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To our knowledge, the adoption of Learning Health System (LHS) concepts or approaches for improving stroke care, patient outcomes, and value have not previously been summarized. This topical review provides a summary of the published evidence about LHSs applied to stroke, and case examples applied to different aspects of stroke care from high and low-to-middle income countries. Our attempt to systematically identify the relevant literature and obtain real-world examples demonstrated the dissemination gaps, the lack of learning and action for many of the related LHS concepts across the continuum of care but also elucidated the opportunity for continued dialogue on how to study and scale LHS advances. In the field of stroke, we found only a few published examples of LHSs and health systems globally implementing some selected LHS concepts, but the term is not common. A major barrier to identifying relevant LHS examples in stroke may be the lack of an agreed taxonomy or terminology for classification. We acknowledge that health service delivery settings that leverage many of the LHS concepts do so operationally and the lessons learned are not shared in peer-reviewed literature. It is likely that this topical review will further stimulate the stroke community to disseminate related activities and use keywords such as learning health system so that the evidence base can be more readily identified.

Background: Real-world evidence is limited on whether antihypertensive medications help avert major adverse cardiovascular events (MACE) after stroke without increasing the risk of falls. We investigated the association of adherence to antihypertensive medications on the incidence of MACE and falls requiring hospitalization after stroke. Methods: A retrospective cohort study of adults who were newly dispensed antihypertensive medications after an acute stroke (Australian Stroke Clinical Registry 2012–2016; Queensland and Victoria). Pharmaceutical dispensing records were used to determine medication adherence according to the proportion of days covered in the first 6 months poststroke. Outcomes between 6 and 18 months postdischarge included: (i) MACE, a composite outcome of all-cause death, recurrent stroke or acute coronary syndrome; and (ii) falls requiring hospitalization. Estimates were derived using Cox models, adjusted for >30 confounders using inverse probability treatment weights. Results: Among 4076 eligible participants (median age 68 years; 37% women), 55% had a proportion of days covered ≥80% within 6 months postdischarge. In the subsequent 12 months, 360 (9%) participants experienced a MACE and 337 (8%) experienced a fall requiring hospitalization. After achieving balance between groups, participants with a proportion of days covered ≥80% had a reduced risk of MACE (hazard ratio: 0.68; 95% CI: 0.54–0.84) and falls requiring hospitalization (subdistribution hazard ratio: 0.78; 95% CI: 0.62–0.98) than those with a proportion of days covered Conclusions: High adherence to antihypertensive medications within 6 months poststroke was associated with reduced risks of both MACE and falls requiring hospitalization. Patients should be encouraged to adhere to their antihypertensive medications to maximize poststroke outcomes.

Knowledge about stroke and its management is growing rapidly and stroke systems of care must adapt to deliver evidence-based care. Quality improvement initiatives are essential for translating knowledge from clinical trials and recommendations in guidelines into routine clinical practice. This review focuses on issues central to the measurement of the quality of stroke care, including selection and definition of quality measures, identification of the eligible patient cohorts, optimization of data quality, and considerations for data analysis and interpretation.

Despite digital health tools being popular for supporting self-management of chronic diseases, little research has been undertaken on stroke. We developed and pilot tested, using a randomized controlled design, a multicomponent digital health programme, known as Inspiring Virtual Enabled Resources following Vascular Events (iVERVE), to improve self-management after stroke. The 4-week trial incorporated facilitated person-centred goal setting, with those in the intervention group receiving electronic messages aligned to their goals, versus limited administrative messages for the control group. In this paper, we describe the participant experience of the various components involved with the iVERVE trial.Mixed method design: satisfaction surveys (control and intervention) and a focus group interview (purposively selected intervention participants). Experiences relating to goal setting and overall trial satisfaction were obtained from intervention and control participants, with feedback on the electronic message component from intervention participants. Inductive thematic analysis was used for interview data and open-text responses, and closed questions were summarized descriptively. Triangulation of data allowed participants' perceptions to be explored in depth.Overall, 27/54 trial participants completed the survey (13 intervention: 52%; 14 control: 48%); and 5/8 invited participants in the intervention group attended the focus group. Goal setting: The approach was considered comprehensive, with the involvement of health professionals in the process helpful in developing realistic, meaningful and person-centred goals. Electronic messages (intervention): Messages were perceived as easy to understand (92%), and the frequency of receipt was considered appropriate (11/13 survey; 4/5 focus group). The content of messages was considered motivational (62%) and assisted participants to achieve their goals (77%). Some participants described the benefits of receiving messages as a 'reminder' to act. Overall trial satisfaction: Messages were acceptable for educating about stroke (77%). Having options for short message services or email to receive messages was considered important. Feedback on the length of the intervention related to specific goals, and benefits of receiving the programme earlier after stroke was expressed.The participant experience has indicated acceptance and utility of iVERVE. Feedback from this evaluation is invaluable to inform refinements to future Phase II and III trials, and wider research in the field.Two consumer representatives sourced from the Stroke Foundation (Australia) actively contributed to the design of the iVERVE programme. In this study, participant experiences directly contributed to the further development of the iVERVE intervention and future trial design.

Although medication adherence is commonly measured in electronic datasets using the proportion of days covered (PDC), no standardized approach is used to calculate and report this measure. We conducted a scoping review to understand the approaches taken to calculate and report the PDC for cardiovascular medicines to develop improved guidance for researchers using this measure. After prespecifying methods in a registered protocol, we searched Ovid Medline, Embase, Scopus, CINAHL Plus and grey literature (1 July 2012 to 14 December 2020) for articles containing the terms "proportion of days covered" and "cardiovascular medicine", or synonyms and subject headings. Of the 523 articles identified, 316 were reviewed in full and 76 were included (93% observational studies; 47% from the USA; 2 grey literature articles). In 45 articles (59%), the PDC was measured from the first dispensing/claim date. Good adherence was defined as 80% PDC in 61 articles, 56% of which contained a rationale for selecting this threshold. The following parameters, important for deriving the PDC, were often not reported/unclear: switching (53%), early refills (45%), in-hospital supplies (45%), presupply (28%) and survival (7%). Of the 46 articles where dosing information was unavailable, 59% reported how doses were imputed. To improve the transparent and systematic reporting of the PDC, we propose the TEN-SPIDERS tool, covering the following PDC parameters: Threshold, Eligibility criteria, Numerator and denominator, Survival, Presupply, In-hospital supplies, Dosing, Early Refills, and Switching. Use of this tool will standardize reporting of the PDC to facilitate reliable comparisons of medication adherence estimates between studies.

Purpose of Review To critically appraise literature on recent advances and methods using “big data” to evaluate stroke outcomes and associated factors. Recent Findings Recent big data studies provided new evidence on the incidence of stroke outcomes, and important emerging predictors of these outcomes. Main highlights included the identification of COVID-19 infection and exposure to a low-dose particulate matter as emerging predictors of mortality post-stroke. Demographic (age, sex) and geographical (rural vs. urban) disparities in outcomes were also identified. There was a surge in methodological (e.g., machine learning and validation) studies aimed at maximizing the efficiency of big data for improving the prediction of stroke outcomes. However, considerable delays remain between data generation and publication. Summary Big data are driving rapid innovations in research of stroke outcomes, generating novel evidence for bridging practice gaps. Opportunity exists to harness big data to drive real-time improvements in stroke outcomes.

