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ObjectiveTo examine the impact of nursing team size and composition on inpatient hospital mortality.DesignA retrospective longitudinal study using linked nursing staff rostering and patient data. Multilevel conditional logistic regression models with adjustment for patient characteristics, day and time-invariant ward differences estimated the association between inpatient mortality and staffing at the ward-day level. Two staffing measures were constructed: the fraction of target hours worked (fill-rate) and the absolute difference from target hours.SettingThree hospitals within a single National Health Service Trust in England.Participants19 287 ward-day observations with information on 4498 nurses and 66 923 hospital admissions in 53 inpatient hospital wards for acutely ill adult patients for calendar year 2017.Main outcome measureIn-hospital deaths.ResultsA statistically significant association between the fill-rate for registered nurses (RNs) and inpatient mortality (OR 0.9883, 95% CI 0.9773 to 0.9996, p=0.0416) was found only for RNs hospital employees. There was no association for healthcare support workers (HCSWs) or agency workers. On average, an extra 12-hour shift by an RN was associated with a reduction in the odds of a patient death of 9.6% (OR 0.9044, 95% CI 0.8219 to 0.9966, p=0.0416). An additional senior RN (in NHS pay band 7 or 8) had 2.2 times the impact of an additional band 5 RN (fill-rate for bands 7 and 8: OR 0.9760, 95% CI 0.9551 to 0.9973, p=0.0275; band 5: OR 0.9893, 95% CI 0.9771 to 1.0017, p=0.0907).ConclusionsRN staffing and seniority levels were associated with patient mortality. The lack of association for HCSWs and agency nurses indicates they are not effective substitutes for RNs who regularly work on the ward.

Background Resilient Healthcare research centres on understanding and improving quality and safety in healthcare. The Concepts for Applying Resilience Engineering (CARE) model highlights the relationships between demand, capacity, work-as-done, work-as-imagined, and outcomes, all of which are central aspects of Resilient Healthcare theory. However, detailed descriptions of the nature of misalignments and the mechanisms used to adapt to them are still unknown. Objective The objectives were to identify and classify types of misalignments between demand and capacity and types of adaptations that were made in response to misalignments. Methods The study involved 88.5 hours of non-participant ethnographic observations in a large, teaching hospital in central London. The wards included in the study were: two surgical wards, an older adult ward, a critical care unit, and the Acute Assessment Unit (AAU), an extension unit created to expedite patient flow out of the Emergency Department. Data were collected via observations of routine clinical work and ethnographic interviews with healthcare professionals during the observations. Field notes were transcribed and thematically analysed using a combined deductive-inductive approach based on the CARE model. Results A total of 365 instances of demand-capacity misalignment were identified across the five wards included in the study. Of these, 212 had at least one observed corresponding work adaptation. Misalignments identified include equipment, staffing, process, communication, workflow, and space. Adaptations identified include process, resource redistribution, and extra-role performance. For all misalignment types observed across the five in-patient settings, process adaptations were the most frequently used adaptations. The exception to this was for staffing misalignments, which were most frequently responded to with extra-role performance adaptations. Of the three process adaptations, hospital workers most often adapted by changing how the process was done. Conclusions This study contributes a new version of the CARE model that includes types of misalignments and corresponding adaptations, which can be used to better understand work-as-done. This affords insight into the complexity of the system and how it might be improved by reducing misalignments via work system redesign or by enhancing adaptive capacity.

Background Open Disclosure (OD) is open and timely communication about harmful events arising from health care with those affected. It is an entitlement of service-users and an aspect of their recovery, as well as an important dimension of service safety improvement. Recently, OD in maternity care in the English National Health Service has become a pressing public issue, with policymakers promoting multiple interventions to manage the financial and reputational costs of communication failures. There is limited research to understand how OD works and its effects in different contexts. Methods Realist literature screening, data extraction, and retroductive theorisation involving two advisory stakeholder groups. Data relevant to families, clinicians, and services were mapped to theorise the relationships between contexts, mechanisms, and outcomes. From these maps, key aspects for successful OD were identified. Results After realist quality appraisal, 38 documents were included in the synthesis (22 academic, 2 training guidance, and 14 policy report). 135 explanatory accounts were identified from the included documents (with n = 41 relevant to families; n = 37 relevant to staff; and n = 37 relevant to services). These were theorised as five key mechanism sets: (a) meaningful acknowledgement of harm, (b) opportunity for family involvement in reviews and investigations, (c) possibilities for families and staff to make sense of what happened, (d) specialist skills and psychological safety of clinicians, and (e) families and staff knowing that improvements are happening. Three key contextual factors were identified: (a) the configuration of the incident (how and when identified and classified as more or less severe); (b) national or state drivers, such as polices, regulations, and schemes, designed to promote OD; and (c) the organisational context within which these these drivers are recieived and negotiated. Conclusions This is the first review to theorise how OD works, for whom, in what circumstances, and why. We identify and examine from the secondary data the five key mechanisms for successful OD and the three contextual factors that influence this. The next study stage will use interview and ethnographic data to test, deepen, or overturn our five hypothesised programme theories to explain what is required to strengthen OD in maternity services.

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