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

2020 ◽  
Vol 8 (16) ◽  
pp. 1-162 ◽  
Author(s):  
Peter Griffiths ◽  
Christina Saville ◽  
Jane E Ball ◽  
Rosemary Chable ◽  
Andrew Dimech ◽  
...  
Keyword(s):  
Nursing Care ◽  
Response Rate ◽  
Nurse Staffing ◽  
Cost Savings ◽  
Cost Effective ◽  
Staffing Levels ◽  
The Mean ◽  
Staffing Requirements ◽  
Hospital Wards ◽  
Professional Judgement

Background The Safer Nursing Care Tool is a system designed to guide decisions about nurse staffing requirements on hospital wards, in particular the number of nurses to employ (establishment). The Safer Nursing Care Tool is widely used in English hospitals but there is a lack of evidence about how effective and cost-effective nurse staffing tools are at providing the staffing levels needed for safe and quality patient care. Objectives To determine whether or not the Safer Nursing Care Tool corresponds to professional judgement, to assess a range of options for using the Safer Nursing Care Tool and to model the costs and consequences of various ward staffing policies based on Safer Nursing Care Tool acuity/dependency measure. Design This was an observational study on medical/surgical wards in four NHS hospital trusts using regression, computer simulations and economic modelling. We compared the effects and costs of a ‘high’ establishment (set to meet demand on 90% of days), the ‘standard’ (mean-based) establishment and a ‘flexible (low)’ establishment (80% of the mean) providing a core staff group that would be sufficient on days of low demand, with flexible staff re-deployed/hired to meet fluctuations in demand. Setting Medical/surgical wards in four NHS hospital trusts. Main outcome measures The main outcome measures were professional judgement of staffing adequacy and reports of omissions in care, shifts staffed more than 15% below the measured requirement, cost per patient-day and cost per life saved. Data sources The data sources were hospital administrative systems, staff reports and national reference costs. Results In total, 81 wards participated (85% response rate), with data linking Safer Nursing Care Tool ratings and staffing levels for 26,362 wards × days (96% response rate). According to Safer Nursing Care Tool measures, 26% of all ward-days were understaffed by ≥ 15%. Nurses reported that they had enough staff to provide quality care on 78% of shifts. When using the Safer Nursing Care Tool to set establishments, on average 60 days of observation would be needed for a 95% confidence interval spanning 1 whole-time equivalent either side of the mean. Staffing levels below the daily requirement estimated using the Safer Nursing Care Tool were associated with lower odds of nurses reporting ‘enough staff for quality’ and more reports of missed nursing care. However, the relationship was effectively linear, with staffing above the recommended level associated with further improvements. In simulation experiments, ‘flexible (low)’ establishments led to high rates of understaffing and adverse outcomes, even when temporary staff were readily available. Cost savings were small when high temporary staff availability was assumed. ‘High’ establishments were associated with substantial reductions in understaffing and improved outcomes but higher costs, although, under most assumptions, the cost per life saved was considerably less than £30,000. Limitations This was an observational study. Outcomes of staffing establishments are simulated. Conclusions Understanding the effect on wards of variability of workload is important when planning staffing levels. The Safer Nursing Care Tool correlates with professional judgement but does not identify optimal staffing levels. Employing more permanent staff than recommended by the Safer Nursing Care Tool guidelines, meeting demand most days, could be cost-effective. Apparent cost savings from ‘flexible (low)’ establishments are achieved largely by below-adequate staffing. Cost savings are eroded under the conditions of high temporary staff availability that are required to make such policies function. Future work Research is needed to identify cut-off points for required staffing. Prospective studies measuring patient outcomes and comparing the results of different systems are feasible. Trial registration Current Controlled Trials ISRCTN12307968. Funding This project was funded by the National Institute for Health Research (NIHR) Health Services and Delivery Research programme and will be published in full in Health Services and Delivery Research; Vol. 8, No. 16. See the NIHR Journals Library website for further project information.

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

2020 ◽  
Author(s):  
Peter Griffiths ◽  
Christina Saville ◽  
Jane E Ball ◽  
Jeremy Jones ◽  
Thomas Monks
Keyword(s):  
Cost Effectiveness ◽  
Significant Proportion ◽  
Nurse Staffing ◽  
Cost Savings ◽  
Cost Effective ◽  
Adverse Outcomes ◽  
List Type ◽  
Economic Modelling ◽  
The Face ◽  
Hospital Wards

