Chiara Dall’oRa

Background Hospital overheating arising from more frequent heatwaves threatens healthcare staff wellbeing, patient safety and service continuity, but is often managed as an estates or seasonal problem. We examined how interacting organisational, infrastructural and experiential conditions sustain overheating vulnerability and unequal thermal burden in hospitals in the south of England. Methods We conducted a six-phase, multi-source qualitative systems inquiry integrating 129 overheating incident reports from two National Health Service (NHS) hospitals in Hampshire, England, six stakeholder interviews, two focus groups with healthcare staff and patients (n=12), and a national stakeholder refinement focus group (n=4). AI-supported thematic analysis was combined with context-mechanism-outcome synthesis and iterative AcciMap construction, to produce an integrated systems explanation. Results Twenty themes were consolidated into six interacting explanatory pathways: 1) recognition without durable resilience; 2) hidden visibility; 3) workaround-based resilience; 4) unequal adaptive capacity; 5) underuse of emergency preparedness and business-continuity systems; 6) institutional framing. The analysis indicated that, within the hospital settings investigated, overheating persisted despite recognition because ownership, information, resources and delivery capacity were fragmented across system levels. Frontline workarounds sustained care but could conceal thermal burden and defer structural adaptation. Staff and patients had unequal capacity to regulate exposure because of differences in mobility, autonomy, physiology, clinical dependency and occupational role. Existing preparedness systems offered a route from seasonal reaction to anticipatory action, but overheating was not consistently embedded within them. The AcciMap showed how shared factors connected the six pathways and identified coordinated intervention entry points across monitoring, governance, preparedness, service delivery and infrastructure. Conclusions Overheating in hospitals in England is best understood as a socio-technical patient-safety and adaptation challenge, not a single-domain estates problem. Our analysis indicates that durable resilience requires environmental intelligence linked to accountable decisions, support for staff and patient adaptation, activation of preparedness systems and long-term infrastructure change.

Objective: To elicit and quantify registered nurses’ (RNs’) preferences for key shift attributes and to estimate the trade-offs between shift pattern characteristics and pay. Design: Cross-sectional online discrete choice experiment with d-efficient design; 12 choice tasks per respondent. Preferences were estimated using multinomial logit models with clustered standard errors; willingness to accept (WTA) values were derived as ratios of attribute coefficients to the pay coefficient. Setting: United Kingdom. Participants: 1449 registered nurses (RNs) recruited via the Nursing and Midwifery Council distribution list. Primary and secondary outcome measures: Utility coefficients (β) for shift length, schedule predictability, shift request flexibility, weekend working frequency, pay level and night-shift frequency; WTA derived from the pay attribute; subgroup and interaction analyses by age, pay band, current shift status, caring responsibilities, sector and satisfaction. Results: All six attributes were statistically significant predictors of shift pattern choices. The strongest aversions were to night-only working (β=−1.113) and having no whole weekends off (β=−0.790), which required an estimated 29% additional compensation in the primary model and 21% additional compensation, respectively. Unpredictable rotas (β=−0.220), restricted shift-choice flexibility (β=−0.189 for only swaps) and absence of pay increase (β=−0.525) also reduced utility. Nine-to-ten-hour shifts were preferred over 8-hour shifts (β=0.144), whereas 12.5-hour shifts were disliked (β=−0.179). Subgroup analyses showed significant heterogeneity by age and current shift status, with more limited evidence of pay-band differences. Interaction analyses suggested broadly consistent aversion to night work and weekend loss across the nursing workforce. Conclusions: Nurses strongly prefer rota designs that avoid exclusive night work and protect whole weekends off. Predictability and meaningful scope to request shifts also matter. These preference estimates provide policy-relevant benchmarks for rota design and unsocial-hours compensation.

