution, resulting in low baseline staffing and a national shortage of RNs. Repeatedly, new staffing solutions are sought rather than tackle the problem of too few RNs head-on.

Factors That Influence Nurse Staffing Levels in Acute Care Hospital Settings

PURPOSE

To identify which patient and hospital characteristics are related to nurse staffing levels in acute care hospital settings.

DESIGN

A cross-sectional design was used for this study.

METHODS

The sample comprised 1,004 patients across 10 hospitals in the Andalucian Health Care System (southern Spain) in 2015. The sampling was carried out in a stratified, consecutive manner on the basis of (a) hospital size by geographical location, (b) type of hospital unit, and (c) patients' sex and age group. Random criteria were used to select patients based on their user identification in the electronic health record system. The variables were grouped into two categories, patient and hospital characteristics. Multilevel linear regression models (MLMs) with random intercepts were used. Two models were fitted: the first was the null model, which contained no explanatory variables except the intercepts (fixed and random), and the second (explanatory) model included selected independent variables. Independent variables were allowed to enter the explanatory model if their univariate association with the nurse staffing level in the MLM was significant at p < .05.

RESULTS

Two hierarchical levels were established to control variance (patients and hospital). The model variables explained 63.4% of the variance at level 1 (patients) and 71.8% at level 2 (hospital). Statistically significant factors were the type of hospital unit (p = .002), shift (p < .001), and season (p < .001). None of the variables associated with patient characteristics obtained statistical significance in the model.

CONCLUSIONS

Nurse staffing levels were associated with hospital characteristics rather than patient characteristics.

CLINICAL RELEVANCE

This study provides evidence about factors that impact on nurse staffing levels in the settings studied. Further studies should determine the influence of patient characteristics in determining optimal nurse staffing levels.

Pro-judge study: Nurses' professional judgement in nurse staffing systems

AIMS

Aim of this study is to better understand the role of nurses' professional judgment in nurse staffing systems.

DESIGN

Qualitative comparative case study design of nurse staffing systems in England and Wales.

METHODS

Data will be collected through a variety of sources: individual interviews, observations of relevant meetings and analysis of key documents. Ethical approval for the study was granted in August 2020 from The Healthcare Research Ethics Committee (SREC reference: REC741). Data generation will be informed by science and technology studies and practice theories.

DISCUSSION

Ensuring adequate numbers of nurses are available to care for patients in response to shifting demand is an international policy priority. Emerging evidence on the use of formal workforce planning methodologies across the developed world highlights both the centrality of nurses' professional judgement in nurse staffing methodologies and the urgent need for theoretically informed research to better understand and conceptualise its contribution to decision-making. This study is designed to address this gap in understanding. It takes advantage of nurses' experiences of managing the service and staffing impacts of the Covid-19 pandemic and differences in strategic approaches to nurse staffing systems between England and Wales.

IMPACT

The research will: make visible the knowledge and skills that underpin professional judgement in nurse staffing decisions and provide a conceptual language with which to articulate this; lay the foundations for evidence-based programmes of nurse education and continuing professional development; furnish the evidence to inform the development of nurse-led decision support tools to augment professional judgement; and generate wider insights into the effectiveness of nurse staffing systems in practice.

Ward staffing guided by a patient classification system: A multi-criteria analysis of "fit" in three acute hospitals

AIMS

To assess how well the Safer Nursing Care Tool (SNCT) predicts staffing requirements on hospital wards, and to use professional judgement to generate hypotheses about factors associated with a "poor fit".

BACKGROUND

The SNCT is widely used in the UK, but there is scant evidence about factors that influence the quality of staffing decisions based upon such patient classification systems.

METHODS

Secondary analysis of data from 69 wards in three acute hospitals to assess the precision of the estimated staffing requirement, variation of estimates, correspondence with professional judgement and achieved staffing levels. Nursing workforce leads suggested factors associated with poor fit, based on the wards that rated worst.

RESULTS

39% of wards were frequently understaffed, while frequent overstaffing was less common (12%). 24% of wards needed a sample of over 182 days to estimate the establishment precisely. Potential reasons identified for poor fit included high turnover, older patients, high levels of 1-to-1 specialing, cancer care, small ward size and high within-day variation in demand.

CONCLUSIONS

Using a staffing tool without applying professional judgement or triangulating against other methods can lead to inaccurate estimates of staffing requirements and unsafe staffing levels.