AbstractBackgroundIn 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.ObjectivesWe 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 SettingWe developed an agent-based simulation model, where units move between being understaffed, adequately staffed or overstaffed as staff supply and demand, measured by the Safer Nursing Care Tool, varies. Staffing shortfalls are addressed firstly by floating staff from overstaffed units, secondly by hiring temporary staff. We compared a standard staffing plan (baseline rosters set to match average demand) with a ‘resilient’ plan set to match higher demand, and a ‘flexible’ plan, set at a lower level. We varied assumptions about temporary staff availability. We estimated the effect of unresolved low staffing on length of stay and death, calculating cost per life saved.ResultsStaffing plans with higher baseline rosters led to higher costs but improved outcomes. Cost savings from low baseline staff largely arose because shifts were left under staffed. Cost effectiveness for higher baseline staff was improved with high temporary staff availability. With limited temporary staff available, the resilient staffing plan (higher baseline staff) cost £9,506 per life saved compared to the standard plan. The standard plan cost £13,967 per life saved compared to the flexible (low baseline) plan. With unlimited temporary staff, the resilient staffing plan cost £5,524 per life saved compared to the standard plan and the standard plan cost £946 per life saved compared with the flexible plan. Cost-effectiveness of higher baseline staffing was more favourable when negative effects of high temporary staffing were modelled.ConclusionFlexible staffing can be guided by shift-by-shift measurement of patient demand, but proper attention must be given to ensure that the baseline number of staff rostered is sufficient.In the face of staff shortages, low baseline staff rosters with high use of flexible staff on hospital wards is not an efficient or effective use of nurses whereas high baseline rosters may be cost-effective. Flexible staffing plans that minimise the number of nurses routinely rostered are likely to harm patients because temporary staff may not be available at short notice.Study registration: ISRCTN 12307968Tweetable abstractEconomic model of hospital wards shows low baseline staff levels with high use of flexible staff are not cost-effective and don’t solve nursing shortages].What is already known?Because nursing is the largest staff group, accounting for a significant proportion of hospital’s variable costs, ward nurse staffing is frequently the target of cost containment measuresStaffing decisions need to address both the baseline staff establishment to roster, and how best to respond to fluctuating demand as patient census and care needs varyFlexible deployment of staff, including floating staff and using temporary hires, has the potential to minimise expenditure while meeting varying patient need, but high use of temporary staff may be associated with adverse outcomes.What this paper addsOur simulation shows that low baseline staff rosters that rely heavily on flexible staff increase the risk of patient death and provide cost savings largely because wards are often left short staffed under real world availability of temporary staff.A staffing plan set to meet average demand appears to be cost effective compared to a plan with a lower baseline but is still associated with frequent short staffing despite the use of flexible deployments.A staffing plan with a higher baseline, set to meet demand 90% of the time, is more resilient in the face of variation and may be highly cost effective

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

BMJ Open ◽  
2020 ◽  
Vol 10 (5) ◽  
pp. e035828
Author(s):  
Peter Griffiths ◽  
Christina Saville ◽  
Jane Ball ◽  
David Culliford ◽  
Natalie Pattison ◽  
...  
Keyword(s):  
Observational Study ◽  
Nursing Care ◽  
Nurse Staffing ◽  
Nursing Workload ◽  
Staffing Level ◽  
Surgical Specialty ◽  
Staffing Levels ◽  
Staffing Requirements ◽  
Staffing Adequacy ◽  
Adequate Staffing

ObjectivesThe 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.DesignObservational study linking datasets of staffing requirements (estimated using a tool) to professional judgements of adequate staffing. Multilevel logistic regression modelling.Setting81 medical/surgical units in four acute care hospitals.Participants22 364 unit days where staffing levels and SNCT ratings were linked to nurse reports of "enough staff for quality".Primary outcome measuresSNCT-estimated staffing requirements and nurses’ assessments of staffing adequacy.ResultsThe 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.ConclusionsThe 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 numberISRCTN12307968.

Nurse Staffing Levels and Patient-Reported Missed Nursing Care

2015 ◽  
Vol 30 (4) ◽  
pp. 306-312 ◽  
Author(s):  
Beverly Waller Dabney ◽  
Beatrice J. Kalisch
Keyword(s):  
Nursing Care ◽  
Nurse Staffing ◽  
Staffing Levels ◽  
Patient Reported ◽  
Missed Nursing Care

scholarly journals The impact of nurse staffing levels and nurse’s education on patient mortality in medical and surgical wards: an observational multicentre study

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Filip Haegdorens ◽  
Peter Van Bogaert ◽  
Koen De Meester ◽  
Koenraad G. Monsieurs
Keyword(s):  
Cardiac Arrest ◽  
Mortality Rate ◽  
Control Period ◽  
Nurse Staffing ◽  
Control Group ◽  
Unplanned Admission ◽  
Unexpected Death ◽  
Staffing Levels ◽  
The Mean ◽  
The Impact