Introduction: Observational studies are increasingly being used to provide evidence on the real-world effectiveness of medications for preventing vascular diseases, such as stroke. We investigated whether the real-world effectiveness of treatment with lipid-lowering medications after ischemic stroke is affected by prevalent-user bias. Methods: An observational cohort study of 90-day survivors of ischemic stroke using person-level data from the Australian Stroke Clinical Registry (2012–2016; 45 hospitals) linked to administrative (pharmaceutical, hospital, death) records. The use of, and adherence to (proportion of days covered Results: Of 11,217 eligible patients (median age 72 years, 42% female), 9,294 (83%) used lipid-lowering medications within 90 days post-discharge, including 5,479 new users. In both prevalent-user and new-user designs, nonusers (vs. users) had significantly greater rates of mortality (hazard ratio [HR] 2.35, 95% CI: 1.89–2.92) or all-cause readmissions (HR 1.22, 95% CI: 1.05–1.40) but not cardiovascular disease readmission. In contrast, associations between having poor (vs. good) adherence on outcomes were stronger among new users than all users. Among new users, having poor adherence was associated with greater rates of mortality (HR 1.48, 95% CI: 1.12–1.96), all-cause readmission (HR 1.14, 95% CI: 1.02–1.27), and cardiovascular disease readmission (HR 1.20, 95% CI: 1.01–1.42). Conclusions: The real-world effectiveness of treatment with lipid-lowering medications after stroke is attenuated when evaluated based on prevalent-user rather than new-user design. These findings may have implications for designing studies on the real-world effectiveness of secondary prevention medications.

Background and Purpose: Primary care physicians (PCPs) provide ongoing management after stroke. However, little is known about how best to measure physician encounters with reference to longer term outcomes. We aimed to compare methods for measuring regularity and continuity of PCP encounters, based on survival following stroke using linked healthcare data. Methods: Data from the Australian Stroke Clinical Registry (2010–2014) were linked with Australian Medicare claims from 2009 to 2016. Physician encounters were ascertained within 18 months of discharge for stroke. We calculated three separate measures of continuity of encounters (consistency of visits with primary physician) and three for regularity of encounters (distribution of service utilization over time). Indices were compared based on 1-year survival using multivariable Cox regression models. The best performing measures of regularity and continuity, based on model fit, were combined into a composite “optimal care” variable. Results: Among 10,728 registrants (43% female, 69% aged ≥65 years), the median number of encounters was 17. The measures most associated with survival (hazard ratio [95% confidence interval], Akaike information criterion [AIC], and Bayesian information criterion [BIC]) were the Continuity of Care Index (COCI, as a measure of continuity; 0.88 [0.76–1.02], p = 0.099, AIC = 13,746, BIC = 13,855) and our persistence measure of regularity (encounter at least every 6 months; 0.80 [0.67–0.95], p = 0.011, AIC = 13,742, BIC = 13,852). Our composite measure, persistent plus COCI ≥80% (24% of registrants; 0.80 [0.68–0.94], p = 0.008, AIC = 13,742, BIC = 13,851), performed marginally better than our persistence measure alone. Conclusions: Our persistence measure of regularity or composite measure may be useful when measuring physician encounters following stroke.

Introduction: Treatment with several therapeutic classes of medication is recommended for secondary prevention of stroke. We analyzed the associations between the number of classes of prevention medications supplied within 90 days after discharge for ischemic stroke (IS)/transient ischemic attack (TIA) and survival. Methods: This is a retrospective cohort study of adults with first-ever IS/TIA (2010–2014) from the Australian Stroke Clinical Registry individually linked with data from national pharmaceutical and Medicare claims. Exposure was the number of classes of recommended medications, i.e., blood pressure-lowering, antithrombotic, or lipid-lowering agents, supplied to patients within 90 days after discharge for IS/TIA. The longitudinal association between the number of classes of medications and survival was evaluated with Cox proportional hazards regression models using the landmark approach. A landmark date of 90 days after hospital discharge was used to separate exposure and outcome periods, and only patients who survived until this date were included. Results: Of 8,429 patients (43% female, median age 74 years, 80% IS), 607 (7%) died in the year following 90 days after discharge. Overall, 56% of patients were supplied all 3 classes of medications, 28% 2 classes of medications, 11% 1 class of medications, and 5% no class of medications. Compared to patients supplied all 3 medication classes, adjusted hazard ratios for all-cause mortality ranged from 1.43 (95% confidence interval [CI]: 1.18–1.72) in those supplied 2 medication classes to 2.04 (95% CI: 1.44–2.88) in those supplied with no medication class. Discussion/Conclusion: Treatment with all 3 classes of guideline-recommended medications within 90 days after discharge was associated with better survival. Ongoing efforts are required to ensure optimal pharmacological intervention for secondary prevention of stroke.

Oral and Poster Abstracts (in alphabetical order of first author) The following abstracts were accepted for presentation at the Stroke Society of Australasia Annual Scientific Meeting of 2021. We thank the authors for their contribution to the meeting and the Scientific Committee for their valuable input into the program. Erin Godecke and Nawaf Yassi Scientific Committee Co-Chairs

Background Evidence for digital health programmes to support people living with stroke is growing. We assessed the feasibility of a protocol and procedures for the Recovery-focused Community support to Avoid readmissions and improve Participation after Stroke (ReCAPS) trial. Methods We conducted a mixed-method feasibility study. Participants with acute stroke were recruited from three hospitals (Melbourne, Australia). Eligibility: Adults with stroke discharged from hospital to home within 10 days, modified Rankin Score 0–4 and prior use of Short Message System (SMS)/email. While in hospital, recruited participants contributed to structured person-centred goal setting and completed baseline surveys including self-management skills and health-related quality of life. Participants were randomised 7–14 days after discharge via REDCap® (1:1 allocation). Following randomisation, the intervention group received a 12-week programme of personalised electronic support messages (average 66 messages sent by SMS or email) aligned with their goals. The control group received six electronic administrative messages. Feasibility outcomes included the following: number of patients screened and recruited, study retainment, completion of outcome measures and acceptability of the ReCAPS intervention and trial procedures (e.g. participant satisfaction survey, clinician interviews). Protocol fidelity outcomes included number of goals developed (and quality), electronic messages delivered, stop messages received and engagement with messages. We undertook inductive thematic analysis of interview/open-text survey data and descriptive analysis of closed survey questions. Results Between November 2018 and October 2019, 312 patients were screened; 37/105 (35%) eligible patients provided consent (mean age 61 years; 32% female); 33 were randomised (17 to intervention). Overall, 29 (88%) participants completed the12-week outcome assessments with 12 (41%) completed assessments in the allocated timeframe and 16 also completing the satisfaction survey (intervention=10). Overall, trial participants felt that the study was worthwhile and most would recommend it to others. Six clinicians participated in one of three focus group interviews; while they reported that the trial and the process of goal setting were acceptable, they raised concerns regarding the additional time required to personalise goals. Conclusion The study protocol and procedures were feasible with acceptable retention of participants. Consent and goal personalisation procedures should be centralised for the phase III trial to reduce the burden on hospital clinicians. Trial registration Australian New Zealand Clinical Trials Registry, ACTRN12618001468213 (date 31/08/2018); Universal Trial Number: U1111-1206-7237

Background Historically, national programs for collecting stroke data in Australia required the use of multiple online tools. Clinicians were required to enter overlapping variables for the same patient in the different databases. From 2013 to 2016, the Australian Stroke Data Tool (AuSDaT) was built as an integrated data management solution. Objective In this article, we have described the development, implementation, and evaluation phases of establishing the AuSDaT. Method In the development phase, a governance structure with representatives from different data collection programs was established. Harmonisation of data variables, drawn from six programs used in hospitals for monitoring stroke care, was facilitated through creating a National Stroke Data Dictionary. The implementation phase involved a staged deployment for two national programs over 12 months. The evaluation included an online survey of people who had used the AuSDaT between March 2018 and May 2018. Results By July 2016, data entered for an individual patient was, for the first time, shared between national programs. Overall, 119/422 users (90% female, 61% aged 30–49 years, 57% nurses) completed the online evaluation survey. The two most positive features reported about the AuSDaT were (i) accessibility of the system (including simultaneous user access), and (ii) the ability to download reports to benchmark local data against peer hospitals or national performance. More than three quarters of respondents ( n = 92, 77%) reported overall satisfaction with the data collection tool. Conclusion The AuSDaT reduces duplication and enables users from different national programs for stroke to enter standardised data into a single system. Implications This example may assist others who seek to establish a harmonised data management solution for different disease areas where multiple programs of data collection exist. The importance of undertaking continuous evaluation of end-users to identify preferences and aspects of the tool that are not meeting current requirements were illustrated. We also highlighted the opportunities to increase interoperability, utility, and facilitate the exchange of accurate and meaningful data.

