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Introduction: Despite global concerns about the safety and quality of health care, population-wide studies of hospital outcomes are uncommon. The SAFety, Effectiveness of care and Resource use among Australian Hospitals (SAFER Hospitals) study seeks to estimate the incidence of serious adverse events, mortality, unplanned rehospitalisations and direct costs following hospital encounters using nationwide data, and to assess the variation and trends in these outcomes., Methods and Analysis: SAFER Hospitals is a cohort study with retrospective and prospective components. The retrospective component uses data from 2012 to 2018 on all hospitalised patients age ≥18 years included in each State and Territories' Admitted Patient Collections. These routinely collected datasets record every hospital encounter from all public and most private hospitals using a standardised set of variables including patient demographics, primary and secondary diagnoses, procedures and patient status at discharge. The study outcomes are deaths, adverse events, readmissions and emergency care visits. Hospitalisation data will be linked to subsequent hospitalisations and each region's Emergency Department Data Collections and Death Registries to assess readmissions, emergency care encounters and deaths after discharge. Direct hospital costs associated with adverse outcomes will be estimated using data from the National Cost Data Collection. Variation in these outcomes among hospitals will be assessed adjusting for differences in hospitals' case-mix. The prospective component of the study will evaluate the temporal change in outcomes every 4 years from 2019 until 2030., Ethics and Dissemination: Human Research Ethics Committees of the respective Australian states and territories provided ethical approval to conduct this study. A waiver of informed consent was granted for the use of de-identified patient data. Study findings will be disseminated via presentations at conferences and publications in peer-reviewed journals., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Aims: Acute coronary syndrome (ACS) is a costly condition for health service provision yet variation in the delivery of care between hospitals persists. A composite measure of adherence with evidence-based clinical-process indicators (CPIs) could better inform hospital performance reporting and clinical outcomes in the management of ACS., Methods: Data on 7444 ACS patients from 39 Australian hospitals were used to derive a hospital-specific composite quality score by calculating mean adherence to 14 evidence-based CPIs. Using the generalized estimating equation to account for clustering of patients within hospitals and the GRACE risk score to adjust for differences in presenting risk, we evaluated associations between the hospital-specific composite quality score, in-hospital major adverse events, in-hospital mortality and mortality and readmission for ACS at 6 months., Results: Hospitals had a mean adherence of 68.3% (SD 21.7) with the composite quality score. There was significant variation between hospital adherence tertile 1 (79%) and tertile 3 (56%), P < 0.0001. With risk adjustment, there was an association between hospitals with a higher composite quality score and reduced in-hospital adverse events (OR: 0.85, CI: 0.71-0.99) and survival at hospital discharge (OR: 0.47; 95% CI: 0.28-0.77). There was trending improvement in survival at 6 months (OR 0.48; CI: 0.20-1.16) and fewer readmissions to hospital for ACS at 6 months (OR 0.79; CI 0.60-1.05)., Conclusion: The association between the quality composite score and reduced in-hospital events and survival at hospital discharge supports the utility of reporting CPIs in routine hospital performance reporting on the management of ACS., Australia and New Zealand Clinical Trial Registration (anzctr): CONCORDANCE Registry ACTRN12614000887673., (Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2016. For permissions please email: journals.permissions@oup.com.)

Objective. Effective translation of evidence to practice may depend on systems of care characteristics within the health service. The present study evaluated associations between hospital expertise and infrastructure capacity and acute coronary syndrome (ACS) care as part of the SNAPSHOT ACS registry. Methods. A survey collected hospital systems and process data and our analysis developed a score to assess hospital infrastructure and expertise capacity. Patient-level data from a registry of 4387 suspected ACS patients enrolled over a 2-wee Results. Of 375 participating hospitals, 348 (92.8%) were included in the analysis. Higher expertise was associated with increased coronary angiograms (440/1329; 33.1%), 580/1656 (35.0%) and 609/1402 (43.4%) for low, intermediate and high expertise capacity respectively; P < 0.001) and the prescription of guideline therapies observed a tendency for an association with (531/1329 (40.0%), 733/1656 (44.3%) and 603/1402 (43.0%) for low, intermediate and high expertise capacity respectively; P = 0.056), but not rehabilitation (474/1329 (35.7%), 603/1656 (36.4%) and 535/1402 (38.2%) for low, intermediate and high expertise capacity respectively; P = 0.377). Higher expertise capacity was associated with a lower incidence of major adverse events (152/1329 (11.4%), 142/1656 (8.6%) and 149/149 (10.6%) for low, intermediate and high expertise capacity respectively; P = 0.026), as well as adjusted mortality within 18 months (low vs intermediate expertise capacity: odds ratio (OR) 0.79, 95% confidence interval (CI) 0.58-1.08, P = 0.153; intermediate vs high expertise capacity: OR 0.64, 95% CI 0.48-0.86, P = 0.003). Conclusions. Both higher-level expertise in decision making and infrastructure capacity are associated with improved evidence translation and survival over 18 months of an ACS event and have clear healthcare design and policy implications. [ABSTRACT FROM AUTHOR]