Abstract Background Growing evidence indicates that improved nurse staffing in acute hospitals is associated with lower hospital mortality. Current research is limited to studies using hospital level data or without proper adjustment for confounders which makes the translation to practice difficult. Method In this observational study we analysed retrospectively the control group of a stepped wedge randomised controlled trial concerning 14 medical and 14 surgical wards in seven Belgian hospitals. All patients admitted to these wards during the control period were included in this study. Pregnant patients or children below 17 years of age were excluded. In all patients, we collected age, crude ward mortality, unexpected death, cardiac arrest with Cardiopulmonary Resuscitation (CPR), and unplanned admission to the Intensive Care Unit (ICU). A composite mortality measure was constructed including unexpected death and death up to 72 h after cardiac arrest with CPR or unplanned ICU admission. Every 4 months we obtained, from 30 consecutive patient admissions across all wards, the Charlson comorbidity index. The amount of nursing hours per patient days (NHPPD) were calculated every day for 15 days, once every 4 months. Data were aggregated to the ward level resulting in 68 estimates across wards and time. Linear mixed models were used since they are most appropriate in case of clustered and repeated measures data. Results The unexpected death rate was 1.80 per 1000 patients. Up to 0.76 per 1000 patients died after CPR and 0.62 per 1000 patients died after unplanned admission to the ICU. The mean composite mortality was 3.18 per 1000 patients. The mean NHPPD and proportion of nurse Bachelor hours were respectively 2.48 and 0.59. We found a negative association between the nursing hours per patient day and the composite mortality rate adjusted for possible confounders (B = − 2.771, p = 0.002). The proportion of nurse Bachelor hours was negatively correlated with the composite mortality rate in the same analysis (B = − 8.845, p = 0.023). Using the regression equation, we calculated theoretically optimal NHPPDs. Conclusions This study confirms the association between higher nurse staffing levels and lower patient mortality controlled for relevant confounders.

scholarly journals Home Videos as a Cost-Effective Tool for the Diagnosis of Paroxysmal Events in Infants: Prospective Study (Preprint)

2018 ◽  
Author(s):  
Lu-Lu Huang ◽  
Yang-Yang Wang ◽  
Li-Ying Liu ◽  
Hong-Ping Tang ◽  
Meng-Na Zhang ◽  
...  
Keyword(s):  
Diagnostic Accuracy ◽  
Mobile Phone ◽  
Mobile Phones ◽  
Cost Savings ◽  
Cost Effective ◽  
Educational Background ◽  
Hospital Level ◽  
Home Videos ◽  
Online Consultation ◽  
The Mean

BACKGROUND The diagnosis of paroxysmal events in infants is often challenging. Reasons include the child’s inability to express discomfort and the inability to record video electroencephalography at home. The prevalence of mobile phones, which can record videos, may be beneficial to these patients. In China, this advantage may be even more significant given the vast population and the uneven distribution of medical resources. OBJECTIVE The aim of this study is to investigate the value of mobile phone videos in increasing the diagnostic accuracy and cost savings of paroxysmal events in infants. METHODS Clinical data, including descriptions and home videos of episodes, from 12 patients with paroxysmal events were collected. The investigation was conducted in six centers during pediatric academic conferences. All 452 practitioners present were asked to make their diagnoses by just the descriptions of the events, and then remake their diagnoses after watching the corresponding home videos of the episodes. The doctor’s information, including educational background, profession, working years, and working hospital level, was also recorded. The cost savings from accurate diagnoses were measured on the basis of using online consultation, which can also be done easily by mobile phone. All data were recorded in the form of questionnaires designed for this study. RESULTS We collected 452 questionnaires, 301 of which met the criteria (66.6%) and were analyzed. The mean correct diagnoses with and without videos was 8.4 (SD 1.7) of 12 and 7.5 (SD 1.7) of 12, respectively. For epileptic seizures, mobile phone videos increased the mean accurate diagnoses by 3.9%; for nonepileptic events, it was 11.5% and both were statistically different (P=.006 for epileptic events; P<.001 for nonepileptic events). Pediatric neurologists with longer working years had higher diagnostic accuracy; whereas, their working hospital level and educational background made no difference. For patients with paroxysmal events, at least US $673.90 per capita and US $128 million nationwide could be saved annually, which is 12.02% of the total cost for correct diagnosis. CONCLUSIONS Home videos made on mobile phones are a cost-effective tool for the diagnosis of paroxysmal events in infants. They can facilitate the diagnosis of paroxysmal events in infants and thereby save costs. The best choice for infants with paroxysmal events on their initial visit is to record their events first and then show the video to a neurologist with longer working years through online consultation.

scholarly journals Nurse staffing and patient-perceived quality of nursing care: a cross-sectional analysis of survey and administrative data in German hospitals