BACKGROUND: Hospital arrival via ambulance influences treatment of acute stroke. We aimed to determine the factors associated with use of ambulance and access to evidence-based care among patients with stroke. METHODS: Patients with first-ever strokes from the Australian Stroke Clinical Registry (2010-2013) were linked with administrative data (emergency, hospital admissions). Multilevel, multivariable regression models were used to determine patient, clinical and system factors associated with arrival by ambulance. RESULTS: Among the 6,262 patients with first-ever stroke, 4,737 (76%) arrived by ambulance (52% male; 80% ischaemic). Patients who were older, frailer, with comorbidities or were unable to walk on admission (stroke severity) were more likely to arrive by ambulance to hospital. Compared to those using other means of transport, those who used ambulances arrived to hospital sooner after stroke onset (minutes, 124 vs 397) and were more likely to receive reperfusion therapy (adjusted odds ratio, 1.57, 95% CI: 1.09, 2.27). CONCLUSION: Patients with stroke who use ambulances arrived faster and were more likely to receive reperfusion therapy compared to those using personal transport. Further public education about using ambulance services at all times, instead of personal transport when stroke is suspected is needed to optimise access to time critical care.

Background: Evidence is growing on anticancer effects of statins. We investigated whether the effectiveness of treatment with statins after ischemic stroke on mortality is influenced by a history of cancer. Methods: Analyses of 90-day survivors of ischemic stroke (2012–2016; 45 hospitals) using linked registry and administrative data. Dispense of statins within 90 days postdischarge was determined from pharmaceutical records. Participants were followed from 91 days postdischarge until death or June 30, 2018. History of cancer was determined from hospital data. Propensity score–adjusted Cox proportional hazards regression model was used to determine the association between being dispensed statins and survival. The influence of history of cancer on this association was assessed based on the concepts of (1) statistical interaction and (2) biological interaction using 3 indices: relative excess risk due to interaction>0, attributable proportion due to interaction >0, or synergy index >1. Results: Among 9948 eligible participants (median age=72 years, 42% female), there were 1463 deaths. In adjusted analyses, there was no statistical interaction between being dispensed statins and history of cancer on mortality ( P =0.156). However, being dispensed statins had a significant positive biological interaction with having a history of cancer on mortality: relative excess risk due to interaction, 2.80 (95% CI, 1.56–5.05), attributable proportion due to interaction, 0.45 (95% CI, 0.23–0.66), and synergy index, 2.14 (95% CI, 1.32–3.49). Conclusions: Treatment with statins after ischemic stroke may confer additional survival benefits for people who also have had cancer.

Background: Evidence for digital health programs to support people living with stroke is limited. We assessed the feasibility of a protocol and procedures for the Recovery-focused Community support to Avoid readmissions and improve Participation after Stroke (ReCAPS) intervention. Method: We conducted a mixed-method feasibility study. Participants with acute stroke were recruited from three hospitals (Melbourne, Australia). Eligibility: Adults discharged home within 10 days of hospital admission, modified Rankin Score 0-4, and prior use of Short Message System (SMS) or email. While in hospital participants contributed to structured person-centred goal setting with clinicians, provided responses to surveys including assessment of self-management skills and health-related quality of life. Participants were randomised 7-14 days after discharge via REDCap® (1:1 allocation). Following randomisation, the intervention group received a 12-week program of personalised electronic support messages (average 66 messages sent by SMS or email) aligned to their goals. The control group received six electronic administrative messages. Feasibility outcomes included: number of patients screened and recruited, study retainment, completion of outcome measures, number of electronic messages delivered, and acceptability of the ReCAPS intervention and trial procedures (participant satisfaction survey, clinician interviews and researcher communications). We undertook inductive thematic analysis of interview/open-text survey data, and descriptive analysis of closed survey questions.Results: Between November 2018 and October 2019, 312 patients were screened; 37/105 (35%) eligible patients provided consent (mean age 61 years; 32% female); 33 were randomised (17 to intervention). Outcome assessments at 12-weeks were completed by 88% of participants with 16 also completing the satisfaction survey (intervention=10). Overall, trial participants felt that the study was worthwhile and most would recommend it to others. Six clinicians participated in one of three focus group interviews; while they reported that the trial and the process of goal setting acceptable, they raised concerns regarding the additional time required to personalise goals. Conclusion: The study protocol and procedures were feasible with acceptable retention of participants. Consent and goal personalisation procedures should be centralised for the Phase III trial to reduce the burden on hospital clinicians. Trial Registration: Australian New Zealand Clinical Trials Registry: ACTRN12618001468213 (Date 31/08/2018); Universal Trial Number: U1111-1206-7237

Correctly identifying people with suspected stroke is essential for ensuring rapid treatment. Our aims were to determine the sensitivity of emergency dispatcher and paramedic identification of patients with stroke, the factors associated with correct identification, and whether there were any implications for hospital arrival times.Observational study using patient-level data from the Australian Stroke Clinical Registry (2015-2017) linked with ambulance and emergency department records for the state of Victoria. The registry diagnosis was the reference standard to compare with the provisional diagnoses made by emergency services personnel classified as "suspected" and "not suspected" stroke/transient ischemic attack (TIA). Multivariable logistic and quintile regressions were used to determine factors associated with correct identification and timely arrival to hospital.Overall, 4717 (64%) were matched to ambulance transport records (median age: 73 years, 43% female). Stroke/TIA was suspected in 56% of registrants by call-takers and 69% by paramedics. Older patients (75+ years) (adjusted odds ratio [aOR]: 0.61; 95% confidence interval [CI]: 0.49-0.75), females (aOR: 0.86; 95% CI: 0.75-0.99), those with severe stroke or intracerebral hemorrhage were less often suspected as stroke. Cases identified as stroke had a shorter arrival time to hospital (unadjusted median minutes: stroke, 54 [43, 72] vs not stroke, 66 [51, 89]).Emergency dispatchers and paramedics identified over half of patients with stroke in the prehospital setting. Important patient characteristics, such as being female and those having a severe stroke, were found that may enable refinement of prehospital ambulance protocols and dispatcher/paramedic education. Those correctly identified as stroke, arrived earlier to hospital optimizing their chances of receiving time-critical treatments.

