Objective: To describe hospitalisation rates following COVID-19 infection in NSW. Design, setting and participants: Analysis of all confirmed COVID-19 cases diagnosed in NSW from 1 January to 31 May 2020 extracted from the NSW Notifiable Conditions Information Management System and linked to routinely collected hospitalisation data. Outcome measures: In-patient hospitalisations and hospital service utilisation details. Results: There were 3,101 COVID-19 cases diagnosed between 1 January and 31 May 2020 in NSW: mean age 46.7 years, 50.5% were females. Overall, 12.5% (n = 389) had a record of inpatient hospitalisation, 4.2% (n = 130) were admitted to ICU and 1.9% (n = 58) received ventilation. Among adult cases, hospital and ICU admission rates increased with increasing age: 2.9% of those aged 20–29 years were hospitalised, increasing to 46.6% of those aged 80–89 years; 0.6% of those aged 20–29 years were admitted to ICU, increasing to 11.2% of those aged 70–79 years. The median time from symptoms to hospitalisation was seven days (IQR 4–11). The median time in hospital was nine days (IQR 4–20), and in ICU six days (IQR 2–15); the median time in hospital increased with older age. Almost half (49.4%) of those hospitalised with a diagnostic code had pneumonia/lower respiratory tract infection and another 36.6% had an upper respiratory tract infection or other known COVID-19 symptoms. Conclusion: COVID-19 is a serious infection particularly in older adults. During January to May of 2020, 1 in 8 of those diagnosed in NSW were hospitalised. While this partly reflects the cautious approach to case management in the initial phase of the pandemic, it also demonstrates the large potential impact of COVID-19 on Australian health services and need for continuing mitigation strategies.

IntroductionPeople with end-stage kidney disease (ESKD) have up to 30-fold higher risk of stroke than the general population.ObjectiveTo determine risk factors associated with stroke death in the ESKD population.MethodsWe identified all patients with incident ESKD in Australia (1980–2013) and New Zealand (1988–2012) from the Australian and New Zealand Dialysis and Transplant Registry (ANZDATA) registry. We ascertained underlying cause of death from data linkage with national death registries and risk factors from ANZDATA. Using a competing risks multivariable regression model, we estimated cumulative incidence of stroke and non-stroke deaths, and risk factors for stroke deaths (adjusted sub-HR, SHR).ResultsWe included 60 823 people with ESKD. There were 941 stroke deaths and 33 377 non-stroke deaths during 381 874 person-years of follow-up. Overall, the cumulative incidence of stroke death was 0.9% and non-stroke death was 36.8% 5 years after starting ESKD treatment. The risk of stroke death was higher at older ages (SHR 1.92, 95% CI 1.45 to 2.55), in females (SHR 1.41, 95% CI 1.21 to 1.64), in people with cerebrovascular disease (SHR 2.39, 95% CI 1.99 to 2.87), with ESKD caused by hypertensive/renovascular disease (SHR 1.39, 95% CI 1.09 to 1.78) or polycystic kidney disease (SHR 1.38, 95% CI 1.00 to 1.90), with earlier year of ESKD treatment initiation (SHR 1.93, 95% CI 1.56 to 2.39) and receiving dialysis (transplant vs haemodialysis SHR 0.27, 95% CI 0.09 to 0.84).ConclusionPatients with ESKD with higher risk of stroke death are older, women, with cerebrovascular disease, with hypertensive/renovascular or polycystic kidney disease cause of ESKD, with earlier year of ESKD treatment and receiving dialysis. These groups may benefit from targeted stroke prevention interventions.

