Inpatient midwifery staffing levels and postpartum readmissions: a retrospective multicentre longitudinal study.

BACKGROUND: Preventing readmission to hospital after giving birth is a key priority, as rates have been rising along with associated costs. There are many contributing factors to readmission, and some are thought to be preventable. Nurse and midwife understaffing has been linked to deficits in care quality. This study explores the relationship between staffing levels and readmission rates in maternity settings. METHODS: We conducted a retrospective longitudinal study using routinely collected individual patient data in three maternity services in England from 2015 to 2020. Data on admissions, discharges and case-mix were extracted from hospital administration systems. Staffing and workload were calculated in Hours Per Patient day per shift in the first two 12-hour shifts of the index (birth) admission. Postpartum readmissions and staffing exposures for all birthing admissions were entered into a hierarchical multivariable logistic regression model to estimate the odds of readmission when staffing was below the mean level for the maternity service. RESULTS: 64 250 maternal admissions resulted in birth and 2903 mothers were readmitted within 30 days of discharge (4.5%). Absolute levels of staffing ranged between 2.3 and 4.1 individuals per midwife in the three services. Below average midwifery staffing was associated with higher rates of postpartum readmissions within 7 days of discharge (adjusted OR (aOR) 1.108, 95% CI 1.003 to 1.223). The effect was smaller and not statistically significant for readmissions within 30 days of discharge (aOR 1.080, 95% CI 0.994 to 1.174). Below average maternity assistant staffing was associated with lower rates of postpartum readmissions (7 days, aOR 0.957, 95% CI 0.867 to 1.057; 30 days aOR 0.965, 95% CI 0.887 to 1.049, both not statistically significant). CONCLUSION: We found evidence that lower than expected midwifery staffing levels is associated with more postpartum readmissions. The nature of the relationship requires further investigation including examining potential mediating factors and reasons for readmission in maternity populations.

Safer and more efficient vital signs monitoring protocols to identify the deteriorating patients in the general hospital ward: an observational study.

Background: The frequency at which patients should have their vital signs (e.g. blood pressure, pulse, oxygen saturation) measured on hospital wards is currently unknown. Current National Health Service monitoring protocols are based on expert opinion but supported by little empirical evidence. The challenge is finding the balance between insufficient monitoring (risking missing early signs of deterioration and delays in treatment) and over-observation of stable patients (wasting resources needed in other aspects of care). Objective: Provide an evidence-based approach to creating monitoring protocols based on a patient's risk of deterioration and link these to nursing workload and economic impact. Design: Our study consisted of two parts: (1) an observational study of nursing staff to ascertain the time to perform vital sign observations; and (2) a retrospective study of historic data on patient admissions exploring the relationships between National Early Warning Score and risk of outcome over time. These were underpinned by opinions and experiences from stakeholders. Setting and participants: Observational study: observed nursing staff on 16 randomly selected adult general wards at four acute National Health Service hospitals. Retrospective study: extracted, linked and analysed routinely collected data from two large National Health Service acute trusts; data from over 400,000 patient admissions and 9,000,000 vital sign observations. Results: Observational study found a variety of practices, with two hospitals having registered nurses take the majority of vital sign observations and two favouring healthcare assistants or student nurses. However, whoever took the observations spent roughly the same length of time. The average was 5:01 minutes per observation over a 'round', including time to locate and prepare the equipment and travel to the patient area. Retrospective study created survival models predicting the risk of outcomes over time since the patient was last observed. For low-risk patients, there was little difference in risk between 4 hours and 24 hours post observation. Conclusions: We explored several different scenarios with our stakeholders (clinicians and patients), based on how 'risk' could be managed in different ways. Vital sign observations are often done more frequently than necessary from a bald assessment of the patient's risk, and we show that a maximum threshold of risk could theoretically be achieved with less resource. Existing resources could therefore be redeployed within a changed protocol to achieve better outcomes for some patients without compromising the safety of the rest. Our work supports the approach of the current monitoring protocol, whereby patients' National Early Warning Score 2 guides observation frequency. Existing practice is to observe higher-risk patients more frequently and our findings have shown that this is objectively justified. It is worth noting that important nurse-patient interactions take place during vital sign monitoring and should not be eliminated under new monitoring processes. Our study contributes to the existing evidence on how vital sign observations should be scheduled. However, ultimately, it is for the relevant professionals to decide how our work should be used. Study registration: This study is registered as ISRCTN10863045. Funding: This award was funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme (NIHR award ref: 17/05/03) and is published in full in Health and Social Care Delivery Research; Vol. 12, No. 6. See the NIHR Funding and Awards website for further award information.