Objective: To examine the associations between registered nurses’ shift work patterns and sickness absence in hospital inpatient wards. Design: Retrospective longitudinal study using 1.4 million e-roster and sickness absence records analysed with logistic mixed-effects models. Setting: All adult acute inpatient hospital wards in two large healthcare organisations (Trusts) in England. Participants: Registered nurses (N=7515) working across 95 adult acute wards in 2015–2020. Primary outcome measure: Nurses’ sickness absence in relation to the shift pattern configurations worked in the previous 7 days. Logistic mixed-effects models were adjusted for total working hours, bank hours, previous sickness and part-time status. Results: Higher odds of sickness absence were significantly associated with each additional rest period of fewer than 11.5 hours (OR 1.23, 95% CI 1.19 to 1.27, p<0.001), change between day and night shifts (OR 1.09, 95% CI 1.04 to 1.13, p<0.001) and spell of 3 or more consecutive shifts (OR 1.24, 95% CI 1.16 to 1.32, p<0.001) in the previous 7 days. By accounting for nonlinearity, analyses revealed that working 70% of shifts as ≥12-hour shifts and 100% of shifts as night shifts were associated with increased odds of sickness (OR 1.68, 95% CI 1.53 to 1.84 and OR 1.07, 95% CI 1.01 to 1.13, respectively) when compared with working none of these shift types. Sensitivity analysis using 28-day exposure windows did not change the direction of effects; however, the magnitude and significance of some associations attenuated. Conclusions: This study highlights the organisational consequences of adverse working hours arrangements for registered nurses working in hospital wards. Short recovery periods, frequent shift rotations, consecutive working spells and high proportions of long and night shifts were associated with higher odds of sickness absence, with associations most apparent over 7-day exposure windows. Overall, these findings can inform shift planning policies that better support staff well-being through proactive management of sickness absence.

Background: Managing nurse staffing is complex due to fluctuating demand based on ward occupancy, patient acuity, and dependency. Monitoring staffing adequacy in real time has the potential to inform safe and efficient deployment of staff. Patient classification systems (PCSs) are being used for per shift workload measurement, but they add a frequent administrative task for ward nursing staff. Objective: The objective of this study is to explore whether an algorithm could estimate ward workload using existing routinely recorded data. Methods: Anonymized admission records and assessments from a PCS supporting the safer nursing care tool were used to determine nursing care demand in medical and surgical wards in a single UK hospital between February 2017 and February 2020. Records were linked by ward and time. The data were split into a training set (75%) and a test set (25%). We built a predictive model of ward workload (as measured by the PCS) using routinely recorded administrative data and admission National Early Warning Score. The outcome variable was ward workload derived from the patient classifications, measured as the number of whole-time equivalent (WTE) nursing staff per patient. Results: In a test set of 11,592 ward assessments from 42 wards with a mean WTE per patient of 1.64, the model’s mean absolute error was 0.078, with a mean percentage error of 4.9%. A Bland-Altman plot of the differences between the predicted values and the assessment values showed 95% of them within 0.21 WTE per patient. Conclusions: Predictions of nursing workload from a relatively small number of routinely collected variables showed moderate accuracy for general wards in 1 English hospital. This demonstrates the potential for automating assessments of nurse staffing requirements from routine data, reducing time spent on this nonclinical overhead, and improving monitoring of real-time staffing pressures.

