Cost-Effectiveness of a Government Policy to Incentivise Chronic Disease Management following Stroke: A Modelling Study.

INTRODUCTION: Little is known about the cost-effectiveness of government policies that support primary care physicians to provide comprehensive chronic disease management (CDM). This paper aimed to estimate the potential cost-effectiveness of CDM policies over a lifetime for long-time survivors of stroke. METHODS: A Markov model, using three health states (stable, hospitalised, dead), was developed to simulate the costs and benefits of CDM policies over 30 years (with 1-year cycles). Transition probabilities and costs from a health system perspective were obtained from the linkage of data between the Australian Stroke Clinical Registry (cohort n = 12,368, 42% female, median age 70 years, 45% had CDM claims) and government-held hospital, Medicare, and pharmaceutical claims datasets. Quality-adjusted life years (QALYs) were obtained from a comparable cohort (n = 512, 34% female, median age 69.6 years, 52% had CDM claims) linked with Medicare claims and death data. A 3% discount rate was applied to costs in Australian dollars (AUD, 2016) and QALYs beyond 12 months. Probabilistic sensitivity analyses were used to understand uncertainty. RESULTS: Per-person average total lifetime costs were AUD 142,939 and 8.97 QALYs for those with a claim, and AUD 103,889 and 8.98 QALYs for those without a claim. This indicates that these CDM policies were costlier without improving QALYs. The probability of cost-effectiveness of CDM policies was 26.1%, at a willingness-to-pay threshold of AUD 50,000/QALY. CONCLUSION: CDM policies, designed to encourage comprehensive care, are unlikely to be cost-effective for stroke compared to care without CDM. Further research to understand how to deliver such care cost-effectively is needed.

Risk Factors Associated with Major Adverse Cardiovascular Events after Ischemic Stroke: A Linked Registry Study.

INTRODUCTION: Survivors of stroke are at risk of experiencing subsequent major adverse cardiovascular events (MACE). We aimed to determine the incidence of, and risk factors for, MACE after first-ever ischemic stroke, by age group (18-64 years vs. ≥65 years). METHODS: Observational cohort study using patient-level data from the Australian Stroke Clinical Registry (2009-2013), linked with hospital administrative data. We included adults with first-ever ischemic stroke who had no previous acute cardiovascular admissions and followed these patients for 2 years post-discharge, or until the first post-stroke MACE event. A Fine-Gray sub-distribution hazard model, accounting for the competing risk of non-cardiovascular death, was used to determine factors for incident post-stroke MACE. RESULTS: Among 5,994 patients with a first-ever ischemic stroke (median age 73 years, 45% female), 17% were admitted for MACE within 2 years (129 events per 1,000 person-years). The median time to first post-stroke MACE was 117 days (89 days if aged <65 years vs. 126 days if aged ≥65 years; p = 0.025). Among patients aged 18-64 years, receiving intravenous thrombolysis (sub-distribution hazard ratio [SHR] 0.51 [95% CI, 0.28-0.92]) or being discharged to inpatient rehabilitation (SHR 0.65 [95% CI, 0.46-0.92]) were associated with a reduced incidence of post-stroke MACE. In those aged ≥65 years, being unable to walk on admission (SHR 1.33 [95% CI 1.15-1.54]), and history of smoking (SHR 1.40 [95% CI 1.14-1.71]) or atrial fibrillation (SHR 1.31 [95% CI 1.14-1.51]) were associated with an increased incidence of post-stroke MACE. Acute management in a large hospital (>300 beds) for the initial stroke event was associated with reduced incidence of post-stroke MACE, irrespective of age group. CONCLUSIONS: MACE is common within 2 years of stroke, with most events occurring within the first year. We have identified important factors to consider when designing interventions to prevent MACE after stroke, particularly among those aged <65 years.

In Search of a Gold Standard Tool for Assessing Knowledge of Stroke: A Systematic Review.