Patient recovery in hospital is tracked by measuring heart rate, blood pressure and other 'vital signs' and converting them into a score. These are 'observed' regularly by nursing staff so that deterioration can be spotted early. However, taking observations can disturb patients, and taking them too often causes extra work for staff. More frequent monitoring is recommended for higher scores, but evidence is lacking. To work out how often patients should be monitored, we needed to know how likely it is for patients to become more unwell between observations. We analysed over 400,000 patient records from two hospitals to understand how scores change with time. We looked at three of the most serious risks for patients in hospital. These risks are dying, needing intensive care or having a cardiac arrest. We also looked at the risk that a patient's condition would deteriorate significantly before their measurements were taken again. We identified early signs of deterioration and how changes in vital signs affected the risk of a patient's condition becoming worse. From this we calculated a maximum risk of deterioration. We then calculated different monitoring schedules that keep individual patients below this risk level. Some of those would consume less staff time than current National Health Service guidelines suggest. We also watched staff record patients' vital signs. We learnt it takes about 5 minutes to take these measurements from each patient. This information helped us calculate how costs would change if patients' vital signs were taken more or less often. We found that patients with a low overall score could have their vital signs monitored less often without being in danger of serious harm. This frees up nursing time so that patients with a higher score can be monitored more often. Importantly, this can be achieved without employing more staff.

The important factors nurses consider when choosing shift patterns: A cross-sectional study.

AIM: To gain a deeper understanding of what is important to nurses when thinking about shift patterns and the organisation of working time. DESIGN: A cross-sectional survey of nursing staff working across the UK and Ireland collected quantitative and qualitative responses. METHODS: We recruited from two National Health Service Trusts and through an open call via trade union membership, online/print nursing profession magazines and social media. Worked versus preferred shift length/pattern, satisfaction and choice over shift patterns and nurses' views on aspects related to work and life (when working short, long, rotating shifts) were analysed with comparisons of proportions of agreement and crosstabulation. Qualitative responses on important factors related to shift preferences were analysed with inductive thematic analysis. RESULTS: Eight hundred and seventy-three survey responses were collected. When nurses worked long shifts and rotating shifts, lower proportions reported being satisfied with their shifts and working their preferred shift length and pattern. Limited advantages were realised when comparing different shift types; however, respondents more frequently associated 'low travel costs' and 'better ability to do paid overtime' with long shifts and 'healthy diet/exercise' with short shifts; aspects related to rotating shifts often had the lowest proportions of agreement. In the qualitative analysis, three themes were developed: 'When I want to work', 'Impacts to my life outside work' and 'Improving my work environment'. Reasons for nurses' shift preferences were frequently related to nurses' priorities outside of work, highlighting the importance of organising schedules that support a good work-life balance. RELEVANCE TO CLINICAL PRACTICE: General scheduling practices like adhering to existing shift work guidelines, using consistent and predictable shift patterns and facilitating flexibility over working time were identified by nurses as enablers for their preferences and priorities. These practices warrant meaningful consideration when establishing safe and efficient nurse rosters. PATIENT OR PUBLIC CONTRIBUTION: This survey was developed and tested with a diverse group of stakeholders, including nursing staff, patients, union leads and ward managers. REPORTING METHOD: The Strengthening the Reporting of Observational Studies (STROBE) checklist for cross-sectional studies was used to guide reporting.

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.

Staffing levels and hospital mortality in England: a national panel study using routinely collected data.