Background: The National Health Service faces significant challenges in recruiting and retaining registered nurses. Recruiting unregistered staff is often adopted as a solution to the registered nurse shortage, but recent research found lower registered nurse staffing levels increase hospital mortality with no evidence that higher levels of assistant staff reduced risk. Objectives: To estimate the consequences, costs and cost-effectiveness of variation in the size and composition of the staff on acute hospital wards in England. To determine if results are likely to be sensitive to staff groups such as doctors and therapists, who are not on ward rosters, associations between staffing and outcomes for multiple staff groups, including medical, are explored at hospital level. Design: A national cross-sectional panel study and a patient-level longitudinal observational study using routine data. Setting: All English acute hospital Trusts and a subsample of four Trusts for the patient-level study. Interventions: Naturally occurring variation in the size and composition of the workforce. Participants: Patients experiencing a hospital admission with an overnight stay and nursing staff providing care on inpatient wards. Outcomes: Death, patient and staff experience, length of stay, re-admission, adverse events, incidents (Datix), staff sickness, costs and quality-adjusted life-years. Data sources: Publicly available records of hospital activity, staffing and outcomes (cross-sectional study) and hospital administrative systems (longitudinal study). Results: In the cross-sectional study, lower staffing levels from doctors and allied health professionals were associated with increased risk of death. Higher nurse staffing levels were associated with better patient experience and staff well-being. In the longitudinal study, for adult inpatients, exposure to days with lower-than-expected registered nurses or nursing assistant staff was associated with increased hazard of death (adjusted hazard ratio 1.08/1.07, 95% confidence interval 1.07 to 1.09/1.06 to 1.08) and longer hospital stays. Low registered nurse staffing was also associated with increased hazard of re-admission (adjusted hazard ratio 1.01, 95% confidence interval 1.01 to 1.02). Eliminating low staffing cost £2778 per quality-adjusted life-years gained. Avoidance of registered nurse understaffing gave more benefits and was more cost-effective for highly acute patients. Although high bank or agency staffing was associated with increased hazard of death, avoiding low staffing using temporary staff still reduced mortality but was more costly and less effective than using permanent staff. If costs of avoided hospital stays are included, avoiding low staffing generates a net cost saving. Exploration of thresholds for low staffing indicated a greater beneficial effect from registered nurse staffing higher than current norms. Limitations: This is an observational study. Causal inferences cannot be made from these results in isolation. Quality-adjusted life-years gains were estimated, although conclusions are not sensitive to assumptions or discount rates. We used current ward norms as reference for low staffing. Conclusions: Our results show the adverse effects of low nurse staffing but also show that medical and allied health professional staffing are important considerations for patient safety. Eliminating low registered nurse staffing gave more benefits than eliminating assistant staffing. Future work: Research is needed to validate methods to determine nurse staffing requirements, and the interaction between registered nurse and assistant staffing needs further exploration. Study registration: This study is registered as Current Controlled Trials ClinicalTrials.gov NCT04374812. 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: NIHR128056) and is published in full in Health and Social Care Delivery Research; Vol. 13, No. 25. See the NIHR Funding and Awards website for further award information.

Background Understaffing by nursing staff in hospitals is linked to patients coming to harm and dying unnecessarily. There is a vicious cycle whereby poor work conditions, including understaffing, can lead to nursing vacancies, which in turn leads to further understaffing. Is hospital investment in nursing staff, to eliminate understaffing on wards, cost-effective? Methods This longitudinal observational study analysed data on 185 adult acute units in four hospital Trusts in England over a 5-year period. We modelled the association between a patient’s exposure to ward nurse understaffing (days where staffing was below the ward mean) over the first 5 days of stay and risk of death, risk of readmission and length of stay, using survival analysis and linear mixed models. We estimated the incremental cost-effectiveness of eliminating understaffing by registered nurses (RN) and nursing support (NS) staff, estimating net costs per quality-adjusted life year (QALY). We took a hospital cost perspective. Findings Exposure to RN understaffing is associated with increased hazard of death (adjusted HR (aHR) 1.079, 95% CI 1.070 to 1.089), increased chance of readmission (aHR 1.010, 95% CI 1.005 to 1.016) and increased length of stay (ratio 1.687, 95% CI 1.666 to 1.707), while exposure to NS understaffing is associated with smaller increases in hazard of death (aHR 1.072, 95% CI 1.062 to 1.081) and length of stay (ratio 1.608, 95% CI 1.589 to 1.627) but reduced readmissions (aHR 0.994, 95% CI 0.988 to 0.999). Eliminating both RN and NS understaffing is estimated to cost £2778 per QALY (staff costs only), £2685 (including benefits of reduced staff sickness and readmissions) or save £4728 (including benefits of reduced lengths of stay). Using agency staff to eliminate understaffing is less cost-effective and would save fewer lives than using permanent members of staff. Targeting specific patient groups with improved staffing would save fewer lives and, in the scenarios tested, cost more per QALY than eliminating all understaffing. Interpretation Rectifying understaffing on inpatient wards is crucial to reduce length of stay, readmissions and deaths. According to the National Institute for Health and Care Excellence £10 000 per QALY threshold, it is cost-effective to eliminate understaffing by nursing staff. This research points towards investing in RNs over NS staff and permanent over temporary workers. Targeting particular patient groups would benefit fewer patients and is less cost-effective.

