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Aims: Background: Upper gastrointestinal (UGI) cancers (pancreatic, oesophageal and stomach) have a dismal prognosis, with five-year survival of only 7.7-28.5% even when detected in their early stages and treated with a complete resection. UGI cancers are characterised by a high symptom burden. It is critical that patients with these cancers receive the best possible symptomatic control, while the search continues for treatments to improve survival. Recent research has shown that patient-reported outcomes (PROs), integrated into clinical practice in a meaningful way to drive action, are associated with improved patient health outcomes and decrease burden to the healthcare system. Aim(s): To determine whether the systematic measurement, identification and management of PROs in clinical practice, coupled with information support to patients, improves health outcomes for patients with UGI cancers. Methods and Design: A registry-based randomised, multicentre, controlled trial will be designed to assess whether, compared to usual practice, the UGI Cancer Care Coordination (UGICCC) intervention is effective in improving health-related quality of life in patients diagnosed with UGI cancers, as the primary outcome. The UGICCC intervention involves: (1) collection of PROs to allow patients to track and report their symptoms over time; (2) provision of real-time feedback to patients for management of symptoms; and (3) alerts to a care-coordinator of patients reporting severe or worsening symptoms to allow for triage and follow-up as well as provision of real-time reports to clinicians. The secondary outcome measures are to assess whether patients assigned to the intervention arm demonstrate: reduced health service use and emergency department visits; lower level of information needs; timely referral to palliative care services; and increased median survival. These will be evaluated at baseline, 3-, 6- and 12-months. Participants will be recruited from eight hospitals in Victo

Introduction: Upper gastrointestinal cancers are a significant health problem, with low survival, high symptom burden and unmet supportive care needs. Evidence-based clinical care pathways to standardise symptommanagement could provide a means to reduce symptom burden and improve quality of life in these patients. Method(s): A standardised model for clinical pathway development was used, this included: 1) assembling a team of experts; 2) compiling and reviewing existing literature; and 3) developing the pathway via a consensus working group process. A Clinical Working Group (CWG) was convened and included representatives of relevant specialities with established expertise and clinical experience from across ten public, private, metropolitan and regional health services inVictoria, Australia. Literature reviews were conducted to identify existing clinical symptom management and triage pathways or guidelines for patients with cancer as well as to identify any validated disease-specific patientreported outcome measures in order to ascertain potential symptoms. The initial pathways were drafted by cancer nurse consultants with over 10-years clinical experience in consultation with a 'clinical champion'. The CWGheld workshops to discuss and review each of the draft pathways. The pathways were updated and circulated to the whole CWGvia email for final approval. Result(s): A total of 64 disease-specific symptoms were identified. The CWG finalised and approved 19 clinical pathways to manage these symptoms. Each clinical pathway includes an informed tailored clinical assessment of the symptom based on the NOPQRSTUV Symptom Assessment Acronym, triage of the symptom using the Common Terminology Criteria for Adverse Events (Version 5.0) and interventions for appropriate follow-up care. Conclusion(s): A multidisciplinary approach and clinical consensus informed the development of evidence-based clinical pathways, which provide a standardised platform to appropriately manage and