OBJECTIVES: Examine the association between multiple clinical staff levels and case-mix adjusted patient mortality in English hospitals. Most studies investigating the association between hospital staffing levels and mortality have focused on single professional groups, in particular nursing. However, single staff group studies might overestimate effects or neglect important contributions to patient safety from other staff groups. DESIGN: Retrospective observational study of routinely available data. SETTING AND PARTICIPANTS: 138 National Health Service hospital trusts that provided general acute adult services in England between 2015 and 2019. OUTCOME MEASURE: Standardised mortality rates were derived from the Summary Hospital level Mortality Indicator data set, with observed deaths as outcome in our models and expected deaths as offset. Staffing levels were calculated as the ratio of occupied beds per staff group. We developed negative binomial random-effects models with trust as random effects. RESULTS: Hospitals with lower levels of medical and allied healthcare professional (AHP) staff (e.g, occupational therapy, physiotherapy, radiography, speech and language therapy) had significantly higher mortality rates (rate ratio: 1.04, 95% CI 1.02 to 1.06, and 1.04, 95% CI 1.02 to 1.06, respectively), while those with lower support staff had lower mortality rates (0.85, 95% CI 0.79 to 0.91 for nurse support, and 1.00, 95% CI 0.99 to 1.00 for AHP support). Estimates of the association between staffing levels and mortality were stronger between-hospitals than within-hospitals, which were not statistically significant in a within-between random effects model. CONCLUSIONS: In additional to medicine and nursing, AHP staffing levels may influence hospital mortality rates. Considering multiple staff groups simultaneously when examining the association between hospital mortality and clinical staffing levels is crucial. TRIAL REGISTRATION NUMBER: NCT04374812.

The association between multi-disciplinary staffing levels and mortality in acute hospitals: a systematic review.

OBJECTIVES: Health systems worldwide are faced with the challenge of adequately staffing their hospital services. Much of the current research and subsequent policy has been focusing on nurse staffing and minimum ratios to ensure quality and safety of patient care. Nonetheless, nurses are not the only profession who interact with patients, and, therefore, not the only professional group who has the potential to influence the outcomes of patients while in hospital. We aimed to synthesise the evidence on the relationship between multi-disciplinary staffing levels in hospital including nursing, medical and allied health professionals and the risk of death. METHODS: Systematic review. We searched Embase, Medline, CINAHL, and the Cochrane Library for quantitative or mixed methods studies with a quantitative component exploring the association between multi-disciplinary hospital staffing levels and mortality. RESULTS: We included 12 studies. Hospitals with more physicians and registered nurses had lower mortality rates. Higher levels of nursing assistants were associated with higher patient mortality. Only two studies included other health professionals, providing scant evidence about their effect. CONCLUSIONS: Pathways for allied health professionals such as physiotherapists, occupational therapists, dietitians, pharmacists, to impact safety and other patient outcomes are plausible and should be explored in future studies.

Nurse staffing levels and patient outcomes: A systematic review of longitudinal studies.

BACKGROUND: The contribution of registered nurses towards safe patient care has been demonstrated in many studies. However, most of the evidence linking staffing levels to outcomes is cross-sectional with intrinsic limitations including an inability to establish that presumed cause (staffing) precedes the effect. No reviews have summarised longitudinal studies considering nurse staffing and patient outcomes. OBJECTIVES: To identify and assess the evidence for an association between nurse staffing levels, including the composition of the nursing team, and patient outcomes in acute care settings from longitudinal studies. METHODS: We undertook a systematic review of studies where the association between nurse staffing with patient outcomes was assessed in a longitudinal design. Studies with repeated cross-sectional analyses were excluded unless a difference-in-difference design was used. We searched Medline, CINAHL, Embase and the Cochrane Library up to February 2022. We used the ROBINS-I tool to assess risk of bias. We synthesised results in a tabular form and a narrative grouped by outcome. RESULTS: 27 papers were included. Studies were conducted in a variety of settings and populations, including adult general medical/surgical wards and adult and neonatal intensive care units. Staffing measures were operationalised in a variety of different ways, making direct comparisons between studies difficult and pooled estimates impossible. Most studies were either at serious (n = 12) or critical (n = 5) risk of bias, with only 3 studies at low risk of bias. Studies with the most risk of bias were judged as likely to underestimate the effect of higher registered nurse staffing. Findings are consistent with an overall picture of a beneficial effect from higher registered nurse staffing on preventing patient death. The evidence is less clear for other patient outcomes with a higher risk of bias, but in general the proposition that higher registered nurse staffing is likely to lead to better patient outcomes is supported. Evidence about the contribution of other nursing staff groups is unclear. CONCLUSION: The causal relationship between low registered nurse staffing and mortality is plausible and these estimates of relationships from longitudinal studies provide further support. To address residual uncertainties, future studies should be conducted in more than one hospital and using standardised measures when reporting staffing levels. TWEETABLE ABSTRACT: Having more registered nurses on hospital wards is causally linked to reduced mortality - new review shows there is little room for doubt @ora_dall @workforcesoton @turnel.