IMPLICATIONS FOR NURSING MANAGEMENT

Despite the availability of software to calculate staffing requirements, application of professional judgement remains essential.

The association between ward staffing levels, mortality and hospital readmission in older hospitalised adults, according to presence of cognitive impairment: a retrospective cohort study

BACKGROUND

Lower nurse staffing levels are associated with increased hospital mortality. Older patients with cognitive impairments (CI) have higher mortality rates than similar patients without CI and may be additionally vulnerable to low staffing.

OBJECTIVES

To explore associations between registered nurse (RN) and nursing assistant (NA) staffing levels, mortality and readmission in older patients admitted to general medical/surgical wards.

RESEARCH DESIGN

Retrospective cohort.

PARTICIPANTS

All unscheduled admissions to an English hospital of people aged ≥75 with cognitive screening over 14 months.

MEASURES

The exposure was defined as deviation in staffing hours from the ward daily mean, averaged across the patient stay. Outcomes were mortality in hospital/within 30 days of discharge and 30-day re-admission. Analyses were stratified by CI.

RESULTS

12,544 admissions were included. Patients with CI (33.2%) were exposed to similar levels of staffing as those without. An additional 0.5 RN hours per day was associated with 10% reduction in the odds of death overall (odds ratio 0.90 [95% CI 0.84-0.97]): 15% in patients with CI (OR 0.85 [0.74-0.98]) and 7% in patients without (OR 0.93 [0.85-1.02]). An additional 0.5 NA hours per day was associated with a 15% increase in mortality in patients with no impairment. Readmissions decreased by 6% for an additional 0.5 RN hours in patients with CI.

CONCLUSIONS

Although exposure to low staffing was similar, the impact on mortality and readmission for patients with CI was greater. Increased mortality with higher NA staffing in patients without CI needs exploration.

Beyond ratios - flexible and resilient nurse staffing options to deliver cost-effective hospital care and address staff shortages: A simulation and economic modelling study

BACKGROUND

In the face of pressure to contain costs and make best use of scarce nurses, flexible staff deployment (floating staff between units and temporary hires) guided by a patient classification system may appear an efficient approach to meeting variable demand for care in hospitals.

OBJECTIVES

We modelled the cost-effectiveness of different approaches to planning baseline numbers of nurses to roster on general medical/surgical units while using flexible staff to respond to fluctuating demand.

DESIGN AND SETTING

We developed an agent-based simulation, where hospital inpatient units move between being understaffed, adequately staffed or overstaffed as staff supply and demand (as measured by the Safer Nursing Care Tool patient classification system) varies. Staffing shortfalls are addressed by floating staff from overstaffed units or hiring temporary staff. We compared a standard staffing plan (baseline rosters set to match average demand) with a higher baseline 'resilient' plan set to match higher than average demand, and a low baseline 'flexible' plan. We varied assumptions about temporary staff availability and estimated the effect of unresolved low staffing on length of stay and death, calculating cost per life saved.

RESULTS

Staffing plans with higher baseline rosters led to higher costs but improved outcomes. Cost savings from lower baseline staff mainly arose because shifts were left understaffed and much of the staff cost saving was offset by costs from longer patient stays. With limited temporary staff available, changing from low baseline flexible plan to the standard plan cost £13,117 per life saved and changing from the standard plan to the higher baseline 'resilient' plan cost £8,653 per life saved. Although adverse outcomes from low baseline staffing reduced when more temporary staff were available, higher baselines were even more cost-effective because the saving on staff costs also reduced. With unlimited temporary staff, changing from low baseline plan to the standard cost £4,520 per life saved and changing from the standard plan to the higher baseline cost £3,693 per life saved.

CONCLUSION

Shift-by-shift measurement of patient demand can guide flexible staff deployment, but the baseline number of staff rostered must be sufficient. Higher baseline rosters are more resilient in the face of variation and appear cost-effective. Staffing plans that minimise the number of nurses rostered in advance are likely to harm patients because temporary staff may not be available at short notice. Such plans, which rely heavily on flexible deployments, do not represent an efficient or effective use of nurses.

STUDY REGISTRATION

ISRCTN 12307968 Tweetable abstract: Economic simulation model of hospital units shows low baseline staff levels with high use of flexible staff are not cost-effective and don't solve nursing shortages.

