Background In 2018, the World Health Organization prioritized control of acute rheumatic fever (ARF) and rheumatic heart disease (RHD), including disease surveillance. We developed strategies for estimating contemporary ARF/RHD incidence and prevalence in Australia (2015–2017) by age group, sex, and region for Indigenous and non‐Indigenous Australians based on innovative, direct methods. Methods and Results This population‐based study used linked administrative data from 5 Australian jurisdictions. A cohort of ARF (age <45 years) and RHD cases (<55 years) were sourced from jurisdictional ARF/RHD registers, surgical registries, and inpatient data. We developed robust methods for epidemiologic case ascertainment for ARF/RHD. We calculated age‐specific and age‐standardized incidence and prevalence. Age‐standardized rate and prevalence ratios compared disease burden between demographic subgroups. Of 1425 ARF episodes, 72.1% were first‐ever, 88.8% in Indigenous people and 78.6% were aged <25 years. The age‐standardized ARF first‐ever rates were 71.9 and 0.60/100 000 for Indigenous and non‐Indigenous populations, respectively (age‐standardized rate ratio=124.1; 95% CI, 105.2–146.3). The 2017 Global Burden of Disease RHD prevalent counts for Australia (<55 years) underestimate the burden (1518 versus 6156 Australia‐wide extrapolated from our study). The Indigenous age‐standardized RHD prevalence (666.3/100 000) was 61.4 times higher (95% CI, 59.3–63.5) than non‐Indigenous (10.9/100 000). Female RHD prevalence was double that in males. Regions in northern Australia had the highest rates. Conclusions This study provides the most accurate estimates to date of Australian ARF and RHD rates. The high Indigenous burden necessitates urgent government action. Findings suggest RHD may be underestimated in many high‐resource settings. The linked data methods outlined here have potential for global applicability.

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, MBBS, DPhil (Oxon), FRACP, FAFPHM Background-The incidence of myocardial infarction has declined during the past 4 decades in many populations.However, there are limited population data measuring trends in acute coronary syndromes (ACS). We therefore examined temporal trends in the incidence of hospitalized ACS by age and sex in a population-based cohort. Methods and Results-The Western Australian Data Linkage System, a repository of linked administrative health data, was used to identify 29 421 incident ACS hospitalizations between 1996 and 2007. Poisson log-linear regression models were used to calculate incidence rate changes. Age-standardized incidence rates of ACS declined annually in men by 1.7% (95% confidence interval [CI], Ϫ2.1 to Ϫ1.3) and in women by 1.6% (95% CI, Ϫ2.1 to Ϫ1.0). These declining rates were underpinned by annual reductions in the incidence of unstable angina (men, Ϫ3.0%; 95% CI, Ϫ3.7 to Ϫ2.4; women, Ϫ2.5; 95% CI, Ϫ3.3 to Ϫ1.7), whereas annual changes in myocardial infarction incidence were less (men, Ϫ1.0%; 95% CI, Ϫ1.5 to Ϫ0.5; women, Ϫ0.8%; 95% CI, Ϫ1.6 to 0). However, the overall trends masked age group differences, with ACS incidence increasing annually in 35-to 54-year-old women (2.3%; 95% CI, 1.0 to 3.8), predominantly driven by increasing incidence of myocardial infarction. Conclusions-The age-standardized incidence of ACS decreased significantly in Western Australia from 1996 to 2007. However, an increase in ACS incidence in women ages 35 to 54 years is troubling and warrants further investigation. (Circ Cardiovasc Qual Outcomes. 2011;4:557-564.)

ObjectiveTo examine the feasibility of applying the International Classification of Diseases-perinatal mortality (ICD-PM) coding to an existing data set in the classification of perinatal deaths.MethodsOne author, a researcher with a non-clinical public health background, applied the ICD-PM coding system to South Africa’s national perinatal mortality audit system, the Perinatal Problem Identification Program. The database for this study included all perinatal deaths (n = 26 810), defined as either stillbirths (of birth weight > 1000 g and after 28 weeks of gestation) or early neonatal deaths (age 0–7 days), that occurred between 1 October 2013 and 31 December 2016. A clinical obstetrician verified the coding.FindingsThe South African classification system does not include the timing of death; however, under the ICD-PM system, deaths could be classified as antepartum (n = 15 619; 58.2%), intrapartum (n = 3725; 14.0%) or neonatal (n = 7466; 27.8%). Further, the South African classification system linked a maternal condition to only 40.3% (10 802/26 810) of all perinatal deaths; this proportion increased to 68.9% (18 467/26 810) under the ICD-PM system.ConclusionThe main benefit of using the clinically relevant and user-friendly ICD-PM system was an enhanced understanding of the data, in terms of both timing of death and maternal conditions. We have also demonstrated that it is feasible to convert an existing perinatal mortality classification system to one which is globally comparable and can inform policy-makers internationally.