Importance: Rates of work-related stress and sickness absence are high among nurses. The consequences of sickness absence are severe for health systems’ efficiency and productivity.Objective: To examine the association between nurse staffing configurations and sickness absence in hospital inpatient unit nursing teams.Design, Setting, and Participants: This retrospective longitudinal case-control study using routinely collected hospital data among 4 general acute care hospitals in England examined 18 674 registered nurses (RNs) and nursing support (NS) staff working in 116 hospital units. Data were analyzed from April 1, 2015, to February 29, 2020.Exposure: Nursing team skill mix, temporary staffing hours, understaffing, proportion of long shifts (≥12 hours) worked, and full-time or part-time work status in the previous 7 days.Main Outcome and Measure: The main outcome was the number of episodes of sickness absence, which was defined as a sequence of sickness days with no intervening days of work.Results: There were 2 690 080 shifts and 43 097 sickness episodes. The incident rates for starting a sickness episode were 2.0% for NSs and 1.4% for RNs. In total, there were 18 674 members of staff; 2 188 562 (81.6%) were shifts by staff classified as working full time and 493 400 (18.4%) by staff classified as working part time. A skill mix composed of more RNs was associated with a 2% reduction in the odds of RN sickness absence for each 10% change in the proportion of RN hours (odds ratio [OR], 0.98; 95% CI, 0.96-0.99). Moving from the lower quartile skill mix (ie, approximately 55% of the nursing hours worked by RNs) to the upper quartile (ie, approximately 75% of the nursing hours worked by RNs) was associated with a 4% reduction in odds of sickness absence. Working only long shifts in the prior 7 days was associated with a 26% increase in the odds of sickness absence for RNs compared with working no long shifts (OR, 1.26; 95% CI, 1.19-1.33). Part-time work for RNs was associated with higher sickness absence (OR, 1.09; 95% CI, 1.03-1.15). For RNs, there was a significant interaction between part-time work and RN understaffing, whereby short staffing in the previous week increased sickness absence for full-time staff but not among those working part time. NS understaffing was not associated with sickness absence for any staffing group.Conclusions and Relevance: This retrospective case-control study found that exposure to RN understaffing increased the risk of sickness absence in nursing teams. Adverse working conditions for nurses, already known to pose a risk to patient safety, may also create risks for nurses and the possibility of further exacerbating staff shortages.

Aim: To understand how preferences and constraints of nursing staff, nurse managers and hospital directors interact and influence decisions around nurse shift patterns Background: Globally, many nursing staff have expressed intention to leave the profession and high levels of stress and burnout. Shift patterns are often cited as a key driver of negative nurse outcomes. How preferences and constraints of staff groups involved in nurse shift scheduling interact to shape decisions remains unexplored. Design: Qualitative study. We interviewed 17 nursing staff, 5 nurse managers and 6 hospital directors. Methods: Staff were recruited through 5 NHS Trusts based in the North, Midlands, East and South of England. The results were analysed using inductive and deductive framework analysis. Results: Three themes were identified that influenced nurses’ decisions for shift scheduling: 1/ Balancing Choice with Consistency, Predictability and Flexibility; 2/Adequate Rest and Recovery Between Shifts; and 3/Enjoyment and Engagement at Work. There was a meta-theme of conflicting priorities for shift scheduling between nursing staff, nurse managers and hospital directors across these three themes. Conclusions: Different priorities for shift scheduling of nursing staff, nurse managers and hospital directors created potential or actual conflict. Solutions appeared to consist of compromises where priorities of different staff groups were simultaneously upheld to an acceptable level. This occurred through collaborative interactions across staff groups. Implications for Practice: Nursing staff, nurse managers and hospital directors can facilitate choice and flexibility and navigate conflicts in nurse shift scheduling through collaborative approaches that enhance awareness and effective communication. Reporting Method: Qualitative data was reported using the EQUATOR checklist COREQ. No Patient or Public Contribution What does this paper contribute to the wider global clinical community? Collaborative approaches can influence conflicting priorities of staff groups in relation to nurse shift scheduling. Staff understanding other staff priorities for nurse shift scheduling enhances awareness.