Introduction: Recent randomized trials showing improved outcomes for later-presenting acute ischaemic stroke (AIS) patients with large vessel occlusion (LVO) treated with endovascular clot retrieval (ECR) may result in substantial increases in CTP utilization. This 3-hospital, single-institution cohort study aimed to compare 2017 and 2018 patient cohorts for the following: CTP use in AIS. Prevalence of LVO in all patients having CTP. Number and clinical characteristics of patients triaged to ECR. Number of patients receiving CTP relative to similar-acuity total ED presentations. Method(s): Inclusion criteria: Consecutive adult emergency (ED) patients receiving CTP for suspected AIS. Study period 1:1 January-30 June 2017; Period 2:1 January-30 June 2018. Data collection: age, gender, triage category, NIHSS (National Institute of Health Stroke Score), symptoms/signs, time elapsed since last seen well (TESLSW) to triage, disposition (home/other). Result(s): A 38.7 % increase in CTP (512 in 2017, 710 in 2018) occurred with 39/512 (7.6%) and 72/710 (10.1%) having intended ECR. CTPs per intended ECR declined from 13.1 to 9.9. 36/512 (7.0%) and 58/710 (8.2%) patients had ECR (61.1% increase) and 22/36 (61.1%) and 25/58 (43.1%) of these were discharged home in 2017 and 2018, respectively, an increase of 3/22(14%). Conclusion(s): Despite a 38.7% increase in CTP utilization, we experienced a reduction in the number of CTPs performed/patient triaged to ECR. This did not reflect higher LVO prevalence among later presenters but may reflect changed selection criteria for CTP and/or decision making about suitability for ECR.Copyright © 2020 The Royal Australian and New Zealand College of Radiologists

Background and Purpose: Severity-based assessment tools may assist in prehospital triage of patients to comprehensive stroke centers (CSCs) for endovascular thrombectomy (EVT), but criticisms regarding diagnostic inaccuracy have not been adequately addressed. This study aimed to quantify the benefits and disadvantages of severity-based triage in a large real-world paramedic validation of the Ambulance Clinical Triage for Acute Stroke Treatment (ACT-FAST) algorithm. Method(s): Ambulance Victoria paramedics assessed the prehospital ACT-FAST algorithm in patients with suspected stroke from November 2017 to July 2019 following an 8-minute training video. All patients were transported to the nearest stroke center as per current guidelines. ACT-FAST diagnostic accuracy was compared with hospital imaging for the presence of large vessel occlusion (LVO) and need for CSC-level care (LVO, intracranial hemorrhage, and tumor). Patient-level time saving to EVT was modeled using a validated Google Maps algorithm. Disadvantages of CSC bypass examined potential thrombolysis delays in non-LVO infarcts, proportion of patients with false-negative EVT, and CSC overburdening. Result(s): Of 517 prehospital assessments, 168/517 (32.5%) were ACT-FAST positive and 132/517 (25.5%) had LVO. ACT-FAST sensitivity and specificity for LVO was 75.8% and 81.8%, respectively. Positive predictive value was 58.8% for LVO and 80.0% when intracranial hemorrhage and tumor (CSC-level care) were included. Within the metropolitan region, 29/55 (52.7%) of ACT-FAST-positive patients requiring EVT underwent a secondary interhospital transfer. Prehospital bypass with avoidance of secondary transfers was modeled to save 52 minutes (95% CI, 40.0-61.5) to EVT commencement. ACT-FAST was false-positive in 8 patients receiving thrombolysis (8.1% of 99 non-LVO infarcts) and false-negative in 4 patients with EVT requiring secondary transfer (5.4% of 74 EVT cases). CSC bypass was estimated to over-triage 1.1 patients-pe

Objectives To describe contemporary characteristics and diagnoses in prehospital patients with chest pain and to identify factors suitable for the early recognition of high-risk and low-risk conditions. Design Prospective observational cohort study. Setting Two centre study in a Swedish county emergency medical services (EMS) organisation. Participants Unselected inclusion of 2917 patients with chest pain contacting the EMS due to chest pain during 2018. Primary outcome measures Low-risk or high-risk condition, that is, occurrence of time-sensitive diagnosis on hospital discharge. Results Of included EMS missions, 68% concerned patients with a low-risk condition without medical need of acute hospital treatment in hindsight. Sixteen per cent concerned patients with a high-risk condition in need of rapid transport to hospital care. Numerous variables with significant association with low-risk or high-risk conditions were found. In total high-risk and low-risk prediction models shared six predictive variables of which ST-depression on ECG and age were most important. Previously known risk factors such as history of acute coronary syndrome, diabetes and hypertension had no predictive value in the multivariate analyses. Some aspects of the symptoms such as pain intensity, pain in the right arm and paleness did on the other hand appear to be helpful. The area under the curve (AUC) for prediction of low-risk candidates was 0.786 and for high-risk candidates 0.796. The addition of troponin in a subset increased the AUC to >0.8 for both. Conclusions A majority of patients with chest pain cared for by the EMS suffer from a low-risk condition and have no prognostic reason for acute hospital care given their diagnosis on hospital discharge. A smaller proportion has a high-risk condition and is in need of prompt specialist care. Building models with good accuracy for prehospital identification of these groups is possible. The use of risk stratification models could make a mor