BACKGROUND: Knowledge of stroke is essential to empower people to reduce their risk of these events. However, valid tools are required for accurate and reliable measurement of stroke knowledge. We aimed to systematically review contemporary stroke knowledge assessment tools and appraise their content validity, feasibility, and measurement properties. METHODS: The protocol was registered in PROSPERO (CRD42023403566). Electronic databases (MEDLINE, PsycInfo, CINAHL, Embase, Scopus, Web of Science) were searched to identify published articles (1 January 2015-1 March 2023), in which stroke knowledge was assessed using a validated tool. Two reviewers independently screened titles and abstracts prior to undertaking full-text review. COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) methods guided the appraisal of content validity (relevance, comprehensiveness, comprehensibility), feasibility, and measurement properties. RESULTS: After removing duplicates, the titles and abstracts of 718 articles were screened; 323 reviewed in full; with 42 included (N = 23 unique stroke knowledge tools). For content validity, all tools were relevant, two were comprehensive, and seven were comprehensible. Validation metrics were reported for internal consistency (n = 20 tools), construct validity (n = 17 tools), cross-cultural validity (n = 15 tools), responsiveness (n = 9 tools), reliability (n = 7 tools), structural validity (n = 3 tools), and measurement error (n = 1 tool). The Stroke Knowledge Test met all content validity criteria, with validation data for six measurement properties (n = 3 rated "Sufficient"). CONCLUSION: Assessment of stroke knowledge is not standardised and many tools lacked validated content or measurement properties. The Stroke Knowledge Test was the most comprehensive but requires updating and further validation for endorsement as a gold standard.

Access to inpatient mood management services after stroke in Australian acute and rehabilitation hospitals.

OBJECTIVE: Post-stroke mental health impairments are common, but under-assessed and under-treated. We aim to describe trends in the provision of mood management to patients with stroke, and describe factors associated with adoption of national mood management recommendations for stroke within Australian hospitals. DESIGN: Secondary analysis of cross-sectional data from the biennial Stroke Foundation Audit Program. SETTING: Participating acute (2011-2021) and rehabilitation hospitals (2012-2020) in Australia. PARTICIPANTS: In the acute audit, 22,937 stroke cases were included from 133 hospitals. In the rehabilitation audit, 15,891 stroke cases were included from 127 hospitals. MAIN MEASURES: Hospital- and patient-level mood management processes. RESULTS: Among 133 acute hospitals (22,937 stroke episodes), improvements were made between 2011 and 2021 in utilization of mood screening (17% [2011], 33% [2021]; p < 0.001) and access to psychologists during hospital stay (18% [2011], 45% [2021]; p < 0.001). There was no change in access to a psychologist among those with a mood impairment (p = 0.34). Among 127 rehabilitation hospitals (15,891 stroke episodes) improvements were observed for mood screening (35% [2012], 61% [2020]; p < 0.001), and access to a psychologist during hospital stay (38% [2012], 68% [2020]; p < 0.001) and among those with a mood-impairment (30% [2012], 50% [2020]; p < 0.001). Factors associated with receiving mood management processes included: younger age, not requiring an interpreter and longer length of stay. CONCLUSIONS: Adherence to mood management recommendations has improved over 10 years within Australian hospitals. Those aged over 65, requiring an interpreter, or with shorter hospital stays are at risk of missing out on appropriate mood management.

Fracture Risk Increases After Stroke or Transient Ischemic Attack and Is Associated With Reduced Quality of Life.

BACKGROUND: Fractures are a serious consequence following stroke, but it is unclear how these events influence health-related quality of life (HRQoL). We aimed to compare annualized rates of fractures before and after stroke or transient ischemic attack (TIA), identify associated factors, and examine the relationship with HRQoL after stroke/TIA. METHODS: Retrospective cohort study using data from the Australian Stroke Clinical Registry (2009-2013) linked with hospital administrative and mortality data. Rates of fractures were assessed in the 1-year period before and after stroke/TIA. Negative binomial regression, with censoring at death, was used to identify factors associated with fractures after stroke/TIA. Respondents provided HRQoL data once between 90 and 180 days after stroke/TIA using the EuroQoL 5-dimensional 3-level instrument. Adjusted logistic regression was used to assess differences in HRQoL at 90 to 180 days by previous fracture. RESULTS: Among 13 594 adult survivors of stroke/TIA (49.7% aged ≥75 years, 45.5% female, 47.9% unable to walk on admission), 618 fractures occurred in the year before stroke/TIA (45 fractures per 1000 person-years) compared with 888 fractures in the year after stroke/TIA (74 fractures per 1000 person-years). This represented a relative increase of 63% (95% CI, 47%-80%). Factors associated with poststroke fractures included being female (incidence rate ratio [IRR], 1.34 [95% CI, 1.05-1.72]), increased age (per 10-year increase, IRR, 1.35 [95% CI, 1.21-1.50]), history of prior fracture(s; IRR, 2.56 [95% CI, 1.77-3.70]), and higher Charlson Comorbidity Scores (per 1-point increase, IRR, 1.18 [95% CI, 1.10-1.27]). Receipt of stroke unit care was associated with fewer poststroke fractures (IRR, 0.67 [95% CI, 0.49-0.93]). HRQoL at 90 to 180 days was worse among patients with prior fracture across the domains of mobility, self-care, usual activities, and pain/discomfort. CONCLUSIONS: Fracture risk increases substantially after stroke/TIA, and a history of these events is associated with poorer HRQoL at 90 to 180 days after stroke/TIA.

