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IntroductionTo prevent further vascular events, prescribing of multiple classes of medications (antihypertensive, antithrombotic and lipid-lowering) is recommended in national clinical guidelines following ischaemic stroke. Objectives and ApproachUsing real-world data, we determined the association between optimal combination pharmacotherapy (supply of all three classes, “optimal pharmacotherapy”) and survival after stroke. We linked a cohort of patients with first-ever ischaemic stroke from the Australian Stroke Clinical Registry (2010-2014) with national pharmaceutical dispensing and national mortality data. Cox regression was used to determine associations between pharmacotherapy in the first 30 days of stroke with 1-year (from day 31 to 395) all-cause mortality. All analyses were adjusted for socio-demographic (age, sex) and clinical characteristics (stroke severity, discharge destination). ResultsAmong 6684 patients discharged following first-ever ischaemic stroke (median length-of-stay 5 days), 6466 patients who survived to 30 days were included (44% female, median age 74 years). During the first 30 days from discharge, 71.4% received ≥1 medication class, and 32.9% (n=2125) received optimal pharmacotherapy. Patients with optimal pharmacotherapy were older (≥75 years 50.3% vs

IntroductionRecent advances in Australia mean that it is possible to link national clinical registries with government held administrative datasets. However, formal evaluations of such activities and the potential impact for research are lacking. Objectives and ApproachWe aimed to assess the feasibility and accuracy of linking registrants from the Australian Stroke Clinical Registry (AuSCR) with the Medicare enrolment file. Following data custodian and ethics approvals, personal linkage identifiers were submitted to the Australian Institute of Health and Welfare (AIHW). De-identified data from AuSCR and the AIHW were submitted into the Secure Unified Research Environment and merged using project specific person-based IDs. We calculated the proportion of patients linked with the Medicare enrolment file that were present in the associated Medicare and medication dispensing datasets and the proportion with claims after their date of death. Logistic regression was used to identify factors associated with a non-merged patient. Results17,980 AuSCR registrants (January 2010-July 2014) were submitted for linkage (median age 76 years; 46% female; 67% ischaemic stroke; 16% TIA). Of these, 93% were merged with Medicare (N=16,648) and 95% with subsidised medication dispensing claims data (N=17,079). In those who died, 127 (0.8%) had one or more Medicare claim and 411 (2.4%) had one or more medications dispensed after their death date. Asian born registrants were less likely to be merged with Medicare (adjusted Odds Ratio [aOR]: 0.54; 95% Confidence Interval [CI]: 0.40, 0.72) than Australian born registrants. Those aged ≥85 years were less likely to be merged with Medicare data than those aged

Introduction and PurposeChronic Disease Management (CDM) plans are used by general practitioners to manage chronic diseases such as stroke. However, there is limited evidence that being on these plans improve adherence to secondary prevention medications after stroke. We aimed to assess the association of the duration on a CDM plan in improving adherence to secondary prevention medications following stroke. MethodsAustralian survivors of stroke or transient ischaemic attack were participants from the STAND FIRM trial. Patients were individually linked with claims for CDM plans from Medicare and dispensings of secondary prevention medications from the Pharmaceutical Benefits Scheme. We estimated (1) duration on a CDM plan based on the timing and Medicare items claimed and (2) the proportion of days that patients would have been covered by these medications (PDC), while accounting for deaths and instances of over-supply. Dosage for each quantity of medication was determined by the regularity in which patients returned for a refill. Logistic regression was used to evaluate factors associated with ≥80% adherence, up to 3 years after stroke, for each of antihypertensive, antithrombotic and lipid-modifying drugs. ResultsThe median PDC for 563 patients (median age 70yrs; 36% female) ranged from 92% to 95% among the three classes of medications. Approximately 27% did not take up a CDM plan, 33% were on plans for