Background: Surgical capacity building has gained substantial momentum. However, care at the hospital level depends on improved access to emergency services. There is no established model for facilitating trauma and EMS system capacity in LMIC settings. This manuscript describes our model for multi-disciplinary collaboration to advance trauma and EMS capacity in Rwanda, along with our lessons and recommendations. Methods: After high-level meetings at the Ministry of Health in Rwanda (MOH), in 2016, a capacity building plan focusing on improved clinical services, quality improvement/research and leadership capacity across prehospital and emergency settings. The main themes for the collaborative model included for empowerment of staff, improving clinical service delivery, and investing in systems and infrastructure. Funding was sought and incorporated into the Sector Wide Approaches to Planning process at the Ministry of Health of Rwanda. Findings: A shared mental model was created through a fully funded immersion program for Rwandese leaders from emergency medicine, nursing, prehospital care, and injury policy. Prehospital care delivery was standardized within Kigali through a train-the-trainers program with four new context-appropriate short courses in trauma, medical, obstetric/neonatal, and pediatric emergencies and expanded across the country to reach >600 staff at district and provincial hospitals. Forty-two protocols and checklists were implemented to standardize prehospital care across specialties. The WHO Trauma Registry was instituted across four major referral centers in the country capturing over 5,000 injured patients. Long-term research capacity development included Masters' Degree support for 11 staff. Conclusions and recommendations: This collaboration was highly productive in empowering staff and leadership, standardizing clinical service delivery in EMS, and investing in systems and infrastructure. This can be a useful model for trauma and EMS system

Background: There is a strong biomedical focus within emergency care. However, while failure to meet patients’ fundamental care needs has severe consequences for the patient, there is limited knowledge on how nursing care is provided in emergency rooms and the related implications for patients. Aim: This study aims to explore how fundamental care needs of critically ill patients are met in emergency rooms. Methods: Non-participant observations at an emergency department in Sweden included 108 observations and field notes (150 h). Data were analysed using descriptive statistics. Results: Observations showed that registered nurses (RN) identified patients’ fundamental care needs and provided nursing care. However, the RNs’ focus on the patient decreased over time. When the RN communicated with the patient, the patients’ physical needs were met to a greater extent. The organisational structure and physical environment of emergency rooms limit RNs’ ability to meet patients’ fundamental care needs. Conclusion: Not all patients had their fundamental care needs optimally met. This study highlights the importance of RNs working in an integrated manner; an RN working bedside is crucial for establishing a patient–nurse relationship to meet the patient's physical, psychosocial, and relational needs.

The emergency handover of critical patients is used to describe the moment when re-sponsibility for the care of a patient is transferred from one critical patient care healthcare team to another, requiring the accurate delivery of information. However, the literature provides few validated assessment tools for the transfer of critical patients in urgent care and emergency settings. To identify the available evaluation tools that assess the handover of critical patients in urgent and emergency care settings in addition to evaluations of their psychometric properties, a systematic review was carried out using PubMed, Scopus, Cinahl, Web of Science (WoS), and PsycINFO, in accordance with PRISMA guidelines. The quality of the studies was assessed using the COSMIN checklist. Finally, eight articles were identified, of which only three included validated tools for evaluating the handover of critical patients in emergency care. Content validity, construct validity, and internal consistency were the most studied psychometric properties. Three studies evaluated error and reliability, criterion validity, hypothesis testing, and sensitivity. None of them considered cross-cultural adaptation or the translation process. This systematic psychometric review shows the existing ambiguities in the handover of critically ill patients and the scarcity of validated evaluation tools. For all of these reasons, we consider it necessary to further investigate urgent care and emergency handover settings through the design and validation of an assessment tool. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