Correction: Nurses' experiences and preferences around shift patterns: A scoping review.

[This corrects the article DOI: 10.1371/journal.pone.0256300.].

Because they're worth it? A discussion paper on the value of 12-h shifts for hospital nursing.

The organisation of the 24-h day for hospital nurses in two 12-h shifts has been introduced with value propositions of reduced staffing costs, better quality of care, more efficient work organisation, and increased nurse recruitment and retention. While existing reviews consider the impact of 12-h shifts on nurses' wellbeing and performance, this discussion paper aims to specifically shed light on whether the current evidence supports the value propositions around 12-h shifts. We found little evidence of the value propositions being realised. Staffing costs are not reduced with 12-h shifts, and outcomes related to productivity and efficiency, including sickness absence and missed nursing care are negatively affected. Nurses working 12-h shifts do not perform more safely than their counterparts working shorter shifts, with evidence pointing to a likely negative effect on safe care due to increased fatigue and sleepiness. In addition, nurses working 12-h shifts may have access to fewer educational opportunities than nurses working shorter shifts. Despite some nurses preferring 12-h shifts, the literature does not indicate that this shift pattern leads to increased recruitment, with studies reporting that nurses working long shifts are more likely to express intention to leave their job. In conclusion, there is little if any support for the value propositions that were advanced when 12-h shifts were introduced. While 12-h shifts might be here to stay, it is important that the limitations, including reduced productivity and efficiency, are recognised and accepted by those in charge of implementing schedules for hospital nurses.

The organisation of nurse staffing in intensive care units: A qualitative study.

AIMS: To examine the organisation of the nursing workforce in intensive care units and identify factors that influence how the workforce operates. BACKGROUND: Pre-pandemic UK survey data show that up to 60% of intensive care units did not meet locally agreed staffing numbers and 40% of ICUs were closing beds at least once a week because of workforce shortages, specifically nursing. Nurse staffing in intensive care is based on the assumption that sicker patients need more nursing resource than those recovering from critical illness. These standards are based on historical working, and expert professional consensus, deemed the weakest form of evidence. METHODS: Focus groups with intensive care health care professionals (n = 52 participants) and individual interviews with critical care network leads and policy leads (n = 14 participants) in England between December 2019 and July 2020. Data were analysed using framework analysis. FINDINGS: Three themes were identified: the constraining or enabling nature of intensive care and hospital structures; whole team processes to mitigate nurse staffing shortfalls; and the impact of nurse staffing on patient, staff and intensive care flow outcomes. Staff made decisions about staffing throughout a shift and were influenced by a combination of factors illuminated in the three themes. CONCLUSIONS: Whilst nurse:patient ratios were clearly used to set the nursing establishment, it was clear that rostering and allocation/re-allocation during a shift took into account many other factors, such as patient and family nursing needs, staff well-being, intensive care layout and the experience, and availability, of other members of the multi-professional team. This has important implications for future planning for intensive care nurse staffing and highlights important factors to be accounted for in future research studies. IMPLICATIONS FOR NURSING MANAGEMENT: In order to safeguard patient and staff safety, factors such as the ICU layout need to be considered in staffing decisions and the local business case for nurse staffing needs to reflect these factors. Patient safety in intensive care may not be best served by a blanket 'ratio' approach to nurse staffing, intended to apply uniformly across health services.

Student nurses' views on shift patterns: What do they prefer and why? Results from a Tweetchat.

