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Background: Nurses play a crucial role in maintaining the safety of surgical patients. Few nurse staffing studies have looked specifically at surgical patients to examine the impact of exposure to low staffing on patient outcomes. Methods: A longitudinal patient analysis was conducted in four organizations in England using routine data from 213 910 admissions to all surgical specialties. Patients' staffing exposures were modelled as counts of understaffed registered nurse and nurse assistant days in the first 5 inpatient days. Understaffing was identified when staffing per patient-day was below the mean for the ward. Cox models were used to examine mortality within 30 days of admission and readmission within 30 days of discharge. Generalized linear models were used to investigate duration of hospital stay and occurrence of hospital-acquired conditions. Results: Increased exposure to registered nurse understaffing was associated with longer hospital stay and increased risk of deep vein thrombosis, pneumonia, and pressure ulcers. This was also true for nurse assistant understaffing, but the effect sizes tended to be smaller. In the Cox models, there were similarly increased hazards of death for registered nurse understaffing (HR 1.09, 95% c.i. 1.07 to 1.12) and nurse assistant understaffing (HR 1.10, 1.08 to 1.13), whereas the effect size of registered nurse understaffing for readmission (HR 1.02, 1.02 to 1.03) was greater than that seen with nurse assistants (HR 1.01, 1.01 to 1.02). Conclusion: Understaffing by both registered nurses and nursing assistants is associated with increased risks of a range of adverse events, and generally larger effects are seen with registered nurse understaffing. This observational longitudinal study examined nurse staffing levels and their association with a variety of adverse patient outcomes for inpatient admissions to all surgical specialties. The patient-level data came from four disparate National Health Service hospital Trusts in England. The results indicated generally larger adverse effects for registered nurse understaffing compared with understaffing for nurse assistants (healthcare support workers and nurse associates). [ABSTRACT FROM AUTHOR]

Health service providers must balance the needs of high-risk patients who require urgent medical attention against those of lower-risk patients who require reassurance or less urgent medical care. Based on their characteristics, we developed a tool to classify patients as low- or high-risk, with correspondingly different patient pathways through a service. Rather than choosing the threshold between low- and high-risk patients solely considering classification accuracy, we demonstrate the use of discrete-event simulation to find the best threshold from an operational perspective as well. Moreover, the predictors in classification tools are often categorical, and may be inter-dependent. Defining joint distributions of these variables from empirical data assumes that missing combinations are impossible. Our new approach involves using Poisson regression to estimate the joint distributions in the underlying population. We demonstrate our methods on a practical example: setting the threshold between low- and high-risk patients with proposed different pathways through a breast diagnostic clinic. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background Planning numbers of nursing staff allocated to each hospital ward (the 'staffing establishment') is challenging because both demand for and supply of staff vary. Having low numbers of registered nurses working on a shift is associated with worse quality of care and adverse patient outcomes, including higher risk of patient safety incidents. Most nurse staffing tools recommend setting staffing levels at the average needed but modelling studies suggest that this may not lead to optimal levels. Objective Using computer simulation to estimate the costs and understaffing/overstaffing rates delivered/caused by different approaches to setting staffing establishments. Methods We used patient and roster data from 81 inpatient wards in four English hospital Trusts to develop a simulation of nurse staffing. Outcome measures were understaffed/overstaffed patient shifts and the cost per patient- day. We compared staffing establishments based on average demand with higher and lower baseline levels, using an evidence-based tool to assess daily demand and to guide flexible staff redeployments and temporary staffing hires to make up any shortfalls. Results When baseline staffing was set to meet the average demand, 32% of patient shifts were understaffed by more than 15% after redeployment and hiring from a limited pool of temporary staff. Higher baseline staffing reduced understaffing rates to 21% of patient shifts. Flexible staffing reduced both overstaffing and understaffing but when used with low staffing establishments, the risk of critical understaffing was high, unless temporary staff were unlimited, which was associated with high costs. Conclusion While it is common practice to base staffing establishments on average demand, our results suggest that this may lead to more understaffing than setting establishments at higher levels. Flexible staffing, while an important adjunct to the baseline staffing, was most effective at avoiding understaffing when high numbers of permanent staff were employed. Low staffing establishments with flexible staffing saved money because shifts were unfilled rather than due to efficiencies. Thus, employing low numbers of permanent staff (and relying on temporary staff and redeployments) risks quality of care and patient safety. [ABSTRACT FROM AUTHOR]