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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. 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. [ABSTRACT FROM AUTHOR]

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 <80% [poor adherence] vs. ≥80% [good adherence]), lipid-lowering medications within 90 days post-discharge was determined from pharmaceutical records. Users were further classified as prevalent (continuing) or new users, based on dispensing within 90 days prior to stroke. A propensity score-adjusted Cox regression was used to evaluate the effectiveness of lipid-lowering medications on outcomes (all-cause mortality, all-cause and cardiovascular disease readmission) within the subsequent year. Analyses were undertaken using prevalent-user (all users vs. nonusers) and new-user designs (new users vs. nonusers). 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. [ABSTRACT FROM AUTHOR]

The aim of this study was to describe differences in long-term outcomes for patients discharged to inpatient rehabilitation facilities (IRFs) following stroke compared to patients discharged directly home or to residential aged care facilities (RACFs). Cohort study. Data from the Australian Stroke Clinical Registry were linked to hospital admissions records and the national death index. Main outcomes: death and hospital readmissions up to 12 months post-admission, Health-related Quality of Life (HRQoL) 90-180 days post-admission. Of 8,555 included patients (median age 75, 55% male, 83% ischemic stroke), 4,405 (51.5%) were discharged home, 3,442 (40.2%) to IRFs, and 708 (8.3%) to RACFs. No between-group differences were observed in hazard of death between patients discharged to IRFs versus home. Fewer patients discharged to IRFs were readmitted to hospital within 90, 180 or 365-days compared to patients discharged home (adjusted subhazard ratio [aSHR]:90-days 0.54, 95%CI 0.49, 0.61; aSHR:180-days 0.74, 95%CI 0.67, 0.82; aSHR:365-days 0.85, 95%CI 0.78, 0.93). Fewer patients discharged to IRFs reported problems with mobility compared to those discharged home (adjusted OR 0.54, 95%CI 0.47, 0.63), or to RACFs (aOR 0.35, 95%CI 0.25, 0.48). Overall HRQoL between 90-180 days was worse for people discharged to IRFs versus those discharged home and better than those discharged to RACFs. Several long-term outcomes differed significantly for patients discharged to different settings after stroke. Patients discharged to IRFs reported some better outcomes than people discharge directly home despite having markers of more severe stroke. People with mild strokes are usually discharged directly home, people with moderate severity strokes to inpatient rehabilitation, and people with very severe strokes are usually discharged to residential aged care facilities. People discharged to inpatient rehabilitation reported fewer problems with mobility and had a reduced risk of hospital readmission in the first year post-stroke compared to people discharged directly home after stroke. The median self-reported health-related quality of life for people discharged to residential aged care equated to 'worst health state imaginable'. [ABSTRACT FROM AUTHOR]