Background National organisational surveys and clinical audits to monitor and guide improvements to the delivery of evidence-based acute stroke care have been undertaken in Australia since 1999. This study aimed to determine the association between repeated national audit cycles on stroke service provision and care delivery from 1999 to 2019. Methods Cross-sectional study using data from organisational surveys (1999, 2004, 2007–2019) and clinical data from the biennial National Stroke Acute Audit (2007–2019). Age-, sex-, and stroke severity-adjusted proportions were reported for adherence to guideline-recommended care processes. Multivariable, logistic regression models were performed to determine the association between repeated audit cycles and service provision (organisational) and care delivery (clinical). Results Overall, 197 hospitals provided organisational survey data (1999–2019), with 24,996 clinical cases from 136 hospitals (around 40 cases per audit) (2007–2019). We found significant improvements in service organisation between 1999 and 2019 for access to stroke units (1999: 42%, 2019: 81%), thrombolysis services (1999: 6%, 2019: 85%), and rapid assessment/management for patients with transient ischaemic attack (1999: 11%, 2019: 61%). Analyses of patient-level audits for 2007 to 2019 found the odds of receiving care processes per audit cycle to have significantly increased for thrombolysis (2007: 3%, 2019: 11%; OR 1.15, 95% CI 1.13, 1.17), stroke unit access (2007: 52%, 2019: 69%; OR 1.15, 95% CI 1.14, 1.17), risk factor advice (2007: 40%, 2019: 63%; OR 1.10, 95% CI 1.09, 1.12), and carer training (2007: 24%, 2019: 51%; OR 1.12, 95% CI 1.10, 1.15). Conclusions Between 1999 and 2019, the quality of acute stroke care in Australia has improved in line with best practice evidence. Standardised monitoring of stroke care can inform targeted efforts to reduce identified gaps in best practice, and illustrate the evolution of the health system for stroke.

Background Stroke is a high-cost condition. Detailed patient-level assessments of the costs of care received and outcomes achieved provide useful information for organisation and optimisation of the health system. Objectives To describe the costs of hospital care for stroke and transient ischaemic attack (TIA) and investigate factors associated with costs. Methods Retrospective cohort study using data from the Australian Stroke Clinical Registry (AuSCR) collected between 2009 and 2013 linked to hospital administrative data and clinical costing data in Queensland. Clinical costing data include standardised assignment of costs from hospitals that contribute to the National Hospital Costing programme. Patient-level costs for each hospital admission were described according to the demographic, clinical and treatment characteristics of patients. Multivariable median regression with clustering by hospital was used to determine factors associated with greater costs. Results Among 22 hospitals, clinical costing data were available for 3909 of 5522 patient admissions in the AuSCR (71%). Compared to those without clinical costing data, patients with clinical costing data were more often aged Conclusion Medical and nursing costs were incurred by most patients admitted with stroke or TIA, and were relatively more expensive on average than other cost buckets such as imaging and allied health. Implications Scaling this data linkage to national data collections may provide valuable insights into activity-based funding at public hospitals. Regular report of these costs should be encouraged to optimise economic evaluations.

Objective: In Australia, approximately 3 in 4 people with acute stroke use an ambulance. Few examples of merging ambulance clinical records, hospital government data, and national registry data for stroke exist. We sought to understand the advantages of using linked datasets for describing the full clinical journey of people with stroke and the possibility of investigating their long-term outcomes based on pre-hospital management of stroke. Method: Patient-level data from the Australian Stroke Clinical Registry (AuSCR) (January 2013-October 2017) were linked with Ambulance Victoria (AV) records and Victorian Emergency Minimum Dataset (VEMD). Probabilistic iterative matching on personal identifiers were used and records merged with a project specific identification number. Results: Of the 7,373 episodes in the AuSCR and 6,001 in the AV dataset; 4,569 (62%) were matched. Unmatched records that were positive for “arrival by ambulance” in the AuSCR and VEMD (no corresponding record in AV) were submitted to AV. AV were able to identify 148/435 additional records related to these episodes. The final cohort included 4,717 records (median age: 73 years, female 42%, ischemic stroke 66%). Conclusion: The results of the data linkage provides greater confidence for use of these data for future research related to pre-hospital management of stroke.

Stroke can be prevented through effective management of risk factors. However, current primary stroke prevention approaches are insufficient and often fragmented. Primary stroke prevention strategies are predominantly targeted at behavioural (eg, smoking cessation and lifestyle modifications) and pharmacological interventions (ie, prevention medications). There is also a need to consider interrelating structural factors that support, or hinder, prevention actions and behaviours of individuals. Without addressing these structural factors, it is impossible to maximise the benefits of behavioural and pharmacological interventions at the population level. We propose a tripartite approach to primary stroke prevention, comprising behavioural, pharmacological, and structural interventions, which is superimposed on the socioecological model. This approach could minimise the current fragmentation and inefficiency of primary stroke prevention.

Background Governments have responsibility for ensuring the quality and fitness-for-purpose of personal health data provided to them. While these health information assets are used widely for research, this secondary usage has received minimal research attention. Objective This study aimed to investigate the secondary uses, in research, of population health and administrative datasets (information assets) of the Department of Health (DoH), Victoria, Australia. The objectives were to (i) identify research based on these datasets published between 2008 and 2020; (ii) describe the data quality studies published between 2008 and 2020 for each dataset and (iii) evaluate “fitness-for-purpose” of the published research. Method Using a modified scoping review, research publications from 2008 to 2020 based on information assets related to health service provision and containing person-level data were reviewed. Publications were summarised by data quality and purpose-categories based on a taxonomy of data use. Fitness-for-purpose was evaluated by comparing the publicly stated purpose(s) for which each information asset was collected, with the purpose(s) assigned to the published research. Results Of the >1000 information assets, 28 were utilised in 756 publications: 54% were utilised for general research purposes, 14% for patient safety, 10% for quality of care and 39% included data quality-related publications. Almost 85% of publications used information assets that were fit-for-purpose. Conclusion The DoH information assets were used widely for secondary purposes, with the majority identified as fit-for-purpose. We recommend that data custodians, including governments, provide information on data quality and transparency on data use of their health information assets.

Background and Purpose: A comprehensive understanding of the long-term impact of stroke assists in health care planning. We aimed to determine changes in rates, causes, and associated factors for hospital presentations among long-term survivors of stroke. Methods: Person-level data from the AuSCR (Australian Stroke Clinical Registry) during 2009 to 2013 were linked with state-based health department emergency department and hospital admission data. The study cohort included adults with first-ever stroke who survived the first 6 months after discharge from hospital. Annualized rates of hospital presentations (nonadmitted emergency department or admission)/person/year were calculated for 1 to 12 months prior, and 7 to 12 months (inclusive) after hospitalization. Multilevel, negative binomial regression was used to identify associated factors after adjustment for prestroke hospital presentations and stratification for perceived impairment status. Perceived impairments to health were defined according to the subscales and visual analog health status scores on the 5-Dimension European Quality of Life Scale. Results: There were 7183 adults with acute stroke, 7-month survivors (median age 72 years; 56% male; 81% ischemic, and 42% with impairment at 90–180 days) from 39 hospitals included in this landmark analysis. Annualized presentations/person increased from 0.88 (95% CI, 0.86–0.91) to 1.25 (95% CI, 1.22–1.29) between the prestroke and poststroke periods, with greater rate increases in those with than without perceived impairment (55% versus 26%). Higher presentation rates were most strongly associated with older age (≥85 versus 65 years, incidence rate ratio, 1.52 [95% CI, 1.27–1.82]) and greater comorbidity score (incidence rate ratio, 1.06 [95% CI, 1.02–1.10]), whereas reduced rates were associated with greater social advantage (incidence rate ratio, 0.71 [95% CI, 0.60–0.84]). Poststroke hospital presentations (7–12 months) were most frequently related to recurrent cardiovascular and cerebrovascular events and sequelae of stroke. Conclusions: A large increase in annualized hospital presentation rates after stroke indicates the potential for improved community management and support for this vulnerable patient group.