The association between 12-hour shifts and nurses-in-charge's perceptions of missed care and staffing adequacy: a retrospective cross-sectional observational study

Background

Due to worldwide nursing shortages and difficulty retaining staff, long shifts for nursing staff (both registered nurses and nursing assistants) working in hospitals have been adopted widely. Because long shifts reduce the daily number of shifts from three to two, many assume that long shifts improve productivity by removing one handover and staff overlap. However, it is unclear whether staffing levels are more likely to be perceived as adequate when more long shifts are used.

Objectives

To investigate the association between the proportion of long (≥12‐hour) shifts worked on a ward and nurses-in-charge's perceptions that the staffing level was sufficient to meet patient need.

Methods

A retrospective cross-sectional study using routinely collected data (patient administrative data and rosters) linked to nurses-in-charge's reports from 81 wards within four English hospitals across 1 year (2017). Hierarchical logistic regression models were used to determine associations between the proportion of long shifts and nurses-in-charge's reports of having enough staff for quality or leaving necessary nursing care undone, after controlling for the staffing level relative to demand (shortfall). We tested for interactions between staffing shortfall and the proportion of long shifts.

Results

The sample comprised 19648 ward days. On average across wards, 72% of shifts were long. With mixed short and long shifts, the odds of nurses-in-charge reporting that there were enough staff for quality were 14-17% lower than when all shifts were long. For example, the odds of reporting enough staff for quality with between 60-80% long shifts was 15% lower (95% confidence interval 2% to 27%) than with all long shifts. Associations with nursing care left undone were consistent with this pattern. Although including interactions between staffing shortfalls and the proportion of long shifts did not improve model fit, the effect of long shifts did appear to differ according to shortfall, with lower proportions of long shifts associated with benefits when staffing levels were high relative to current norms.

Conclusions

Rather than a clear distinction between wards using short and long shifts, we found that a mixed pattern operated on most days and wards, with no wards using all short shifts. We found that when wards use exclusively long shifts rather than a mixture, nurses-in-charge are more likely to judge that they have enough staff. However, the adverse effects of mixed shifts on perceptions of staffing adequacy may be reduced or eliminated by higher staffing levels.

ISRCTN 12307968.

Tweetable abstract

12-hour shifts in nursing: a mix of short and long shifts may be worse than all long shifts.

The association between 12-hour shifts and nurses-in-charge's perceptions of missed care and staffing adequacy: a retrospective cross-sectional observational study

BACKGROUND

Due to worldwide nursing shortages and difficulty retaining staff, long shifts for nursing staff (both registered nurses and nursing assistants) working in hospitals have been adopted widely. Because long shifts reduce the daily number of shifts from three to two, many assume that long shifts improve productivity by removing one handover and staff overlap. However, it is unclear whether staffing levels are more likely to be perceived as adequate when more long shifts are used.

OBJECTIVES

To investigate the association between the proportion of long (≥12-hour) shifts worked on a ward and nurses-in-charge's perceptions that the staffing level was sufficient to meet patient need.

METHODS

A retrospective cross-sectional study using routinely collected data (patient administrative data and rosters) linked to nurses-in-charge's reports from 81 wards within four English hospitals across 1 year (2017). Hierarchical logistic regression models were used to determine associations between the proportion of long shifts and nurses-in-charge's reports of having enough staff for quality or leaving necessary nursing care undone, after controlling for the staffing level relative to demand (shortfall). We tested for interactions between staffing shortfall and the proportion of long shifts.

RESULTS

The sample comprised 19648 ward days. On average across wards, 72% of shifts were long. With mixed short and long shifts, the odds of nurses-in-charge reporting that there were enough staff for quality were 14-17% lower than when all shifts were long. For example, the odds of reporting enough staff for quality with between 60-80% long shifts was 15% lower (95% confidence interval 2% to 27%) than with all long shifts. Associations with nursing care left undone were consistent with this pattern. Although including interactions between staffing shortfalls and the proportion of long shifts did not improve model fit, the effect of long shifts did appear to differ according to shortfall, with lower proportions of long shifts associated with benefits when staffing levels were high relative to current norms.

CONCLUSIONS

Rather than a clear distinction between wards using short and long shifts, we found that a mixed pattern operated on most days and wards, with no wards using all short shifts. We found that when wards use exclusively long shifts rather than a mixture, nurses-in-charge are more likely to judge that they have enough staff. However, the adverse effects of mixed shifts on perceptions of staffing adequacy may be reduced or eliminated by higher staffing levels. ISRCTN 12307968. Tweetable abstract 12-hour shifts in nursing: a mix of short and long shifts may be worse than all long shifts.

