Both intravenous thrombolysis (IVT) and intra-arterial endovascular thrombectomy (ET) improve the outcome of patients with acute ischaemic stroke, with endovascular thrombectomy being an option for those patients with large vessel occlusions. We sought to understand how organisation of services affects time to treatment for both intravenous thrombolysis and endovascular thrombectomy. Method: A multi-objective optimisation approach was used to explore the relationship between the number of intravenous thrombolysis and endovascular thrombectomy centres and times to treatment. The analysis is based on 238,887 emergency stroke admissions in England over 3 years (2013-2015). Results: Providing hyper-acute care only in comprehensive stroke centres (CSC, providing both intravenous thrombolysis and endovascular thrombectomy, and performing >150 endovascular thrombectomy per year, maximum 40 centres) in England would lead to 15% of patients being more than 45 min away from care, and would create centres with up to 4300 stroke admissions/year. Mixing hyper-acute stroke units (providing intravenous thrombolysis only) with comprehensive stroke centres speeds time to intravenous thrombolysis and mitigates admission numbers to comprehensive stroke centres, but at the expense of increasing time to endovascular thrombectomy. With 24 comprehensive stroke centres and all remaining current acute stroke units as hyperacute stroke units, redirecting patients directly to attend a comprehensive stroke centre by accepting a small delay (15-min maximum) in intravenous thrombolysis reduces time to endovascular thrombectomy: 25% of all patients would be redirected from hyper-acute stroke units to a comprehensive stroke centre, with an average delay in intravenous thrombolysis of 8 min, and an average improvement in time to endovascular thrombectomy of 80 min. The balance of comprehensive stroke centre:hyper-acute stroke unit admissions would change from 24:76 to 49:51. Conclusion: Planning of hyper-acute stroke services is best achieved when considering all forms of acute care and ambulance protocol together. Times to treatment need to be considered alongside manageable and sustainable admission numbers.

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BackgroundHospital emergency admissions have risen annually, exacerbating pressures on emergency departments (EDs) and acute medical units. These pressures have an adverse impact on patient experience and potentially lead to suboptimal clinical decision-making. In response, a variety of innovations have been developed, but whether or not these reduce inappropriate admissions or improve patient and clinician experience is largely unknown.AimsTo investigate the interplay of service factors influencing decision-making about emergency admissions, and to understand how the medical assessment process is experienced by patients, carers and practitioners.MethodsThe project used a multiple case study design for a mixed-methods analysis of decision-making about admissions in four acute hospitals. The primary research comprised two parts: value stream mapping to measure time spent by practitioners on key activities in 108 patient pathways, including an embedded study of cost; and an ethnographic study incorporating data from 65 patients, 30 carers and 282 practitioners of different specialties and levels. Additional data were collected through a clinical panel, learning sets, stakeholder workshops, reading groups and review of site data and documentation. We used a realist synthesis approach to integrate findings from all sources.FindingsPatients’ experiences of emergency care were positive and they often did not raise concerns, whereas carers were more vocal. Staff’s focus on patient flow sometimes limited time for basic care, optimal communication and shared decision-making. Practitioners admitted or discharged few patients during the first hour, but decision-making increased rapidly towards the 4-hour target. Overall, patients’ journey times were similar, although waiting before being seen, for tests or after admission decisions, varied considerably. The meaning of what constituted an ‘admission’ varied across sites and sometimes within a site. Medical and social complexity, targets and ‘bed pressure’, patient safety and risk, each influenced admission/discharge decision-making. Each site responded to these pressures with different initiatives designed to expedite appropriate decision-making. New ways of using hospital ‘space’ were identified. Clinical decision units and observation wards allow potentially dischargeable patients with medical and/or social complexity to be ‘off the clock’, allowing time for tests, observation or safe discharge. New teams supported admission avoidance: an acute general practitioner service filtered patients prior to arrival; discharge teams linked with community services; specialist teams for the elderly facilitated outpatient treatment. Senior doctors had a range of roles: evaluating complex patients, advising and training juniors, and overseeing ED activity.ConclusionsThis research shows how hospitals under pressure manage complexity, safety and risk in emergency care by developing ‘ground-up’ initiatives that facilitate timely, appropriate and safe decision-making, and alternative care pathways for lower-risk, ambulatory patients. New teams and ‘off the clock’ spaces contribute to safely reducing avoidable admissions; frontline expertise brings value not only by placing senior experienced practitioners at the front door of EDs, but also by using seniors in advisory roles. Although the principal limitation of this research is its observational design, so that causation cannot be inferred, its strength is hypothesis generation. Further research should test whether or not the service and care innovations identified here can improve patient experience of acute care and safely reduce avoidable admissions.FundingThe National Institute for Health Research (NIHR) Health Services and Delivery Research programme (project number 10/1010/06). This research was supported by the NIHR Collaboration for Leadership in Applied Health Research and Care South West Peninsula.

