Decoding healthcare teamwork: a typology of hospital teams.

The effectiveness of healthcare depends on successful teamwork. Current understanding of teamwork in healthcare is limited due to the complexity of the context, variety of team structures, and unique demands of healthcare work. This qualitative study aimed to identify different types of healthcare teams based on their structure, membership, and function. The study used an ethnographic approach to observe five teams in an English hospital. Data were analyzed using a combined inductive-deductive approach based on the Temporal Observational Analysis of Teamwork framework. A typology was developed, consisting of five team types: structural, hybrid, satellite, responsive, and coordinating. Teams were challenged to varying degrees with staffing, membership instability, equipment shortages, and other elements of the healthcare environment. Teams varied in their ability to respond to these challenges depending on their characteristics, such as their teamworking style, location, and membership. The typology developed in this study can help healthcare organizations to better understand and design effective teams for different healthcare contexts. It can also guide future research on healthcare teams and provide a framework for comparing teams across settings. To improve teamwork, healthcare organizations should consider the unique needs of different team types and design effective training programs accordingly.

Improving the quality of written communication at patient discharge: triangulation of qualitative analyses and intervention co-design.

BACKGROUND: Poor handovers between hospital and primary care threaten safe discharges, with elderly and frail patients most at risk of harm. Using Behavioural Science we explored influences and identified relevant behaviour change techniques (BCTs) to improve written handovers and safety during discharge. METHODS: We conducted two qualitative studies: (1) ethnographic observations (>80 h) collected by five researchers in five purposively sampled clinical areas of a London teaching hospital, investigating routine work and interactions of hospital staff involved in discharges; and (2) 12 semi-structured interviews with hospital staff involved in discharge exploring influences on preparations of written handovers. Written consent was sought from clinical leads for ethnographic observations and from interview participants. Ethnographic fieldnotes and interview transcripts were thematically analysed using inductive and deductive approaches, respectively. Study findings were triangulated to identify key influences, mapped onto the Theoretical Domains Framework (TDF). We identified appropriate BCTs to address observed influences within each TDF domain using the Theory and Techniques Tool. Health-care workers (n=15), patients (n=2) and carers (n=2) selected and designed an intervention to improve written handovers in two workshops. Hospital workshop participants were involved with preparing written discharge handovers. Public participants had either recently been discharged from hospital or cared for someone recently discharged, including patients from groups especially vulnerable during discharge. FINDINGS: Triangulation of study findings generated 11 key influences on preparations of written handovers within five TDF domains: knowledge (eg, lack of awareness of guidelines), skills (staff experience), social or professional role and identity (effective communication), environmental context and resources (working patterns), and social influences (lack of feedback). 14 BCTs were identified to address these influences, including behavioural rehearsal or practice, instruction on how to perform a behaviour, and social support (practical). Workshop participants selected and designed a multifaceted educational intervention to improve written handovers. INTERPRETATION: The quality of handover documentation prepared by hospital staff for primary care teams is affected by influences from multiple domains, requiring a multifaceted approach to improve handovers. Although only based on findings from one hospital, the designed intervention should be tested in clinical settings with key stakeholders, including primary care staff, to evaluate impact on quality of written handovers and patient safety. FUNDING: National Institute for Health and Care Research (NIHR) Imperial Patient Safety Translational Research Centre.

Strengthening open disclosure after incidents in maternity care: a realist synthesis of international research evidence.

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.

Nurse staffing and inpatient mortality in the English National Health Service: a retrospective longitudinal study.

OBJECTIVE: To examine the impact of nursing team size and composition on inpatient hospital mortality. DESIGN: A 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. SETTING: Three hospitals within a single National Health Service Trust in England. PARTICIPANTS: 19 287 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 MEASURE: In-hospital deaths. RESULTS: A 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). CONCLUSIONS: RN 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.

Understanding complex work using an extension of the resilience CARE model: an ethnographic study.

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.

Capturing challenges and trade-offs in healthcare work using the pressures diagram: An ethnographic study.

Healthcare workers must balance competing priorities to deliver high-quality patient care. Rasmussen's Dynamic Safety Model proposed three factors that organisations must balance to maintain acceptable performance, but there has been little empirical exploration of these ideas, and little is known about the risk trade-offs workers make in practice. The aim of this study was to investigate the different pressures that healthcare workers experience, what risk trade-off decisions they make in response to pressures, and to analyse the implications for quality and safety. The study involved 88.5 h of ethnographic observations at a large, teaching hospital in central London. The analysis revealed five distinct categories of hospital pressures faced by healthcare workers: efficiency, organisational, workload, personal, and quality and safety pressures. Workers most often traded-off workload, personal, and quality and safety pressures to accommodate system-level priorities. The Pressures Diagram was developed to visualise risk trade-offs and prioritising decisions and to facilitate communication about these aspects of healthcare work.