The association between 12-hour shifts and nurses-in-charge's perceptions of missed care and staffing adequacy: a retrospective cross-sectional observational study

BACKGROUND

Due to worldwide nursing shortages and difficulty retaining staff, long shifts for nursing staff (both registered nurses and nursing assistants) working in hospitals have been adopted widely. Because long shifts reduce the daily number of shifts from three to two, many assume that long shifts improve productivity by removing one handover and staff overlap. However, it is unclear whether staffing levels are more likely to be perceived as adequate when more long shifts are used.

OBJECTIVES

To investigate the association between the proportion of long (≥12-hour) shifts worked on a ward and nurses-in-charge's perceptions that the staffing level was sufficient to meet patient need.

METHODS

A retrospective cross-sectional study using routinely collected data (patient administrative data and rosters) linked to nurses-in-charge's reports from 81 wards within four English hospitals across 1 year (2017). Hierarchical logistic regression models were used to determine associations between the proportion of long shifts and nurses-in-charge's reports of having enough staff for quality or leaving necessary nursing care undone, after controlling for the staffing level relative to demand (shortfall). We tested for interactions between staffing shortfall and the proportion of long shifts.

RESULTS

The sample comprised 19648 ward days. On average across wards, 72% of shifts were long. With mixed short and long shifts, the odds of nurses-in-charge reporting that there were enough staff for quality were 14-17% lower than when all shifts were long. For example, the odds of reporting enough staff for quality with between 60-80% long shifts was 15% lower (95% confidence interval 2% to 27%) than with all long shifts. Associations with nursing care left undone were consistent with this pattern. Although including interactions between staffing shortfalls and the proportion of long shifts did not improve model fit, the effect of long shifts did appear to differ according to shortfall, with lower proportions of long shifts associated with benefits when staffing levels were high relative to current norms.

CONCLUSIONS

Rather than a clear distinction between wards using short and long shifts, we found that a mixed pattern operated on most days and wards, with no wards using all short shifts. We found that when wards use exclusively long shifts rather than a mixture, nurses-in-charge are more likely to judge that they have enough staff. However, the adverse effects of mixed shifts on perceptions of staffing adequacy may be reduced or eliminated by higher staffing levels. ISRCTN 12307968. Tweetable abstract 12-hour shifts in nursing: a mix of short and long shifts may be worse than all long shifts.

Performance of the Safer Nursing Care Tool to measure nurse staffing requirements in acute hospitals: a multicentre observational study

OBJECTIVES

The best way to determine nurse staffing requirements on hospital wards is unclear. This study explores the precision of estimates of nurse staffing requirements made using the Safer Nursing Care Tool (SNCT) patient classification system for different sample sizes and investigates whether recommended staff levels correspond with professional judgements of adequate staffing.

DESIGN

Observational study linking datasets of staffing requirements (estimated using a tool) to professional judgements of adequate staffing. Multilevel logistic regression modelling.

SETTING

81 medical/surgical units in four acute care hospitals.

PARTICIPANTS

22 364 unit days where staffing levels and SNCT ratings were linked to nurse reports of "enough staff for quality".

PRIMARY OUTCOME MEASURES

SNCT-estimated staffing requirements and nurses' assessments of staffing adequacy.

RESULTS

The recommended minimum sample of 20 days allowed the required number to employ (the establishment) to be estimated with a mean precision (defined as half the width of the CI as a percentage of the mean) of 4.1%. For most units, much larger samples were required to estimate establishments within ±1 whole time equivalent staff member. When staffing was lower than that required according to the SNCT, for each hour per patient day of registered nurse staffing below the required staffing level, the odds of nurses reporting that there were enough staff to provide quality care were reduced by 11%. Correspondingly, the odds of nurses reporting that necessary nursing care was left undone were increased by 14%. No threshold indicating an optimal staffing level was observed. Surgical specialty, patient turnover and more single rooms were associated with lower odds of staffing adequacy.

CONCLUSIONS

The SNCT can provide reliable estimates of the number of nurses to employ on a unit, but larger samples than the recommended minimum are usually required. The SNCT provides a measure of nursing workload that correlates with professional judgements, but the recommended staffing levels may not be optimal. Some important sources of systematic variations in staffing requirements for some units are not accounted for. SNCT measurements are a potentially useful adjunct to professional judgement but cannot replace it.

TRIAL REGISTRATION NUMBER

ISRCTN12307968.