IntroductionDespite being recommended in clinical guidelines for secondary prevention of stroke, there are limited real-world data on outcomes associated with use of statins post-stroke. Objectives and ApproachWe aimed to investigate the association between statin use and cardiovascular mortality post-stroke. We conducted a retrospective cohort study using prospectively collected data from the Australian Stroke Clinical Registry (2010-2014), linked with national medication dispensing and mortality data. We observed adult patients with first-ever ischaemic stroke or transient ischaemic attack (TIA) for 1-year following hospital discharge, or until their date of death, whichever occurred first. Statin use, defined as having an available statin dispensing, was assessed daily and treated as a time-varying exposure to account for patients who discontinued or reinitiated statins during follow-up. Multivariable, competing-risks regression, with non-cardiovascular death as the competing risk, was used to investigate the association between statin use and 1-year cardiovascular mortality. ResultsAmong 8363 patients discharged following first-ever ischaemic stroke or TIA (48% aged ≥75 years, 45% female, 20% TIA, median length-of-stay 5 days), 945 died within 1 year, with 763 deaths being cardiovascular-related. The proportion of statin users was 65% at 90 days, 64% at 180 days, and 62% at 1 year. Groups least likely to be statin users at 1-year were women (odds ratio [OR]: 0.75; 95% CI: 0.67-0.85), patients aged

IntroductionThe growing burden of chronic diseases means some governments have been providing financial incentives for multidisciplinary care and self-management support delivered within primary care. Currently, population-based evaluations of the effectiveness of these policies are lacking. AimTo outline the methodological approach for our study that is designed to evaluate the effectiveness (including cost) of primary care policies for chronic diseases in Australia using stroke as a case study. MethodsPerson-level linkages will be undertaken between registrants from the Australian Stroke Clinical Registry (AuSCR) and (i) Government-held Medicare Australia claims data, to identify receipt or not of chronic disease management and care coordination primary care items; (ii) state government-held hospital data, to define outcomes; and (iii) government-held pharmaceutical and aged care claims data, to define covariates. N=1500 randomly selected AuSCR registrants will be sent surveys to obtain patient experience information. In Australia, unique identifiers are unavailable. Therefore, personal-identifiers will be submitted to government data linkage units. Researchers will merge the de-identified datasets for analysis using a project identifier. An economic evaluation will also be undertaken. AnalysisThe index event will be the first stroke recorded in the AuSCR. Multivariable competing risks Poisson regression for multiple events, adjusted by a propensity score, will be used to test for differences in the rates of hospital presentations and medication adherence for different care (policy) types. Our estimated sample size of 25,000 patients will provide 80% estimated power (α >0.05) to detect a 6-8% difference in rates. The incremental costs per Quality-adjusted life years gained of community-based care following the acute event will be estimated from a health sector perspective. ConclusionCompletion of this study will provide a novel and comprehensive evaluation of the effectiveness and cost-effectiveness of Australian primary care policies. Its success will enable us to highlight the value of data-linkage for this type of research.

IntroductionThe global burden of chronic diseases is large and increasing. In response, governments are investing substantial funds in innovative models of primary care, characterised by multidisciplinary care and self-management support for people with chronic conditions. Currently, large scale population-based evaluations of the effectiveness of these policies are lacking. Objectives and ApproachWe aim to evaluate the effectiveness and cost-effectiveness of enhanced primary care policies for chronic diseases funded through Medicare Australia using stroke as a case study. Person-level linkages from the following will be used: Australian Stroke Clinical Registry (AuSCR) to define the cohort; Australian government-held Medicare claims data to identify receipt or not of enhanced primary care items; state government-held hospital data to define outcomes; and Australian government-held pharmaceutical and aged care claims data to define covariates. In Australia, unique identifiers are not used therefore, personal-identifiers will be submitted to data linkage units and content records merged using a Project-ID. ResultsIdentifiers from ~25,000 AuSCR registrants (2012-2016), from Victoria and Queensland will be submitted for linkage. The index event is the first event recorded in the AuSCR. Data applications to state health departments and the Australian Institute of Health and Welfare have commenced. To obtain detailed information on patient’s primary care experience 1,500 randomly selected AuSCR registrants are being sent surveys. Multivariable analyses using a competing risks Poisson regression model for multiple events and adjusted by a propensity score, will be used to test for differences in the rates of hospital presentations. We have power (a >0.05) to detect a ≥6% difference in the number of hospital contacts between those who did and did not receive enhanced primary care. An economic evaluation will also be undertaken. Conclusion/ImplicationsThis is the largest stroke data linkage study in Australia. The breadth of data will provide a comprehensive evaluation of the effectiveness of enhanced primary care policies within “real world” healthcare provision. Methods will advance the use of population data linkage in healthcare evaluation where unique identifiers are unavailable.

