The aim of this study was to investigate regional variation in the characteristics, incidence and outcomes of out-of-hospital cardiac arrest (OHCA) in Australia and New Zealand. This was a population-based cohort study of OHCA using data from the Aus-ROC Australian and New Zealand OHCA Epistry over the period of 01 January 2015-31 December 2015. Seven ambulance services contributed data to the Epistry with a capture population of 19.8 million people. All OHCA attended by ambulance, regardless of aetiology or patient age, were included. In 2015, there were 19,722 OHCA cases recorded in the Aus-ROC Epistry with an overall crude incidence of 102.5 cases per 100,000 population (range: 51.0-107.7 per 100,000 population). Of all OHCA cases attended by EMS (excluding EMS-witnessed cases), bystander CPR was performed in 41% of cases (range: 36%-50%). Resuscitation was attempted (by EMS) in 48% of cases (range: 40%-68%). The crude incidence for attempted resuscitation cases was 47.6 per 100,000 population (range: 34.7-54.1 per 100,000 population). Of cases with attempted resuscitation, 28% survived the event (range: 21%-36%) and 12% survived to hospital discharge or 30 days (range: 9%-17%; data provided by five ambulance services). In the first results of the Aus-ROC Australian and New Zealand OHCA Epistry, significant regional variation in the incidence, characteristics and outcomes was observed. Understanding the system-level and public health drivers of this variation will assist in optimisation of the chain of survival provided to OHCA patients with the aim of improving outcomes.

While noting the importance of data quality, existing process mining methodologies (i) do not provide details on how to assess the quality of event data (ii) do not consider how the identification of data quality issues can be exploited in the planning, data extraction and log building phases of any process mining analysis, (iii) do not highlight potential impacts of poor quality data on different types of process analyses. As our key contribution, we develop a process-centric, data quality-driven approach to preparing for a process mining analysis which can be applied to any existing process mining methodology. Our approach, adapted from elements of the well known CRISP-DM data mining methodology, includes conceptual data modeling, quality assessment at both attribute and event level, and trial discovery and conformance to develop understanding of system processes and data properties to inform data extraction. We illustrate our approach in a case study involving the Queensland Ambulance Service (QAS) and Retrieval Services Queensland (RSQ). We describe the detailed preparation for a process mining analysis of retrieval and transport processes (ground and aero-medical) for road-trauma patients in Queensland. Sample datasets obtained from QAS and RSQ are utilised to show how quality metrics, data models and exploratory process mining analyses can be used to (i) identify data quality issues, (ii) anticipate and explain certain observable features in process mining analyses, (iii) distinguish between systemic and occasional quality issues, and (iv) reason about the mechanisms by which identified quality issues may have arisen in the event log. We contend that this knowledge can be used to guide the data extraction and pre-processing stages of a process mining case study to properly align the data with the case study research questions.

The number of people presenting to EDs with mental health problems is increasing. To enhance and promote the delivery of safe and efficient healthcare to this group, there is a need to identify evidence‐based, best‐practice models of care. This scoping review aims to identify and evaluate current research on interventions commenced or delivered in the ED for people presenting with a mental health problem. A systematic search of eight databases using search terms including emergency department, mental health, psyc* and interventions, with additional reference chaining, was undertaken. For included studies, level of evidence was assessed using the NHMRC research guidelines and existing knowledge was synthesised to map key concepts and identify current research gaps. A total of 277 papers met the inclusion criteria. These were grouped thematically into seven domains based on primary intervention type: pharmacological (n = 43), psychological/behavioural (n = 25), triage/assessment/screening (n = 28), educational/informational (n = 12), case management (n = 28), referral/follow up (n = 36) and mixed interventions (n = 105). There was large heterogeneity observed as to the level of evidence within each intervention group. The interventions varied widely from pharmacological to behavioural. Interventions were focused on either staff, patient or institutional process domains. Few interventions focused on multiple domains (n = 64) and/or included the patient's family (n = 1). The effectiveness of interventions varied. There is considerable, yet disconnected, evidence around ED interventions to support people with mental health problems. A lack of integrated, multifaceted, person‐centred interventions is an important barrier to providing effective care for this vulnerable population who present to the ED.

Introduction Out-of-hospital cardiac arrest (OHCA) is a global health problem with low survival. Regional variation in survival has heightened interest in combining cardiac arrest registries to understand and improve OHCA outcomes. While individual OHCA registries exist in Australian and New Zealand ambulance services, until recently these registries have not been combined. The aim of this protocol paper is to describe the rationale and methods of the Australian Resuscitation Outcomes Consortium (Aus-ROC) OHCA epidemiological registry (Epistry). Methods and analysis The Aus-ROC Epistry is designed as a population-based cohort study. Data collection started in 2014. Six ambulance services in Australia (Ambulance Victoria, SA Ambulance Service, St John Ambulance Western Australia and Queensland Ambulance Service) and New Zealand (St John New Zealand and Wellington Free Ambulance) currently contribute data. All OHCA attended by ambulance, regardless of aetiology or patient age, are included in the Epistry. The catchment population is approximately 19.3 million persons, representing 63% of the Australian population and 100% of the New Zealand population. Data are collected using Utstein-style definitions. Information incorporated into the Epistry includes demographics, arrest features, ambulance response times, treatment and patient outcomes. The primary outcome is ‘survival to hospital discharge’, with ‘return of spontaneous circulation’ as a key secondary outcome. Ethics and dissemination Ethics approval was independently sought by each of the contributing registries. Overarching ethics for the Epistry was provided by Monash University HREC (Approval No. CF12/3938—2012001888). A population-based OHCA registry capturing the majority of Australia and New Zealand will allow risk-adjusted outcomes to be determined, to enable benchmarking across ambulance providers, facilitate the identification of system-wide strategies associated with survival from OHCA, and allow monitoring of temporal trends in process and outcomes to improve patient care. Findings will be shared with participating ambulance services and the academic community.