IntroductionThe patient journey for residents of New South Wales (NSW) Australia with ST-elevation myocardial infarction (STEMI) often involves transfer between hospitals and these can include stays in hospitals in other jurisdictions. ObjectiveTo estimate the change in enumeration of STEMI hospitalisations and time to subsequent cardiac procedures for NSW residents using cross-jurisdictional linkage of administrative health data. MethodsRecords for NSW residents aged 20 years and over admitted to hospitals in NSW and four adjacent jurisdictions (Australian Capital Territory, Queensland, South Australia, and Victoria) between 1 July 2013 and 30 June 2018 with a principal diagnosis of STEMI were linked with records of the Australian Government Medicare Benefits Schedule (MBS). The number of STEMI hospitalisations, and rates of angiography, percutaneous coronary intervention and coronary artery bypass graft were compared for residents of different local health districts within NSW with and without inclusion of cross-jurisdictional data. ResultsInclusion of cross-jurisdictional hospital and MBS data increased the enumeration of STEMI hospitalisations for NSW residents by 8% (from 15,420 to 16,659) and procedure rates from 85.6% to 88.2%. For NSW residents who lived adjacent to a jurisdictional border, hospitalisation counts increased by up to 210% and procedure rates by up to 70 percentage points. ConclusionsCross-jurisdictional linked hospital data is essential to understand patient journeys of NSW residents who live in border areas and to evaluate adherence to treatment guidelines for STEMI. MBS data are useful where hospital data are not available and for procedures that may be conducted in out-patient settings.

Background For patients experiencing acute myocardial infarction (AMI), particularly ST-elevation myocardial infarction (STEMI), timely revascularisation is important to optimise prognosis. The AMI patient journey often involves presentation to the closest appropriate facility and transfers between hospitals, including across jurisdictions. The Better Cardiac Care (BCC) dataset consists of cross-jurisdictional linked ambulance, emergency, hospital, outpatient, deaths, Medicare and Pharmaceutical Benefits Scheme records for residents of New South Wales (NSW), Australia. This dataset will be updated annually. Methods The BCC dataset comprises 332 million records, from 18 datasets, across 6 jurisdictions. For NSW residents hospitalised for STEMI between 2013 to 2018, we compared the number of STEMI hospitalisations, the proportion of patients receiving revascularisation procedures, and the time to procedures using only NSW records versus records from all jurisdictions and Medicare Benefits Scheme. Results Compared with NSW hospital data, including data from other jurisdictions increased the ascertainment of STEMI hospitalisations by 8.0% and procedures by 11.2% for NSW residents. This increase was greatest for residents living near state borders, increasing the number of STEMI hospitalisations by up to 210% and the percentage receiving procedures by up to 70%. Conclusions Cross-jurisdictional data is essential to understand patient journeys of residents who live in border areas and to evaluate patient care for STEMI and AMI more broadly. Key messages The BCC dataset is a vital asset that enables a more comprehensive view of care for AMI than has been possible to date.

ObjectivesThe BCC project aims to describe the burden of acute myocardial infarction (AMI) and access to cardiac procedures and care for New South Wales (NSW), Australia residents. For patients experiencing AMI, particularly ST-elevation myocardial infarction (STEMI), timely revascularisation is important to optimise prognosis. ApproachThe AMI patient journey often involves presentation to the closest appropriate facility and transfers between hospitals, including across jurisdictions. The BCC dataset consists of cross-jurisdictional linked ambulance, emergency, hospital, outpatient, deaths, Medicare and Pharmaceutical Benefits Scheme records for residents of NSW. For NSW residents hospitalised for STEMI between 2013 to 2018, we compared the number of STEMI hospitalisations, the proportion of patients receiving revascularisation procedures, and the time to procedures using only NSW records versus records from all jurisdictions and Medicare Benefits Scheme. This dataset will be updated annually. ResultsThe BCC dataset comprises 332 million records, from 18 datasets, across 6 jurisdictions. Compared with NSW hospital data, including data from other jurisdictions increased the ascertainment of STEMI hospitalisations by 8.0% (from 15,420 to 16,659) and procedures by 11.2% (from 13,219 to 14,701) for NSW residents. This increase was greatest for residents living near state borders, increasing the number of STEMI hospitalisations by up to 210% and the percentage receiving procedures by up to 70%. ConclusionsCross-jurisdictional data is essential to understand patient journeys of residents who live in border areas and to evaluate patient care for STEMI and AMI more broadly. The BCC dataset is a vital asset that enables a more comprehensive view of care for AMI than has been possible to date.