Purpose: Endovascular thrombectomy (EVT) is the standard of care for acute ischaemic stroke (AIS) caused by large vessel occlusion (LVO). Reducing stroke symptom onset to reperfusion time has been shown to be associated with improved functional outcomes. In this study we aimed to develop a computational model to predict and identify time-related outcomes of community stroke calls within an area based on variable parameters. Methods and Materials: A model to simulate and predict EVT service delivery at capable hospital within a geographic area, city or state was designed using Simply, a Python based discrete event simulation framework. Geolocation data defined by the user as well as that used by the model is sourced using the Google Maps Application Programming Interface (API) and GeoPy. Variables are customized by the user based on their local environment to predict time from the community stroke call to cerebral reperfusion using appropriate data. Result(s): This algorithm can predict the delay between the time that emergency services are notified of a potential stroke and cerebral reperfusion using EVT at capable hospital. Factors including area size and population, number of EVT capable hospitals within the area, number of available angiography machines, availability of ambulances and time of patient transfer between EVT centres and stroke calls can be adjusted to observe the effect of modifying each parameter input. The potential delays are time to admission and triage at peripheral hospitals, inter-hospital patient transfer and the number and availability of EVT capable hospitals. Conclusion(s): This model, made available as an open source web-based application, provides a mean of predicting resource utilisation and wait times for stroke service delivery planning. By modifying parameter inputs, the delivery and coordination of a stroke service within an area, city or state may be optimised and aid the development of new EVT service protocols.

Objective: To demonstrate the potential of machine learning and capability of natural language processing (NLP) to predict disposition of patients based on triage notes in the ED. Method(s): A retrospective cohort of ED triage notes from St Vincent's Hospital (Melbourne) was used to develop a deep-learning algorithm that predicts patient disposition. Bidirectional Encoder Representations from Transformers, a recent language representation model developed by Google, was utilised for NLP. Eighty percent of the dataset was used for training the model and 20% was used to test the algorithm performance. Ktrain library, a wrapper for TensorFlow Keras, was employed to develop the model. Result(s): The accuracy of the algorithm was 83% and the area under the curve was 0.88. Sensitivity, specificity, precision and F1-score of the algorithm were 72%, 86%, 56% and 63%, respectively. Conclusion(s): Machine learning and NLP can be together applied to the ED triage note to predict patient disposition with a high level of accuracy. The algorithm can potentially assist ED clinicians in early identification of patients requiring admission by mitigating the cognitive load, thus optimises resource allocation in EDs.Copyright © 2020 Australasian College for Emergency Medicine

Background: Endovascular clot retrieval (ECR) is the standard of care for acute ischemic stroke caused by large vessel occlusion. Reducing stroke symptom onset to reperfusion time is associated with improved functional outcomes. This study aims to develop a computational model to predict and identify time-related outcomes of community stroke calls within a geographic area based on variable parameters to support planning and coordination of ECR services. Method(s): A discrete event simulation (DES) model to simulate and predict ECR service was designed using SimPy, a process-based DES framework written in Python. Geolocation data defined by the user, as well as that used by the model, were sourced using the Google Maps application programming interface. Variables were customized by the user on the basis of their local environment to provide more accurate prediction. Result(s): A DES model can estimate the delay between the time that emergency services are notified of a potential stroke and potential cerebral reperfusion using ECR at a capable hospital. Variables can be adjusted to observe the effect of modifying each parameter input. By varying the percentage of stroke patients receiving ECR, we were able to define the levels at which our existing service begins to fail in service delivery and assess the effect of adding centers. Conclusion(s): This novel computational DES model can aid the optimization of delivery of a stroke service within a city, state, or country. By varying geographic, population, and other user-defined inputs, the model can be applied to any location worldwide.Copyright © 2020 Elsevier Inc.