IntroductionSurvivors of stroke have complex needs from ongoing disabilities and have increased risk of cardiovascular diseases. The societal costs are therefore substantial. Person-level longitudinal data on the longer-term hospital utilizations of patients with stroke in Australia, and the factors that may influence usage in this setting, are rarely reported. Objectives and ApproachWe used person-level linkages between the Australian Stroke Clinical Registry (AuSCR: 2009-2013) and hospital admission and Emergency Department (ED) data from four states to examine determinants of hospital utilisation following stroke. The index event was the first event recorded in AuSCR. The rate of hospital contacts/person/year was calculated from contacts 30-365 days post-discharge. Disability was determined from responses to EQ-5D-3L data collected at 90-180 days post-stroke. Comorbidities were identified using ICD-10 discharge diagnosis codes (5 year look back including the index event). Negative binomial regression was used adjusting for patient clustering by hospital and pre-stroke contacts and stratified by disability. ResultsAmong 10,082 adults with acute stroke (55% male, median age 74 years, 81% ischaemic, 14% hemorrhagic, 5% undetermined, 44% with disability) from 39 hospitals, 57% had a hospital admission or ED contact in the first 30-365 days post-hospital discharge, with median contacts/person/year post-stroke of 1.09 (Q1, Q3: 0, 3.27) compared to a pre-contact rate of 0 (Q1, Q3: 0, 2.18). The strongest associations with subsequent hospital contacts were prior contacts (IRR:1.10, 95%CI:1.07, 1.13), not able to walk on admission (stroke severity) (IRR:1.19, 95%CI 1.07, 1.31) and having a higher comorbidity index score (IRR:1.18, 95%CI:1.14, 1.22). Within stratified cohorts younger age was associated with increased contacts in those with disability ( Conclusion/ImplicationsIn a large linked cohort of patients we have demonstrated the substantial ongoing burden that stroke imposes on hospital systems, particularly regarding survivors with other comorbidities and younger survivors with disability. Knowledge of disability and comorbidity burden may assist with targeting community and hospital interventions to reduce post-stroke hospital usage.

IntroductionRecent advances in data linkage infrastructure in Australia mean that data can be linked based on various identifiers across datasets. In a first for Australia, we tested the feasibility of linking data between a clinical quality disease registry with Australian and state government health data across multiple jurisdictions. Objectives and ApproachTo determine whether high quality linked data for stroke can be obtained using a non-government managed registry (Australian Stroke Clinical Registry, AuSCR), national death registry data (Australian government), and hospital admission and emergency presentation data (state governments) to assess the accuracy of consistent variables across the different datasets. We used a cohort design with probabilistic data linkage to merge patient-level records. Descriptive statistics presented for matching concordance and Cohen’s kappa for concordance across demographic variables. The sensitivity and specificity of in-hospital deaths collected in the AuSCR was assessed against national death registrations. ResultsThere were 16,214 registrants in the study cohort. Their identifiers in the AuSCR from 2009-2013 were linked with death, emergency department and hospital discharge data from April 2004 to December 2016. In total, 99% of the AuSCR registrants were linked to one or more datasets; 98\% were linked with emergency presentation (80%) and/or admission (95%) data. Linkage to national death registrations identified 4,183 death; 1440 of these were identified as in-hospital deaths in both data sets demonstrating that in-hospital death classification in AuSCR had a 98.7% sensitivity and 99.6% specificity. Concordance between common demographic variables was excellent (kappa 0.84 for aboriginal status and kappa 0.99 for sex). Conclusion/ImplicationsThe majority of AuSCR registrants were accurately linked to the Australian and state government datasets. Linkage quality was excellent and there was high concordance between common variables. The ability to reliably merge the datasets assures future comprehensive analyses of stroke care, ongoing health care resource utilisation and patient outcomes.