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BackgroundIncreasing pressure in the United Kingdom (UK) urgent care system has led to Emergency Departments (EDs) failing to meet the national requirement that 95% of patients are admitted, discharged or transferred within 4-h of arrival. Despite the target being the same for all acute hospitals, individual Trusts organise their services in different ways. The impact of this variation on patient journey time and waiting is unknown. Our study aimed to apply the Lean technique of Value Stream Mapping (VSM) to investigate care processes and delays in patient journeys at four contrasting hospitals.MethodsVSM timing data were collected for patients accessing acute care at four hospitals in South West England. Data were categorised according to waits and activities, which were compared across sites to identify variations in practice from the patient viewpoint. We included Public and Patient Involvement (PPI) to fully interpret our findings; observations and initial findings were considered in a PPI workshop.ResultsOne hundred eight patients were recruited, comprising 25,432 min of patient time containing 4098 episodes of care or waiting. The median patient journey was 223 min (3 h, 43 min); just within the 4-h target. Although total patient journey times were similar between sites, the stage where the greatest proportion of waiting occurred varied. Reasons for waiting were dominated by waits for beds, investigations or results to be available. From our sample we observed that EDs without a discharge/clinical decision area exhibited a greater proportion of waiting time following an admission or discharge decision. PPI interpretation indicated that patients who experience waits at the beginning of their journey feel more anxious because they are ‘not in the system yet’.ConclusionsThe novel application of VSM analysis across different hospitals, coupled with PPI interpretation, provides important insight into the impact of care provision on patient experience. Measures that could reduce patient waiting include automatic notification of test results, and the option of discharge/clinical decision areas for patients awaiting results or departure. To enhance patient experience, good communication with patients and relatives about reasons for waits is essential.

BackgroundThere is a tension in many health-care services between the expertise and efficiency that comes with centralising services and the ease of access for patients. Neonatal care is further complicated by the organisation of care into networks where different hospitals offer different levels of care and where capacity across, or between, networks may be used when local capacity is exhausted.ObjectivesTo develop a computer model that could mimic the performance of a neonatal network and predict the effect of altering network configuration on neonatal unit workloads, ability to meet nurse staffing guidelines, and distance from the parents’ home location to the point of care. The aim is to provide a model to assist in planning of capacity, location and type of neonatal services.DesignDescriptive analysis of a current network, economic analysis and discrete event simulation. During the course of the project, two meetings with parents were held to allow parent input.SettingThe Peninsula neonatal network (Devon and Cornwall) with additional work extending to the Western network.Main outcome measuresAbility to meet nurse staffing guidelines, cost of service provision, number and distance of transfers, average travel distances for parents, and numbers of parents with an infant over 50 km from home.Data sourcesAnonymised neonatal data for 7629 infants admitted into a neonatal unit between January 2011 and June 2013 were accessed from Badger patient care records. Nurse staffing data were obtained from a daily ring-around audit. Further background data were accessed from NHS England general practitioner (GP) Practice Profiles, Hospital Episode Statistics, Office for National Statistics and NHS Connecting for Health. Access to patient care records was approved by the Research Ethics Committee and the local Caldicott Guardian at the point of access to the data.ResultsWhen the model was tested against a period of data not used for building the model, the model was able to predict the occupancy of each hospital and care level with good precision (R2 > 0.85 for all comparisons). The average distance from the parents’ home location (GP location used as a surrogate) was predicted to within 2 km. The number of transfers was predicted to within 2%. The model was used to forecast the effect of centralisation. Centralisation led to reduced nurse requirements but was accompanied by a significant increase in parent travel distances. Costs of nursing depend on how much of the time nursing guidelines are to be met, rising from £4500 per infant to meet guidelines 80% of the time, to £5500 per infant to meet guidelines 95% of the time. Using network capacity, rather than local spare capacity, to meet local peaks in workloads can reduce the number of nurses required, but the number of transfers and the travel distance for parents start to rise significantly above ≈ 70% network capacity utilisation.ConclusionsWe have developed a model that predicts performance of a neonatal network from the perspectives of both the service provider and the parents of infants in care.Future workApplication of the model at a national level.FundingThe National Institute for Health Research Health Services and Delivery Research programme.