Hospitalizations for acute ischemic stroke (AIS) and transient ischemic attack (TIA) decreased during the COVID-19 pandemic. We compared the quality of care and outcomes for patients with AIS/TIA before vs. during the COVID-19 pandemic across the United States Department of Veterans Affairs healthcare system.This retrospective cohort study compared AIS/TIA care quality before (March-September 2019) vs. during (March-September 2020) the pandemic. Electronic health record data were used to identify patient characteristics, quality of care and outcomes. The without-fail rate was a composite measure summarizing whether an individual patient received all of the seven processes for which they were eligible. Mixed effects logistic regression modeling was used to assess differences between the two periods.A decrease in presentations occurred during the pandemic (N = 4360 vs. N = 5636 patients; p = 0.003) and was greater for patients with TIA (-30.4%) than for AIS (-18.7%). The without-fail rate improved during the pandemic (56.2 vs. before 50.1%). The use of high/moderate potency statins increased among AIS patients (OR 1.26 [1.06-1.48]) and remained unchanged among those with TIA (OR 1.04 [0.83,1.29]). Blood pressure measurement within 90-days of discharge was less frequent during the pandemic (57.8 vs. 89.2%, p 0.001). Hypertension control decreased among patients with AIS (OR 0.73 [0.60-0.90]) and TIA (OR 0.72 [0.54-0.96]). The average systolic and diastolic blood pressure was 1.9/1.4 mmHg higher during the pandemic than before (p 0.001). Compared to before, during the pandemic fewer AIS patients had a primary care visit (52.5% vs. 79.8%; p = 0.0001) or a neurology visit (27.9 vs. 41.1%; p = 0.085). Both 30- and 90-day unadjusted all-cause mortality rates were higher in 2020 (3.6% and 6.7%) vs. 2019 (2.9, 5.4%; p = 0.041 and p = 0.006); but these differences were not statistically significant after risk adjustment.Overall quality of care for patients with AIS/TIA did not decline during the COVID-19 pandemic.

To describe types of mental health treatment accessed by community-based stroke survivors and factors associated with access. A sub-group of registrants from the Australian Stroke Clinical Registry completed a supplementary survey 2.5 years post-stroke. Self-reported information about depression/anxiety and treatment access were collected. Demographic and clinical data were obtained through linkages with registry and government data. Staged multivariable logistic regression was conducted to examine factors associated with treatment access. Among 623 registrants surveyed (37% female, median age 69 years), 26% self-reported a medical diagnosis of depression/anxiety at 2.5 years post-stroke. Of these, only 30% reported having accessed mental health services, mostly through government-funded Medicare schemes. Younger age (odds ratio (OR) 0.95, 95% CI 0.93, 0.98), history of mental health treatment (OR 3.38, 95% CI 1.35, 8.48), feeling socially isolated (OR 2.32, 95% CI 1.16, 4.66), self-reported medical diagnosis of depression/anxiety (OR 4.85, 95% CI 2.32, 10.14), and government-subsidised team care plan arrangement (OR 4.05, 95% CI 1.96, 8.37) were associated with receiving treatment. Many stroke survivors have untreated depression/anxiety. Primary care practitioners should be supported in undertaking effective detection and management. Older and newly diagnosed individuals should be educated about depression/anxiety and available supports.Implications for rehabilitationPrimary care providers play a pivotal role in the pathway to mental health care, and therefore should always screen for depression/anxiety and provide comprehensive assessment and referral to specialist services where necessary.Targeted psychoeducation should be provided to survivors of stroke who are older and newly diagnosed with depression/anxiety, to increase awareness about mood problems following stroke.Primary care providers should collaborate with other health professionals (e.g., through coordinating a team care arrangement plan), to address patients��� multiple and complex rehabilitation needs.Rehabilitation professionals should remain informed about current evidence-based treatments for post-stroke depression/anxiety and pathways that enable their patients to access these services. Primary care providers play a pivotal role in the pathway to mental health care, and therefore should always screen for depression/anxiety and provide comprehensive assessment and referral to specialist services where necessary. Targeted psychoeducation should be provided to survivors of stroke who are older and newly diagnosed with depression/anxiety, to increase awareness about mood problems following stroke. Primary care providers should collaborate with other health professionals (e.g., through coordinating a team care arrangement plan), to address patients��� multiple and complex rehabilitation needs. Rehabilitation professionals should remain informed about current evidence-based treatments for post-stroke depression/anxiety and pathways that enable their patients to access these services.

Variation in the delivery of evidence-based care affects outcomes for patients with stroke. A range of hospital (organizational), patient, and clinical factors can affect care delivery. Clinical registries are widely used to monitor stroke care and guide quality improvement efforts within hospitals. However, hospital features are rarely collected. We aimed to explore the influence of hospital resources for stroke, in metropolitan and regional/rural hospitals, on the provision of evidence-based patient care and outcomes. The 2017 National Audit organizational survey (Australia) was linked to patient-level data from the Australian Stroke Clinical Registry (2016–2017 admissions). Regression models were used to assess the associations between hospital resources (based on the 2015 Australian National Acute Stroke Services Framework) and patient care (reflective of national guideline recommendations), as well as 90–180-day readmissions and health-related quality of life. Models were adjusted for patient factors, including the severity of stroke. Fifty-two out of 127 hospitals with organizational survey data were merged with 22 832 Australian Stroke Clinical Registry patients with an admission for a first-ever stroke or transient ischaemic attack (median age 75 years, 55% male, and 66% ischaemic). In metropolitan hospitals (n = 42, 20 977 patients, 1701 thrombolyzed, and 2395 readmitted between 90 and 180 days post stroke), a faster median door-to-needle time for thrombolysis was associated with ≥500 annual stroke admissions [−15.9 minutes, 95% confidence interval (CI) −27.2, −4.7], annual thrombolysis >20 patients (−20.2 minutes, 95% CI −32.0, −8.3), and having specialist stroke staff (dedicated medical lead and stroke coordinator; −12.7 minutes, 95% CI −25.0, −0.4). A reduced likelihood of all-cause readmissions between 90 and 180 days was evident in metropolitan hospitals using care pathways for stroke management (odds ratio 0.82, 95% CI 0.67–0.99). In regional/rural hospitals (n = 10, 1855 patients), being discharged with a care plan was also associated with the use of stroke clinical pathways (odds ratio 3.58, 95% CI 1.45–8.82). No specific hospital resources influenced 90–180-day health-related quality of life. Relevant to all international registries, integrating information about hospital resources with clinical registry data provides greater insights into factors that influence evidence-based care.

Background: Aphasia is a common consequence of stroke, and people who live with this condition experience poor outcomes. Adherence to clinical practice guidelines can promote high-quality service delivery and optimize patient outcomes. However, there are currently no high-quality guidelines specific to post-stroke aphasia management. Aims: To identify and evaluate recommendations from high-quality stroke guidelines that can inform aphasia management. Summary of review: We conducted an updated systematic review in accordance with PRISMA guidelines to identify high-quality clinical guidelines published between January 2015 and October 2022. Primary searches were performed using electronic databases: PubMed, EMBASE, CINAHL, and Web of Science. Gray literature searches were conducted using Google Scholar, guideline databases, and stroke websites. Clinical practice guidelines were evaluated using the Appraisal of Guidelines and Research and Evaluation (AGREE II) tool. Recommendations were extracted from high-quality guidelines (scored > 66.7% on Domain 3: “Rigor of Development”), classified as aphasia-specific or aphasia-related, and categorized into clinical practice areas. Evidence ratings and source citations were assessed, and similar recommendations were grouped. Twenty-three stroke clinical practice guidelines were identified and 9 (39%) met our criteria for rigor of development. From these guidelines, 82 recommendations for aphasia management were extracted: 31 were aphasia-specific, 51 aphasia-related, 67 evidence-based, and 15 consensus-based. Conclusion: More than half of stroke clinical practice guidelines identified did not meet our criteria for rigorous development. We identified 9 high-quality guidelines and 82 recommendations to inform aphasia management. Most recommendations were aphasia-related; aphasia-specific recommendation gaps were identified in three clinical practice areas: “accessing community supports,” “return to work, leisure, driving,” and “interprofessional practice.”