BACKGROUND: The implementation of evidence-based protocols for stroke management in the emergency department (ED) for the appropriate triage, administration of tissue plasminogen activator to eligible patients, management of fever, hyperglycaemia and swallowing, and prompt transfer to a stroke unit were evaluated in an Australian cluster-randomised trial (T3 trial) conducted at 26 emergency departments. There was no reduction in 90-day death or dependency nor improved processes of ED care. We conducted an a priori planned process influential factors that impacted upon protocol uptake. METHOD(S): Qualitative face-to-face interviews were conducted with purposively selected ED and stroke clinicians from two high- and two low-performing intervention sites about their views on factors that influenced protocol uptake. All Trial State Co-ordinators (n = 3) who supported the implementation at the 13 intervention sites were also interviewed. Data were analysed thematically using normalisation process theory as a sensitising framework to understand key findings, and compared and contrasted between interviewee groups. RESULT(S): Twenty-five ED and stroke clinicians, and three Trial State Co-ordinators were interviewed. Three major themes represented key influences on evidence uptake: (i) Readiness to change: reflected strategies to mobilise and engage clinical teams to foster cognitive participation and collective action; (ii) Fidelity to the protocols: reflected that beliefs about the evidence underpinning the protocols impeded the development of a shared understanding about the applicability of the protocols in the ED context (coherence); and (iii) Boundaries of care: reflected that appraisal (reflexive monitoring) by ED and stroke teams about their respective boundaries of clinical practice impeded uptake of the protocols. CONCLUSION(S): Despite initial high 'buy-in' from clinicians, a theoretically informed and comprehensive implementation strategy was unable to overcome s

Background and Purpose-Accurate and rapid detection of anterior circulation large vessel occlusion (LVO) is of paramount importance in patients with acute stroke due to the potentially rapid infarction of at-risk tissue and the limited therapeutic window for endovascular clot retrieval. Hence, the optimal threshold of a new, fully automated software-based approach for LVO detection was determined, and its diagnostic performance evaluated in a large cohort study. Methods-For this retrospective study, data were pooled from: 2 stroke trials, DEFUSE 2 (n=62; 07/08-09/11) and DEFUSE 3 (n=213; 05/17-05/18); a cohort of endovascular clot retrieval candidates (n=82; August 2, 2014-August 30, 2015) and normals (n=111; June 6, 2017-January 28, 2019) from a single quaternary center; and code stroke patients (n=501; January 1, 2017-December 31, 2018) from a single regional hospital. All CTAs were assessed by the automated algorithm. Consensus reads by 2 neuroradiologists served as the reference standard. ROC analysis was used to assess diagnostic performance of the algorithm for detection of (1) anterior circulation LVOs involving the intracranial internal carotid artery or M1 segment middle cerebral artery (M1-MCA); (2) anterior circulation LVOs and proximal M2 segment MCA (M2-MCA) occlusions; and (3) individual segment occlusions. Results-CTAs from 926 patients (median age 70 years, interquartile range: 58-80; 422 females) were analyzed. Three hundred ninety-five patients had an anterior circulation LVO or M2-MCA occlusion (National Institutes of Health Stroke Scale 14 [median], interquartile range: 9-19). Sensitivity and specificity were 97% and 74%, respectively, for LVO detection, and 95% and 79%, respectively, when M2 occlusions were included. On analysis by occlusion site, sensitivities were 90% (M2-MCA), 97% (M1-MCA), and 97% (intracranial internal carotid artery) with corresponding area-under-the-ROC-curves of 0.874 (M2), 0.962 (M1), and 0.997 (intracranial internal ca