AIM: The main aim of the study was to understand student nurses' views around shift patterns. DESIGN: Qualitative study. METHOD: We held a Tweetchat in May 2019, where we asked questions around the frequency of 12-hr shifts working on placement; schedule flexibility while on placement; which shift patterns they preferred and why. Data from the Tweetchat were analysed using reflexive thematic analysis to generate themes from initial codes. RESULTS: Seventy-three nursing students participated in the Tweetchat. The majority reported that they work 12-hr shifts on placements, particularly when based in a hospital. We identified three themes: 'Achieving a personal equilibrium'; 'Meeting the needs of the care environment'; 'Factors affecting negotiation capacity'. Data highlighted a conflict for most students, where they preferred 12-hr shifts because of more time off for study, paid work and leisure, while acknowledging 12-hr shifts negatively affected their fatigue, exhaustion and led them to follow a poor diet and neglect exercise and sleep.

Nurses' experiences and preferences around shift patterns: A scoping review.

OBJECTIVE: To explore the evidence on nurses' experiences and preferences around shift patterns in the international literature. DATA SOURCES: Electronic databases (CINHAL, MEDLINE and Scopus) were searched to identify primary studies up to April 2021. METHODS: Papers reporting qualitative or quantitative studies exploring the subjective experience and/or preferences of nurses around shift patterns were considered, with no restrictions on methods, date or setting. Key study features were extracted including setting, design and results. Findings were organised thematically by key features of shift work. RESULTS: 30 relevant papers were published between 1993 and 2021. They contained mostly qualitative studies where nurses reflected on their experience and preferences around shift patterns. The studies reported on three major aspects of shift work: shift work per se (i.e. the mere fact of working shift), shift length, and time of shift. Across all three aspects of shift work, nurses strive to deliver high quality of care despite facing intense working conditions, experiencing physical and mental fatigue or exhaustion. Preference for or adaptation to a specific shift pattern is facilitated when nurses are consulted before its implementation or have a certain autonomy to self-roster. Days off work tend to mitigate the adverse effects of working (short, long, early or night) shifts. How shift work and patterns impact on experiences and preferences seems to also vary according to nurses' personal characteristics and circumstances (e.g. age, caring responsibilities, years of experience). CONCLUSIONS: Shift patterns are often organised in ways that are detrimental to nurses' health and wellbeing, their job performance, and the patient care they provide. Further research should explore the extent to which nurses' preferences are considered when choosing or being imposed shift work patterns. Research should also strive to better describe and address the constraints nurses face when it comes to choice around shift patterns.

Outcomes sensitive to critical care nurse staffing levels: A systematic review.

OBJECTIVE: To determine associations between variations in registered nurse staffing levels in adult critical care units and outcomes such as patient, nurse, organisational and family outcomes. METHODS: We published and adhered to a protocol, stored in an open access repository and searched for quantitative studies written in the English language and held in CINAHL Plus, MEDLINE, PsycINFO, SCOPUS and NDLTD databases up to July 2020. Three authors independently extracted data and critically appraised papers meeting the inclusion criteria. Results are summarised in tables and discussed in terms of strength of internal validity. A detailed review of the two most commonly measured outcomes, patient mortality and nosocomial infection, is also presented. RESULTS: Our search returned 7960 titles after duplicates were removed; 55 studies met the inclusion criteria. Studies with strong internal validity report significant associations between lower levels of critical care nurse staffing and increased odds of both patient mortality (1.24-3.50 times greater) and nosocomial infection (3.28-3.60 times greater), increased hospital costs, lower nurse-perceived quality of care and lower family satisfaction. Meta-analysis was not feasible because of the wide variation in how both staffing and outcomes were measured. CONCLUSIONS: A large number of studies including several with high internal validity provide evidence that higher levels of critical care nurse staffing are beneficial to patients, staff and health services. However, inconsistent approaches to measurement and aggregation of staffing levels reported makes it hard to translate findings into recommendation for safe staffing in critical care.

How long do nursing staff take to measure and record patients' vital signs observations in hospital? A time-and-motion study.