To critically appraise literature on recent advances and methods using "big data" to evaluate stroke outcomes and associated factors.Recent big data studies provided new evidence on the incidence of stroke outcomes, and important emerging predictors of these outcomes. Main highlights included the identification of COVID-19 infection and exposure to a low-dose particulate matter as emerging predictors of mortality post-stroke. Demographic (age, sex) and geographical (rural vs. urban) disparities in outcomes were also identified. There was a surge in methodological (e.g., machine learning and validation) studies aimed at maximizing the efficiency of big data for improving the prediction of stroke outcomes. However, considerable delays remain between data generation and publication. Big data are driving rapid innovations in research of stroke outcomes, generating novel evidence for bridging practice gaps. Opportunity exists to harness big data to drive real-time improvements in stroke outcomes.

It is unclear whether survivors of stroke or transient ischemic attack (TIA) routinely receive, and understand, education about secondary prevention medications.To investigate whether survivors of stroke/TIA understand explanations about their prescribed prevention medications and associations with medication adherence, control of risk factors, and unmet needs.A survey was administered among survivors of stroke/TIA (random sample N = 1500) from the Australian Stroke Clinical Registry (Victoria and Queensland, 2016). Participants reported whether they understood explanations about each prescribed medication, as well as their unmet needs, perceived control of risk factors, and 30-day medication adherence. Linked pharmacy claims data were also used to determine medication adherence in the previous two years (proportion of days covered ≥80%). Outcomes were analyzed using multivariable logistic regression or multivariable negative binomial regression for frequency of unmet needs.Overall, 630/1455 eligible survivors completed the survey at ≈2.5 years post-admission (median age 69 years; 37% female). Most participants reported using prevention medications (76% antihypertensive; 84% antithrombotic; 76% lipid-lowering) but only 66-75% reported they understood explanations about their medication (75% antihypertensive; 66% antithrombotic; 74% lipid-lowering). Participants who understood explanations about their medication more often reported 30-day adherence for antihypertensive (adjusted odds ratios [aOR]: 1.96; 95% CI: 1.20-3.19), antithrombotic (aOR: 2.03; 95% CI: 1.31-3.14) and lipid-lowering medications (aOR: 1.73; 95% CI: 1.08-2.76). Similar associations were observed for antihypertensive and antithrombotic medications when pharmacy claims data were used to infer 2-year medication adherence. Understanding explanations about medications was also associated with perceived control of risk factors (hypertension: aOR: 11.08; 95% CI: 6.04-20.34; cholesterol aOR: 8.26; 95% CI: 4.72-14.47) and up to 33% fewer unmet needs related to secondary prevention.Expanded efforts are needed to improve the delivery of information about prevention medications to promote medication adherence, control of risk factors, and potentially prevent unmet needs following stroke/TIA.

Background and Purpose: Although a target of 80% medication adherence is commonly cited, it is unclear whether greater adherence improves survival after stroke or transient ischemic attack (TIA). We investigated associations between medication adherence during the first year postdischarge, and mortality up to 3 years, to provide evidence-based targets for medication adherence. Methods: Retrospective cohort study of 1-year survivors of first-ever stroke or TIA, aged ≥18 years, from the Australian Stroke Clinical Registry (July 2010–June 2014) linked with nationwide prescription refill and mortality data (until August 2017). Adherence to antihypertensive agents, statins, and nonaspirin antithrombotic medications was based on the proportion of days covered from discharge until 1 year. Cox regression with restricted cubic splines was used to investigate nonlinear relationships between medication adherence and all-cause mortality (to 3 years postdischarge). Models were adjusted for age, sex, socioeconomic position, stroke factors, primary care factors, and concomitant medication use. Results: Among 8363 one-year survivors of first-ever stroke or TIA (44% aged ≥75 years, 44% female, 18% TIA), 75% were supplied antihypertensive agents. In patients without intracerebral hemorrhage (N=7446), 84% were supplied statins, and 65% were supplied nonaspirin antithrombotic medications. Median adherence was ≈90% for each medication group. Between 1% and 100% adherence, greater adherence to statins or antihypertensive agents, but not nonaspirin antithrombotic agents, was associated with improved survival. When restricted to linear regions above 60% adherence, each 10% increase in adherence was associated with a reduction in all-cause mortality of 13% for antihypertensive agents (hazard ratio, 0.87 [95% CI, 0.81–0.95]), 13% for statins (hazard ratio, 0.87 [95% CI, 0.80–0.95]), and 15% for nonaspirin antithrombotic agents (hazard ratio, 0.85 [95% CI, 0.79–0.93]). Conclusions: Greater levels of medication adherence after stroke or TIA are associated with improved survival, even among patients with near-perfect adherence. Interventions to improve medication adherence are needed to maximize survival poststroke.

To investigate cerebrovascular event (CVE) denials reported by registered patients to the Australian Stroke Clinical Registry, and to examine the factors associated with CVE denial.CVE denials reported from January 1, 2017 to June 30, 2018 were followed up with hospitals to verify their discharge diagnosis. CVE denials were compared with all non-CVE denial registrants and a 5% random sub-sample of non-CVE deniers according to patient and clinical characteristics, quality of care indicators and health outcomes. Multilevel, multivariable logistic regression models were used. Factors explored were age, sex, stroke severity, type of stroke, treatment in a stroke unit, length of stay and discharge destination. Level was defined as hospital.Overall, 339/23,830 (2%) CVE denials were reported during the 18-month period. Hospitals confirmed 117 (61%) of CVE denials as a verified diagnosis of stroke or transient ischaemic attack (TIA). Compared to non-CVE deniers, CVE deniers were younger, had a shorter median length of stay (four days versus one day) and were more likely to be diagnosed with a TIA (64%) compared to the other types of stroke (11% intracerebral haemorrhage; 20% ischaemic; 5% undetermined).Very few patients denied their CVE, with the majority of denials subsequently confirmed as eligible for registry inclusion. Diagnosis of a TIA and shorter length of stay were associated with CVE denial. These findings provide evidence that very few cases are incorrectly entered into a national registry, and highlight the characteristics of those unlikely to accept their clinical diagnosis where further education of diagnosis may be needed.

Background Australia has among the highest prevalence of Crohn disease and ulcerative colitis in the world. Management of the chronic gastrointestinal disorders results in significant societal costs and the standard of care is inconsistent across Australia. Aim To audit the quality of care received by patients admitted for inflammatory bowel disease (IBD) across Australia against national IBD standards. Methods A retrospective cross-sectional survey and clinical audit was undertaken assessing organisational resources, clinical processes and outcome measures. This study was conducted in Australian hospitals that care for inpatients with Crohn disease or ulcerative colitis. The main outcome measures were adherence to national IBD standards and comparison of quality of care between hospitals with and without multidisciplinary IBD services. Results A total of 71 hospitals completed the organisational survey. Only one hospital had a complete multidisciplinary IBD service and 17 had a partial IBD service (IBD nurse, helpline and clinical lead). A total of 1440 inpatient records was reviewed from 52 hospitals (mean age 37 years; 51% female, 53% Crohn disease), approximately 26% of IBD inpatient episodes over a 12-month period in Australia. These patients were chronically unwell with high rates of anaemia (30%) and frequent readmissions (40% within 2 years). In general, care was inconsistent, and documentation was poor. Hospitals with a partial IBD service performed better in many processes and outcome measures: for example, 22% reduction in admissions through emergency departments and greater adherence to standards for safety monitoring of biological (89% vs 59%) and immunosuppressive drugs (79% vs 55%) in those hospitals than those without. Conclusion Patients admitted to hospital suffering from IBD are young, chronically unwell and are subject to substantial variations in clinical documentation and quality of care. Only one hospital met accepted standards for multidisciplinary care; hospitals with even a minimal IBD service provided improved care.