Stroke is a complex, time-sensitive, medical emergency that requires well functioning systems of care to optimise treatment and improve patient outcomes. Education and training campaigns are needed to improve both the recognition of stroke among the general public and the response of emergency medical services. Specialised stroke ambulances (mobile stroke units) have been piloted in many cities to speed up the diagnosis, triage, and emergency treatment of people with acute stroke symptoms. Hospital-based interdisciplinary stroke units remain the central feature of a modern stroke service. Many have now developed a role in the very early phase (hyperacute units) plus outreach for patients who return home (early supported discharge services). Different levels (comprehensive and primary) of stroke centre and telemedicine networks have been developed to coordinate the various service components with specialist investigations and interventions including rehabilitation. Major challenges include the harmonisation of resources for stroke across the whole patient journey (including the rapid, accurate triage of patients who require highly specialised treatment in comprehensive stroke centres) and the development of technology to improve communication across different parts of a service.Copyright © 2020 Elsevier Ltd

Background: The Australasian Triage Scale is a clinical tool used to establish the priority for initial treatment of a patient.1 However, the impact of triage assessment to time to first CT from hospital arrival in aneurysmal sub-arachnoid haemorrhage (aSAH) patients is unknown. Aim(s): To examine triage category and time to CT among aSAH patients. Method(s): A retrospective study of confirmed aSAH was undertaken within Tasmania and South East Victoria from 2010-2016. Patients' data were extracted from digital medical records. Triage category is from 1 = immediately life threatening to 5 = less urgent with 3-5 categorised as lower priority. We analysed median (IQR) time (in hours) to CT by triage category using non-parametric K-sample test. Result(s): A total of 586 aSAH cases were included, 56.7% had triage assessment available: 33% category 1, 32% category 2, 28% category 3, 4% category 4, 5% category 5. The median (IQR) time to CT was 1.35 (0.72-2.67) hours with variation by triage category: category 1, 0.95 (0.53-1.8) hours; category 2, 0.83 (0.63-1.67) hours, category 3, 2.63 (1.78-3.79) hours; category 4, 3.55 (2.37-5.03) hours; category 5, 1.35 (0.63-3.38) hours. Patients with lower priority categories had significant longer time to CT (2.52 h, IQR 1.62-3.8) than patients in higher priority categories (0.93 h, IQR 0.6-1.78); P < 0.0001. Conclusion(s): Around 30% of people presenting with aSAH were triaged in lower priority, leading to longer time to CT. This time to CT is much longer than the time recommended for ischaemic stroke;2 the reasons for this longer duration should be explored.

Objective: The aim of the present study was to perform a cost-benefit analysis of retrospectively identifying missed compensable billings in a public Australian ED. Method(s): A retrospective review of patients who were eligible for billing from the period of 1 April 2018 to 31 January 2019 was undertaken. Individual patient files were examined and reconciliated with the historical billing record and any discrepancies identified. Financial modelling with Vose ModelRisk and R Studio v1.2.5033 was employed to estimate future benefits of such a strategy. Uncertainty analyses included variation in wage cost (AU$0-200/h), discount rate (3-10%), presentation growth rate, percentage compensable, benefit recovered/patient, percentage recoverable and cost per patient. Result(s): A total of 76 523 patients presented during this time. Of these, 2737 patients were deemed compensable. A total of 740 undocumented billing items were identified with an estimated Medicare Benefits Schedule value of $59 870 and an Australian Medical Association value of $152 400. The net present value (NPV) of this identified cash flow stream in perpetuity was $1 436 892 (Medicare Benefits Schedule) and $3 657 600 (Australian Medical Association) (i.e. the total value of recovering this amount of money each year indefinitely, corrected for the time value of money). The positive NPV was maintained with sensitivity analysis. Conclusion(s): All scenarios examined led to a positive NPV favouring retrospectively identifying missed compensable billings.Copyright © 2020 Australasian College for Emergency Medicine