BackgroundMathematical capacity planning methods that can take account of variations in patient complexity, admission rates and delayed discharges have long been available, but their implementation in complex pathways such as stroke care remains limited. Instead simple average based estimates are commonplace. These methods often substantially underestimate capacity requirements.We analyse the capacity requirements for acute and community stroke services in a pathway with over 630 admissions per year. We sought to identify current capacity bottlenecks affecting patient flow, future capacity requirements in the presence of increased admissions, the impact of co-location and pooling of the acute and rehabilitation units and the impact of patient subgroups on capacity requirements. We contrast these results to the often used method of planning by average occupancy, often with arbitrary uplifts to cater for variability.MethodsWe developed a discrete-event simulation model using aggregate parameter values derived from routine administrative data on over 2000 anonymised admission and discharge timestamps. The model mimicked the flow of stroke, high risk TIA and complex neurological patients from admission to an acute ward through to community rehab and early supported discharge, and predicted the probability of admission delays.ResultsAn increase from 10 to 14 acute beds reduces the number of patients experiencing a delay to the acute stroke unit from 1 in every 7 to 1 in 50. Co-location of the acute and rehabilitation units and pooling eight beds out of a total bed stock of 26 reduce the number of delayed acute admissions to 1 in every 29 and the number of delayed rehabilitation admissions to 1 in every 20. Planning by average occupancy would resulted in delays for one in every five patients in the acute stroke unit.ConclusionsPlanning by average occupancy fails to provide appropriate reserve capacity to manage the variations seen in stroke pathways to desired service levels. An appropriate uplift from the average cannot be based simply on occupancy figures. Our method draws on long available, intuitive, but underused mathematical techniques for capacity planning. Implementation via simulation at our study hospital provided valuable decision support for planners to assess future bed numbers and organisation of the acute and rehabilitation services.Electronic supplementary materialThe online version of this article (doi:10.1186/s12913-016-1789-4) contains supplementary material, which is available to authorized users.

Although taxonomic proficiency is a prerequisite for understanding ideas central to biology, previous research has established that learners frequently misclassify animals by not following the tenets of accepted taxonomic rubrics. This has immediate relevance with the recently revised English National Curriculum now requiring concepts of animal classification to be taught to 5–6 year‐olds. The current study represents an attempt to explore how preschool children aged 3–5 years classify animals, and patterns in the ways in which their taxonomic knowledge might progress with age were sought to illuminate potential origins of naive conceptions in the early years. A quantitative approach was employed with a sample of 75 children utilising a structured interview method to determine their ideas about the taxonomic labels animal, fish, amphibian, reptile, bird, mammal and insect. Findings revealed common learning trajectories as children's prototypes developed from 3 to 5 years. These trajectories confirmed that the preschool children held many of the same naive conceptions as those previously reported in older learners. Some of these conceptions started to dissipate with age; however, others began to emerge in the older children within the sample, representing a decline in performance with age. This decline is concerning though can be accounted for by contemporary categorization theory, giving support to the view that science misconceptions can emerge in the early years due to natural maturation (cognitive factors), as well as exposure to formal and informal learning experiences (socio‐cultural factors). To supplement established conceptual change strategies, which deal with already‐formed misconceptions, it is proposed that there be a fresh research emphasis towards conceptual creation where acceptable scientific ideas are seeded at the earliest years of schooling. Accordingly, the role of early years educators would become fundamental to effective science education. © 2014 Wiley Periodicals, Inc. J Res Sci Teach 52: 107–134, 2015