INTRODUCTION: Monitoring vital signs in hospital is an important part of safe patient care. However, there are no robust estimates of the workload it generates for nursing staff. This makes it difficult to plan adequate staffing to ensure current monitoring protocols can be delivered. OBJECTIVE: To estimate the time taken to measure and record one set of patient's vital signs; and to identify factors associated with the time required to measure and record one set of patient's vital signs. METHODS: We undertook a time-and-motion study of 16 acute medical or surgical wards across four hospitals in England. Two trained observers followed a standard operating procedure to record the time taken to measure and record vital signs. We used mixed-effects models to estimate the mean time using whole vital signs rounds, which included equipment preparation, time spent taking vital signs at the bedside, vital signs documentation, and equipment storing. We tested whether our estimates were influenced by nurse, ward and hospital factors. RESULTS: After excluding non-vital signs related interruptions, dividing the length of a vital signs round by the number of vital signs assessments in that round yielded an estimated time per vital signs set of 5 min and 1 second (95% Confidence Interval (CI) = 4:39-5:24). If interruptions within the round were included, the estimated time was 6:26 (95% CI = 6:01-6:50). If only time taking each patient's vital signs at the bedside was considered, after excluding non-vital signs related interruptions, the estimated time was 3:45 (95% CI = 3:32-3:58). We found no substantial differences by hospital, ward or nurse characteristics, despite different systems for recording vital signs being used across the hospitals. DISCUSSION: The time taken to observe and record a patient's vital signs is considerable, so changes to recommended assessment frequency could have major workload implications. Variation in estimates derived from previous studies may, in part, arise from a lack of clarity about what was included in the reported times. We found no evidence that nurses save time when using electronic vital signs recording, or that the grade of staff measuring the vital signs influenced the time taken. CONCLUSIONS: Measuring and recording vital signs is time consuming and the impact of interruptions and preparation away from the bedside is considerable. When considering the nursing workload around vital signs assessment, no assumption of relative efficiency should be made if different technologies or staff groups are deployed.

Night work for hospital nurses and sickness absence: a retrospective study using electronic rostering systems.

There is conflicting evidence on the effect of night work on sickness absence. Most previous studies used self-reporting to identify shift patterns and measure levels of sickness absence. In contrast, this study used objective data from electronic rosters to explore the association of nurses' patterns of night work and sickness absence. This was a retrospective longitudinal study of nurse roster data from 32 general medical and surgical wards in a large acute hospital in England. We used data from 3 years and included both registered nurses and unregistered nursing assistants. We used generalized linear-mixed models to explore the association between night work and the subsequent occurrence of sickness absence. Of 601,282 shifts worked by 1944 nursing staff, 38,051 shifts were lost due to sickness absence. After controlling for potential confounders including proportion of long (≥12 h) shifts worked, proportion of overtime shifts, proportion of shifts worked in the past 7 days, and staff grade, we found that staff working more than 75% of their shifts in the past 7 days as night shifts were more likely to experience sickness absence (aOR = 1.12; 95% CI: 1.03-1.21), compared to staff working on day only schedules. Sub-group analysis found that an association between a high proportion of night shifts worked and long-term sickness (aOR = 1.31; 95% CI: 1.15-1.50), but not short-term sickness. Working high proportions of night shifts, likely representing permanent night work schedules, is associated with a higher risk of long-term sickness absence for nurses working in inpatient adult wards in acute hospitals. The higher sickness absence rates associated with permanent night shifts could result in additional costs or loss of productivity for hospitals. This study challenges the assumption that permanent night schedules maximize circadian adjustment and, therefore, reduce health problems.

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.

Development and validation of a methodology to measure the time taken by hospital nurses to make vital signs observations.

BACKGROUND: Several time and motion studies have sought to quantify the nursing work involved in observing patients' vital signs. However, none of these studies offered a validated methodology that can be replicated. This is reflected in the high variation between these studies in the mean times for measuring and recording observations. AIM: To describe the development and inter-rater reliability of a methodology for observing the nursing time and workload involved in measuring and recording patients' vital signs. DISCUSSION: The authors developed a methodology that used the quality of interactions (QI) tool ( Bridges et al 2018 ) to measure and record the start and finish times of the rounds of nurses observing vital signs and individual observations clustered in rounds. Two raters concurrently documented their observations of nurses undertaking patient observations in a simulated setting. The tool and associated documentation were found to be easy to use, and there was a high level of agreement in measurements by different observers. CONCLUSION: The authors' methodology can be used to reliably measure the time involved in taking vital signs. IMPLICATIONS FOR PRACTICE: Using the QI tool may increase precision when timing and classifying nursing activities concerning observing vital signs. The authors anticipate that it could be adapted effectively to measure several other nursing activities and so support researchers interested in capturing different aspects of nurses' work.

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.