Introduction: Effective, time-critical intervention in acute stroke is crucial to mitigate mortality rate and morbidity, but delivery of reperfusion treatments is often hampered by pre-, in- or inter-hospital system level delays. Disjointed, repetitive and inefficient communication is a consistent contributor to avoidable treatment delay. In the era of rapid reperfusion therapy for ischaemic stroke, there is a need for a communication system to synchronise the flow of clinical information across the entire stroke journey. Material(s) and Method(s): A multi-disciplinary development team designed an electronic communications platform, integrated between web browsers and a mobile application, to link all relevant members of the stroke treatment pathway. The platform uses tiered notifications, geotagging, incorporates multiple clinical score calculators, and is compliant with security regulations. The system safely saves relevant information for audit and research. Result(s): Code Stroke Alert is a platform that can be accessed by emergency medical services (EMS) and hospital staff, coordinating the flow of information during acute stroke care, reducing duplication and error in clinical information handover. Through acceleration of the numerous and complex logistical processes required to achieve reperfusion, Code Stroke Alert offers substantial potential benefit to improve patient outcome. Electronic data logs provide an auditable trail of relevant quality improvement metrics, facilitating quality improvement and research. Discussion(s): Code Stroke Alert will be freely available to health networks globally. The open-source nature of the software offers valuable potential for future development of plug-ins and add-ons, based on individual institutional needs. Prospective, multi-site implementation and measurement of clinical impact are underway.

Background and Purpose-Mobile stroke units (MSUs) are increasingly used worldwide to provide prehospital triage and treatment. The benefits of MSUs in giving earlier thrombolysis have been well established, but the impacts of MSUs on endovascular thrombectomy (EVT) and effect on disability avoidance are largely unknown. We aimed to determine the clinical impact and disability reduction for reperfusion therapies in the first operational year of the Melbourne MSU. Methods-Treatment time metrics for MSU patients receiving reperfusion therapy were compared with control patients presenting to metropolitan Melbourne stroke units via standard ambulance within MSU operating hours. The primary outcome was median time difference in first ambulance dispatch to treatment modeled using quantile regression analysis. Time savings were subsequently converted to disability-adjusted life years avoided using published estimates. Results-In the first 365-day operation of the Melbourne MSU, prehospital thrombolysis was administered to 100 patients (mean age, 73.8 years; 62% men). The median time savings per MSU patient, compared with the control cohort, was 26 minutes (P<0.001) for dispatch to hospital arrival and 15 minutes (P<0.001) for hospital arrival to thrombolysis. The calculated overall time saving from dispatch to thrombolysis was 42.5 minutes (95% CI, 36.0-49.0). In the same period, 41 MSU patients received EVT (mean age, 76 years; 61% men) with median dispatch-to-treatment time saving of 51 minutes ([95% CI, 30.1-71.9], P<0.001). This included a median time saving of 17 minutes ([95% CI, 7.6-26.4], P=0.001) for EVT hospital arrival to arterial puncture for MSU patients. Estimated median disability-adjusted life years saved through earlier provision of reperfusion therapies were 20.9 for thrombolysis and 24.6 for EVT. Conclusions-The Melbourne MSU substantially reduced time to reperfusion therapies, with the greatest estimated disability avoidance driven by the more powerful i

The aim of the present integrative review is to identify and describe risk factors and triggers that may result in patient-initiated violence on inpatient psychiatric units. Original studies were searched for in PubMed, PsycINFO, and the Cumulative Index to Nursing and Allied Health Literature. From the 826 identified publications, 18 were included for a synthesis. The results are presented in three themes, which demonstrate that patient characteristics, staff approach, and the ward environment are influencers that may trigger the emergence of violent incidents. Incidents are discussed from the theoretical framework of complexity science as dynamic, highly variable in manifestation, and adaptive, in that the forthcoming process and outcomes are highly dependent on how the surrounding environment responds. Our recommendation is that staff on inpatient wards recognize the myriad influencers that may trigger inpatient violence in a context of highly complex interactions. © The Author(s) 2019.