Supplemental Digital Content is available in the text., Background and Purpose— Hospital uptake of evidence-based stroke care is variable. We aimed to determine the impact of a multicomponent program involving financial incentives and quality improvement interventions, on stroke care processes. Methods— A prospective study of interventions to improve clinical care quality indicators at 19 hospitals in Queensland, Australia, during 2010 to 2015, compared with historical controls and 23 other Australian hospitals. After baseline routine audit and feedback (control phase, 30 months), interventions involving financial incentives (21 months) and then addition of externally facilitated quality improvement workshops with action plan development (9 months) were implemented. Postintervention phase was 13 months. Data were obtained for the analysis from a previous continuous audit in Queensland and subsequently the Australian Stroke Clinical Registry. Primary outcome: change in median composite score for adherence to ≤8 indicators. Secondary outcomes: change in adherence to self-selected indicators addressed in action plans and 4 national indicators compared with other Australian hospitals. Multivariable analyses with adjustment for clustered data. Results— There were 17 502 patients from the intervention sites (median age, 74 years; 46% women) and 20 484 patients from other Australian hospitals. Patient characteristics were similar between groups. There was an 18% improvement in the primary outcome across the study periods (95% CI, 12%–24%). The largest improvement was following introduction of financial incentives (14%; 95% CI, 8%–20%), while indicators addressed in action plans provided an 8% improvement (95% CI, 1%–17%). The national score (4 indicators) improved by 17% (95% CI, 13%–20%) versus 0% change in other Australian hospitals (95% CI, −0.03 to 0.03). Access to stroke units improved more in Queensland than in other Australian hospitals (P

ObjectivesPatient-reported outcomes (PROs) are increasingly used to measure the patient’s perspective of their outcomes following healthcare interventions. The aim of this study was to determine the preferred formats for reporting service-level PROs data to clinicians, researchers and managers to support greater utility of these data to improve healthcare and patient outcomes.SettingHealthcare professionals receiving PRO data feedback at the health service level.ParticipantsAn interdisciplinary Project Working Group comprised of clinicians participated in three workshops to codesign reporting templates of summarised PRO data (modified Rankin Scale, EuroQol Five Dimension Descriptive System, EuroQol Visual Analogue Scale and Hospital Anxiety and Depression Scale) using a modified Delphi process. An electronic survey was then distributed to short list the preferred templates among a broad sample of clinical end users. A final workshop was undertaken with the Project Working Group to review results and reach consensus on the final templates.Primary and secondary outcome measuresThe recommendation of preferred PRO summary data feedback templates and guiding principles for reporting aggregate PRO data to clinicians was the primary outcome. A secondary outcome was the identification of perceived barriers and enablers to the use of PRO data in hospitals. For each outcome measure, quantitative and qualitative data were summarised.Results31 Working Group members (19 stroke, 2 psychology, 1 pharmacy, 9 researchers) participated in the workshops, where 25/55 templates were shortlisted for wider assessment. The survey was completed by 114 end users. Strongest preferences were identified for bar charts (37/82 votes, 45%) and stacked bar charts (37/91 votes, 41%). At the final workshop, recommendations to enhance communication of PROs data for comparing health service performance were made including tailoring feedback to professional roles and use of case-mix adjustment to ensure fair comparisons.ConclusionsOur research provides guidance on PROs reporting for optimising data interpretation and comparing hospital performance.

Objectives To assess the agreement between pharmaceutical claims data and patient-reported medication use after stroke. Methods Claims data from the Pharmaceutical Benefits Scheme were used to estimate medication use for a subset of participants registered in the Australian Stroke Clinical Registry in 2016. Estimates on medication use were validated against patient-reported responses (considered the reference standard). Key findings For antihypertensive and lipid-lowering medications, the sensitivity of claims data was excellent (85–87%) and the specificity was good (73–78%). Whereas for antithrombotic medications, sensitivity was modest (61%), but specificity was excellent (85%). Conclusions Pharmaceutical claims data can be used to infer medication use after stroke with mostly good to excellent sensitivity and specificity compared with the patient report.

Background and Purpose: Conditions associated with frailty are common in people experiencing stroke and may explain differences in outcomes. We assessed associations between a published, generic frailty risk score, derived from administrative data, and patient outcomes following stroke/transient ischemic attack; and its accuracy for stroke in predicting mortality compared with other measures of clinical status using coded data. Methods: Patient-level data from the Australian Stroke Clinical Registry (2009–2013) were linked with hospital admissions data. We used International Statistical Classification of Diseases and Related Health Problems, Tenth Revision codes with a 5-year look-back period to calculate the Hospital Frailty Risk Score (termed Frailty Score hereafter) and summarized results into 4 groups: no-risk (0), low-risk (1–5), intermediate-risk (5–15), and high-risk (>15). Multilevel models, accounting for hospital clustering, were used to assess associations between the Frailty Score and outcomes, including mortality (Cox regression) and readmissions up to 90 days, prolonged acute length of stay (>20 days; logistic regression), and health-related quality of life at 90 to 180 days (quantile regression). The performance of the Frailty Score was then compared with the Charlson and Elixhauser Indices using multiple tests (eg, C statistics) for predicting 30-day mortality. Models were adjusted for covariates including sociodemographics and stroke-related factors. Results: Among 15 468 adult patients, 15% died ≤90 days. The frailty scores were 9% no risk; 23% low, 45% intermediate, and 22% high. A 1-point increase in frailty (continuous variable) was associated with greater length of stay (OR adjusted , 1.05 [95% CI, 1.04 to 1.06), 90-day mortality (HR adjusted , 1.04 [95% CI, 1.03 to 1.05]), readmissions (OR adjusted , 1.02 [95% CI, 1.02 to 1.03]; and worse health-related quality of life (median difference, −0.010 [95% CI −0.012 to −0.010]). Adjusting for the Frailty Score provided a slightly better explanation of 30-day mortality (eg, larger C statistics) compared with other indices. Conclusions: Greater frailty was associated with worse outcomes following stroke/transient ischemic attack. The Frailty Score provides equivalent precision compared with the Charlson and Elixhauser indices for assessing risk-adjusted outcomes following stroke/transient ischemic attack.

Rationale To address unmet needs, electronic messages to support person-centered goal attainment and secondary prevention may avoid hospital presentations/readmissions after stroke, but evidence is limited. Hypothesis Compared to control participants, there will be a 10% lower proportion of intervention participants who represent to hospital (emergency/admission) within 90 days of randomization. Methods and design Multicenter, double-blind, randomized controlled trial with intention-to-treat analysis. The intervention group receives 12 weeks of personalized, goal-centered, and administrative electronic messages, while the control group only receive administrative messages. The trial includes a process evaluation, assessment of treatment fidelity, and an economic evaluation. Participants: Confirmed stroke (modified Rankin Score: 0-4), aged ≥18 years with internet/mobile phone access, discharged directly home from hospital. Randomization: 1:1 computer-generated, stratified by age and baseline disability. Outcomes assessments: Collected at 90 days and 12 months following randomization. Outcomes Primary outcomes include hospital emergency presentations/admissions within 90 days of randomization. Secondary outcomes include goal attainment, self-efficacy, mood, unmet needs, disability, quality-of-life, recurrent stroke/cardiovascular events/deaths at 90 days and 12 months, and death and cost-effectiveness at 12 months. Sample size: To test our primary hypothesis, we estimated a sample size of 890 participants (445 per group) with 80% power and two-tailed significance threshold of α = 0.05. Given uncertainty for the effect size of this novel intervention, the sample size will be adaptively re-estimated when outcomes for n = 668 are obtained, with maximum sample capped at 1100. Discussion We will provide new evidence on the potential effectiveness, implementation, and cost-effectiveness of a tailored eHealth intervention for survivors of stroke.