BackgroundElectronic health care data contain rich information on medicine use from which adherence can be estimated. Various measures developed with medication claims data called for transparency of the equations used, predominantly because they may overestimate adherence, and even more when used with multiple medications. We aimed to operationalize a novel calculation of adherence with polypharmacy, the daily polypharmacy possession ratio (DPPR), and validate it against the common measure of adherence, the medication possession ratio (MPR) and a modified version (MPRm).MethodsWe used linked health data from the Australian Pharmaceutical Benefits Scheme and Western Australian hospital morbidity dataset and mortality register. We identified a strict study cohort from 16,185 patients aged ≥65 years hospitalized for myocardial infarction in 2003–2008 in Western Australia as an illustrative example. We applied iterative exclusion criteria to standardize the dispensing histories according to previous literature. A SAS program was developed to calculate the adherence measures accounting for various drug parameters.ResultsThe study cohort was 348 incident patients (mean age 74.6±6.8 years; 69% male) with an admission for myocardial infarction who had cardiovascular medications over a median of 727 days (range 74 to 3,798 days) prior to readmission. There were statins (96.8%), angiotensin converting enzyme inhibitors (88.8%), beta-blockers (85.6%), and angiotensin receptor blockers (13.2%) dispensed. As expected, observed adherence values were higher with mean MPR (median 89.2%; Q1: 73.3%; Q3: 104.6%) than mean MPRm (median 82.8%; Q1: 68.5%; Q3: 95.9%). DPPR values were the most narrow (median 83.8%; Q1: 70.9%; Q3: 96.4%). Mean MPR and DPPR yielded very close possession values for 37.9% of the patients. Values were similar in patients with longer observation windows. When the traditional threshold of 80% was applied to mean MPR and DPPR values to signify the threshold for good adherence, 11.6% of patients were classified as good adherers with the mean MPR relative to the DPPR.ConclusionIn the absence of transparent and standardized equations to calculate adherence to polypharmacy from refill databases, the novel DPPR algorithm represents a valid and robust method to estimate medication possession for multi-medication regimens.

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Objectives To assess the risks of stroke and cardiovascular mortality for Aboriginal and non‐Aboriginal Australians with atrial fibrillation. Design Retrospective data linkage cohort study. Setting, participants All people aged 20–84 years hospitalised with atrial fibrillation in Western Australia during 2000–2012. Main outcome measures Stroke incidence rates and mortality after hospitalisation for atrial fibrillation, and 10‐year risks of stroke and of cardiovascular and all‐cause mortality. Results Among 55 482 index admissions with atrial fibrillation, 7.7% of 20–59‐year‐old patients and 1.3% of 60–84‐year‐old patients were Aboriginal Australians. A larger proportion of Aboriginal patients aged 20–59 years had CHA2DS2‐VASc scores of 2 or more (59.8% v 21.8%). In 20–59‐year‐old Aboriginal patients, the incidence during follow‐up (maximum, 10 years; median, 7.1 years) of stroke (incidence rate ratio [IRR], 3.2; 95% CI, 2.5–4.1) and fatal stroke (IRR, 5.7; 95% CI, 3.9–8.9) were markedly higher than for non‐Aboriginal patients. Stroke incidence was higher for 60–84‐year‐old patients, but the difference between Aboriginal and non‐Aboriginal patients was smaller (IRR, 1.6; 95% CI, 1.3–2.0). Cardiovascular mortality during follow‐up was also higher for 20–59‐year‐old Aboriginal patients (IRR, 4.4; 95% CI, 4.3–5.9). The hazards of stroke (adjusted HR [aHR], 1.67; 95% CI, 1.22–2.28) and cardiovascular mortality (aHR, 1.47; 95% CI, 1.18–1.83) in younger Aboriginal patients remained significantly higher after multivariable adjustment; age/sex, principal diagnosis of atrial fibrillation, and CHA2DS2‐VASc score were the most influential factors. Conclusion Stroke risk and cardiovascular mortality are markedly higher for Aboriginal than non‐Aboriginal patients with atrial fibrillation, particularly for patients under 60. Strategies for providing evidence‐based therapies and cardiovascular prevention to Aboriginal people with atrial fibrillation must be improved.

The age-specific decline in fatal and non-fatal first CHD rates in older men and women was not observed in those aged 35-54 years. These novel findings provide evidence for a levelling in the CHD incidence rates in younger adults and puts renewed importance on primary prevention in this group.