BMJ Open ◽  
2021 ◽  
Vol 11 (11) ◽  
pp. e051133
Author(s):  
Vera Winter ◽  
Karina Dietermann ◽  
Udo Schneider ◽  
Jonas Schreyögg
Keyword(s):  
Nursing Care ◽  
Nurse Staffing ◽  
Perceived Quality ◽  
Secondary Outcome ◽  
Skill Mix ◽  
Staffing Levels ◽  
Hospital Units ◽  
The Impact ◽  
Quality Of Nursing

ObjectiveTo examine the impact of nurse staffing on patient-perceived quality of nursing care. We differentiate nurse staffing levels and nursing skill mix as two facets of nurse staffing and use a multidimensional instrument for patient-perceived quality of nursing care. We investigate non-linear and interaction effects.SettingThe study setting was 3458 hospital units in 1017 hospitals in Germany.ParticipantsWe contacted 212 554 patients discharged from non-paediatric, non-intensive and non-psychiatric hospital units who stayed at least two nights in the hospital between January and October 2019. Of those, 30 174 responded, yielding a response rate of 14.2%. Our sample included only those patients. After excluding extreme values for our nurse staffing variables and removing observations with missing values, our final sample comprised 28 136 patients ranging from 18 to 97 years of age (average: 61.12 years) who had been discharged from 3458 distinct hospital units in 1017 hospitals.Primary and secondary outcome measuresPatient-perceived quality of nursing care (general nursing care, guidance provided by nurses, and patient loyalty to the hospital).ResultsFor all three dimensions of patient-perceived quality of nursing care, we found that they significantly decreased as (1) nurse staffing levels decreased (with decreasing marginal effects) and (2) the proportion of assistant nurses in a hospital unit increased. The association between nurse staffing levels and quality of nursing care was more pronounced among patients who were less clinically complex, were admitted to smaller hospitals or were admitted to medical units.ConclusionsOur results indicate that, in addition to nurse staffing levels, nursing skill mix is crucial for providing the best possible quality of nursing care from the patient perspective and both should be considered when designing policies such as minimum staffing regulations to improve the quality of nursing care in hospitals.

Nurse Staffing Levels: Skill Mix and Nursing Care Hours Per Patient Day

2018 ◽  
pp. 465-488
Author(s):  
Alberto Lucchini ◽  
Michele Pirovano ◽  
Christian De Felippis ◽  
Irene Comisso
Keyword(s):  
Nursing Care ◽  
Nurse Staffing ◽  
Skill Mix ◽  
Staffing Levels

scholarly journals The impact of nurse staffing levels and nurse’s education on patient mortality in medical and surgical wards: an observational multicentre study.

2019 ◽  
Author(s):  
Filip Haegdorens ◽  
Peter Van Bogaert ◽  
Koen De Meester ◽  
Koen Monsieurs
Keyword(s):  
Cardiac Arrest ◽  
Mortality Rate ◽  
Control Period ◽  
Nurse Staffing ◽  
Control Group ◽  
Unplanned Admission ◽  
Unexpected Death ◽  
Staffing Levels ◽  
The Mean ◽  
The Impact

Abstract BACKGROUND Growing evidence indicates that improved nurse staffing in acute hospitals is associated with lower hospital mortality. Current research is limited to studies using hospital level data or without proper adjustment for confounders which makes the translation to practice difficult. METHOD In this observational study we analysed retrospectively the control group of a stepped wedge randomised controlled trial concerning 14 medical and 14 surgical wards in seven Belgian hospitals. All patients admitted to these wards during the control period were included in this study. Pregnant patients or children below 17 years of age were excluded. In all patients, we collected age, crude ward mortality, unexpected death, cardiac arrest with Cardiopulmonary Resuscitation (CPR), and unplanned admission to the Intensive Care Unit (ICU). A composite mortality measure was constructed including unexpected death and death up to 72 hours after cardiac arrest with CPR or unplanned ICU admission. Every four months we obtained, from 30 consecutive patient admissions across all wards, the Charlson comorbidity index. The amount of nursing hours per patient days (NHPPD) were calculated every day for 15 days, once every four months. Data were aggregated to the ward level resulting in 68 estimates across wards and time. Linear mixed models were used since they are most appropriate in case of clustered and repeated measures data. RESULTS The unexpected death rate was 1.80 per 1000 patients. Up to 0.76 per 1000 patients died after CPR and 0.62 per 1000 patients died after unplanned admission to the ICU. The mean composite mortality was 3.18 per 1000 patients. The mean NHPPD and proportion of nurse Bachelor hours were respectively 2.48 and 0.59. We found a negative association between the nursing hours per patient day and the composite mortality rate adjusted for possible confounders (B= -2.771, p=0.002). The proportion of nurse Bachelor hours was negatively correlated with the composite mortality rate in the same analysis (B= -8.845, p=0.023). Using the regression equation, we calculated theoretically optimal NHPPDs. CONCLUSIONS This study confirms the association between higher nurse staffing levels and lower patient mortality controlled for relevant confounders.

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