Objectives: It is unclear how acute care influences patient outcomes in those who receive rehabilitation. We aimed to determine the associations between acute stroke therapies, outcomes during inpatient rehabilitation and self-reported outcomes at 90-180 days after stroke. Materials and Methods: Patient-level data from adults with acute stroke registered in the Australian Stroke Clinical Registry (AuSCR, 2014–2017) were linked with data from the Australasian Rehabilitation Outcomes Centre (AROC). The main outcome was relative function gain (RFG), which is a measure of the FIM change achieved between admission to discharge as a proportion of the total gain possible based on admission FIM, relative to the maximum achievable score. Multilevel logistic/median regression analyses were used to investigate the association between RFG achieved in rehabilitation and (1) acute stroke therapies; (2) 90–180 day outcomes (health-related quality of life using EuroQoL-5D-3L; independence according to modified Rankin Scale (score 0–2) and self-reported hospital readmission). Results: Overall, 8397/8507 eligible patients from the AuSCR were linked with corresponding AROC data (95% linkage rate; median age 75 years, 43% female); 4239 had 90–180 days survey data. Receiving thrombolysis (16% of the cohort) had a minimal association with RFG in rehabilitation (coefficient: 0.03; 95% Confidence Interval [CI]: 0.01, 0.05). Greater RFG achieved whilst in in-patient rehabilitation was associated with better longer-term HR-QoL (coefficient 21.77, 95% CI 17.8, 25.8) including fewer problems with mobility, self-care, pain, usual activities and anxiety/depression; greater likelihood of independence (adjusted Odds Ratio: 10.66; 95% CI 7.86, 14.45); and decreased odds of self-reported hospital readmission (adjusted Odds Ratio: 0.53; 95% CI 0.41, 0.70) within 90-180 days post-stroke. Conclusions: Stroke survivors who achieved greater RFG during inpatient rehabilitation had better HR-QoL and were more likely to be independent at follow-up. Acute care processes did not appear to impact RFG or long-term outcomes for those who accessed inpatient rehabilitation. Refereed/Peer-reviewed

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

IntroductionStroke is a leading cause of death and disability. Since 2012, our innovative national data linkage program, has enabled the successful linkage of data from the Australian Stroke Clinical Registry (AuSCR) with national and state-based datasets to investigate the continuum of stroke care and associated outcomes. Objectives and ApproachUsing stroke as a case study, in this symposium we will describe the use of linked data to undertake clinical and economic evaluations and contribute new knowledge for policy and practice. We have undertaken a range of iterative and innovative projects linking the AuSCR (used now in >80 public hospitals across Australia with follow-up survey of patients between 90-180 days) with various administrative datasets. Linkages with the National Death Index, inpatient admissions and emergency presentations, Pharmaceutical Benefits Scheme (PBS), Medicare Benefits Schedule (MBS), Aged Care services; Ambulance Victoria, Australian Rehabilitation Outcomes Centre and general practice network datasets (POLAR) have been achieved. ResultsThe symposium will provide case studies and results from four data linkage projects involving the AuSCR: 1) Stroke123 (NHMRC: #1034415), a study to investigate the impact of quality of acute care on admission/emergency presentations and survival; 2) PRECISE (NHMRC:#1141848), a study to evaluate models of primary care involving linkages with PBS/MBS, aged care services and admissions/emergency data; 3) AMBULANCE: a study to investigate how pre-hospital care affects acute stroke care involving linkages with the ambulance and admissions/emergency datasets; and 4) POLAR: a study to understand the long-term management of stroke involving linkages with primary health data. Conclusion / ImplicationsThe National Stroke Data Linkage Program has been visionary and remains highly contemporary in the field of linked data. A unique feature of this program is the active participation of clinicians and policy-makers to ensure the evidence generated have direct benefits for accelerating change in practice and informing policy.

Background: We examined sex differences in cause of death and cause-specific excess mortality after stroke. Materials and Methods: First-ever strokes (2010-2013; 35 hospitals) participating in the Australian Stroke Clinical Registry were linked to national death registrations and other administrative datasets. One-year cause-specific mortality was categorized as stroke, ischemic heart disease, other cardiovascular disease (CVD; e.g., hypertension), cancer, and other. Specific hazard ratios (sHRs) of death for women compared to men were estimated using competing risk models, with adjustment for factors differing by sex (e.g., age and stroke severity). Age- and sex-specific mortality rates expected in the general population were derived from national data. Standardized mortality ratios (SMRs; observed/expected deaths) were estimated for cause-specific mortality by sex after age standardization. Results: Among 9,441 cases (46% women), women were 7 years older than men, had more severe strokes, and received similar patterns of suboptimal secondary prevention medications at discharge. Women had greater mortality associated with stroke (sHRunadjusted 1.65) and other CVD (sHRunadjusted 1.65), which was related to age and stroke severity rather than other factors. Compared to population norms, those surviving to 30 days had eight-fold increased mortality from stroke (primary/recurrent) events irrespective of sex (SMRage-standardised women 8.8; men 8.3). Excess mortality from other CVD was greater in women (SMRage-standardised 3.6 vs. men 2.8; p = 0.026). Conclusions: Cause-specific mortality after first-ever stroke differs by sex. The greater death rate attributed to stroke/other CVD in women was mostly explained by age and stroke severity. Greater implementation of secondary stroke prevention is relevant to both sexes.

Stroke affects all ages. Despite increased incidence in those65 years, little is known about age-based differences in inpatient rehabilitation management and outcomes.To investigate management and outcomes, comparing younger (65 years) and older (≥65 years) patients with stroke, who received inpatient rehabilitation.Multicentre, cross-sectional study using data from Australian hospitals who participated in the Stroke Foundation national stroke rehabilitation audit (2016-2018). Chi-square tests compared characteristics and care by age. Multivariable regression models were used to compare outcomes by age (e.g. length of stay). Models were adjusted for sex, stroke type and severity factors.7,165 audited cases from 127 hospitals; 23%65 years (66% male; 72% ischaemic stroke). When compared to older patients, younger patients were more likely male (66% vs 52%); identify as Aboriginal or Torres Strait Islander (6% vs 1%); be less disabled on admission; receive psychology (46% vs 34%) input, and community reintegration support, including return to work (OR 1.47, 95% CI 1.03, 2.11), sexuality (OR 1.60, 95% CI 1.39, 1.84) and self-management (OR 1.39, 95% CI 1.23, 1.57) advice. Following adjustment, younger patients had longer lengths of stay (coeff 3.54, 95% CI 2.27, 4.81); were more likely to be independent on discharge (aOR 1.96, 95% CI 1.68, 2.28); be discharged to previous residences (aOR 1.64, 95% CI 1.41, 1.91) and receive community rehabilitation (aOR: 2.27, 95% CI 1.91, 2.70).Age-related differences exist in characteristics, management and outcomes for inpatients with stroke accessing rehabilitation in Australia.