In 2022 the Australian Data Availability and Transparency Act (DATA) commenced, enabling accredited “data users” to access data from “accredited data service providers.” However, the DATA Scheme lacks guidance on “trustworthiness” of the data to be utilised for reuse purposes. Objectives: To determine: (i) Do researchers using government health datasets trust the data? (ii) What factors influence their perceptions of data trustworthiness? and (iii) What are the implications for government and data custodians? Method: Authors of published studies (2008–2020) that utilised Victorian government health datasets were surveyed via a case study approach. Twenty-eight trust constructs (identified via literature review) were grouped into data factors, management properties and provider factors. Results: Fifty experienced health researchers responded. Most (88%) believed that Victorian government health data were trustworthy. When grouped, data factors and management properties were more important than data provider factors in building trust. The most important individual trust constructs were: “compliant with ethical regulation” (100%) and “monitoring privacy and confidentiality” (98%). Constructs of least importance were knowledge of “participant consent” (56%) and “major focus of the data provider was research” (50%). Conclusion: Overall, the researchers trusted government health data, but data factors and data management properties were more important than data provider factors in building trust. Implications: Government should ensure the DATA Scheme incorporates mechanisms to validate those data utilised by accredited data users and data providers have sufficient quality (intrinsic and extrinsic) to meet the requirements of “trustworthiness,” and that evidentiary documentation is provided to support these “accredited data.” [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Movement-based mindfulness interventions (MBI) are complex, multi-component interventions for which the design process is rarely reported. For people with stroke, emerging evidence suggests benefits, but mainstream programs are generally unsuitable. We aimed to describe the processes involved and to conduct a formative evaluation of the development of a novel yoga-based MBI designed for survivors of stroke. We used the Medical Research Council complex interventions framework and principles of co-design. We purposefully approached health professionals and consumers to establish an advisory committee for developing the intervention. Members collaborated and iteratively reviewed the design and content of the program, formatted into a training manual. Four external yoga teachers independently reviewed the program. Formative evaluation included review of multiple data sources and documentation (e.g., formal meeting minutes, focus group discussions, researcher observations). The data were synthesized using inductive thematic analysis. Three broad themes emerged: (a) MBI content and terminology; (b) manual design and readability; and (c) barriers and enablers to deliver the intervention. Various perspectives and feedback on essential components guided finalizing the program. The design phase of a novel yoga-based MBI was strengthened by interdisciplinary, consumer contributions and peer review. The 12-week intervention is ready for testing among survivors of stroke. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: To determine whether preexisting dementia is associated with poorer quality of care and outcomes after stroke in the acute hospital phase. Method: This was a retrospective analysis of pooled data from the Australian Stroke Foundation national audit conducted in 2015 and 2017. Dementia status was obtained from the medical records. Processes of care to assess quality included: stroke unit care, time-dependent therapy, nursing/allied health assessments, and preparation for discharge. Outcomes included in-hospital complications, independence on discharge, and destination. Logistic regression was used to examine associations between dementia status and processes of care. Multilevel random effects logistic regression, with level defined as hospital, was used to examine associations between dementia status and outcomes. Results: There were 683/7,070 (9.7%) audited patients with dementia included. Patients with dementia were less likely to be treated in stroke units (58.3% vs 70.6%), receive thrombolysis if an ischemic stroke (5.8% vs 11.1%), have access within 48 hours to physiotherapy (56.4% vs 69.7%) or occupational therapy (46.8% vs 55.6%), see a dietitian if problems with nutrition (64.4% vs 75.9%), or have mood assessed (2.6% vs 12.3%). Patients with dementia were more likely to receive no rehabilitation (adjusted odds ratio 1.88, 95% confidence interval 1.25, 2.83) and be discharged to residential care (adjusted odds ratio 2.36, 95% confidence interval 1.50, 3.72). Conclusion: People with dementia received poorer quality of care and had worse outcomes after stroke. Our findings raise questions regarding equity and the need for better understanding of why the quality of care differs after stroke for people with dementia. [ABSTRACT FROM AUTHOR]

Purpose Prescribed daily dose (PDD), the number of doses prescribed to be taken per day, is used to calculate medication adherence using pharmacy claims data. PDD can be substituted by (i) one dose per day (1DD), (ii) an estimate based on the 75th percentile of days taken by patients to refill a script (PDD75) or (iii) the World Health Organization's defined daily dose (DDD). We aimed to compare these approaches for estimating the duration covered by medications and whether this affects calculated 1‐year adherence to antihypertensive medications post‐stroke. Methods: We conducted a retrospective review of prospective cohort data from the ongoing Australian Stroke Clinical Registry linked with pharmacy claims data. Adherence was calculated as the proportion of days covered (PDC) for 1DD, PDD75 and DDD. Differences were assessed using Wilcoxon rank‐sum tests. Results: Among 12 628 eligible patients with stroke, 10 057 (80%) were prescribed antihypertensive medications in the year after hospital discharge (78.2% aged ≥65 years, 45.2% female). Overall, the 75th percentile of patient time until next medication refill was 39 days. The greatest variations in dose regimens, estimated using person‐ and dose‐level refill times, were for beta blockers (11.4% taking two tablets/day). There were comparable levels of adherence between 1DD and the PDD75 (median PDC 91.0% vs 91.2%; P = 0.70), but adherence was slightly higher using DDD (92.3%; both P < 0.001). However, this would represent a clinically nonsignificant difference. Conclusion: Adherence to antihypertensive medications shows similar estimates across standard measures of dosage in patients during the first year after an acute stroke. [ABSTRACT FROM AUTHOR]