Receipt of Mental Health Treatment in People Living With Stroke: Associated Factors and Long-Term Outcomes.

BACKGROUND: Untreated poststroke mood problems may influence long-term outcomes. We aimed to investigate factors associated with receiving mental health treatment following stroke and impacts on long-term outcomes. METHODS: Observational cohort study derived from the Australian Stroke Clinical Registry (AuSCR; Queensland and Victorian registrants: 2012-2016) linked with hospital, primary care billing and pharmaceutical dispensing claims data. Data from registrants who completed the AuSCR 3 to 6 month follow-up survey containing a question on anxiety/depression were analyzed. We assessed exposures at 6 to 18 months and outcomes at 18 to 30 months. Factors associated with receiving treatment were determined using staged multivariable multilevel logistic regression models. Cox proportional hazards regression models were used to assess the impact of treatment on outcomes. RESULTS: Among 7214 eligible individuals, 39% reported anxiety/depression at 3 to 6 months following stroke. Of these, 54% received treatment (88% antidepressant medication). Notable factors associated with any mental health treatment receipt included prestroke psychological support (odds ratio [OR], 1.80 [95% CI, 1.37-2.38]) or medication (OR, 17.58 [95% CI, 15.05-20.55]), self-reported anxiety/depression (OR, 2.55 [95% CI, 2.24-2.90]), younger age (OR, 0.98 [95% CI, 0.97-0.98]), and being female (OR, 1.30 [95% CI, 1.13-1.48]). Those who required interpreter services (OR, 0.49 [95% CI, 0.25-0.95]) used a health benefits card (OR, 0.73 [95% CI, 0.59-0.92]) or had continuity of primary care visits (ie, with a consistent physician; OR, 0.78 [95% CI, 0.62-0.99]) were less likely to access mental health services. Among those who reported anxiety/depression, those who received mental health treatment had an increased risk of presenting to hospital (hazard ratio, 1.06 [95% CI, 1.01-1.11]) but no difference in survival (hazard ratio, 0.86 [95% CI, 0.58-1.27]). CONCLUSIONS: Nearly half of the people living with mood problems following stroke did not receive mental health treatment. We have highlighted subgroups who may benefit from targeted mood screening and factors that may improve treatment access.

Factors Associated With Transition From Community to Permanent Residential Aged Care Following Stroke: A Linked Registry Data Study.

BACKGROUND: Understanding factors that influence the transition to permanent residential aged care following a stroke or transient ischemic attack may inform strategies to support people to live at home longer. We aimed to identify the demographic, clinical, and system factors that may influence the transition from living in the community to permanent residential care in the 6 to 18 months following stroke/transient ischemic attack. METHODS: Linked data cohort analysis of adults from Queensland and Victoria aged ≥65 years and registered in the Australian Stroke Clinical Registry (2012-2016) with a clinical diagnosis of stroke/transient ischemic attack and living in the community in the first 6 months post-hospital discharge. Participant data were linked with primary care, pharmaceutical, aged care, death, and hospital data. Multivariable survival analysis was performed to determine demographic, clinical, and system factors associated with the transition to permanent residential care in the 6 to 18 months following stroke, with death modeled as a competing risk. RESULTS: Of 11 176 included registrants (median age, 77.2 years; 44% female), 520 (5%) transitioned to permanent residential care between 6 and 18 months. Factors most associated with transition included the history of urinary tract infections (subhazard ratio [SHR], 1.41 [95% CI, 1.16-1.71]), dementia (SHR, 1.66 [95% CI, 1.14-2.42]), increasing age (65-74 versus 85+ years; SHR, 1.75 [95% CI, 1.31-2.34]), living in regional Australia (SHR, 31 [95% CI, 1.08-1.60]), and aged care service approvals: respite (SHR, 4.54 [95% CI, 3.51-5.85]) and high-level home support (SHR, 1.80 [95% CI, 1.30-2.48]). Protective factors included being dispensed antihypertensive medications (SHR, 0.68 [95% CI, 0.53-0.87]), seeing a cardiologist (SHR, 0.72 [95% CI, 0.57-0.91]) following stroke, and less severe stroke (SHR, 0.71 [95% CI, 0.58-0.88]). CONCLUSIONS: Our findings provide an improved understanding of factors that influence the transition from community to permanent residential care following stroke and can inform future strategies designed to delay this transition.

Does a History of Cancer Influence the Effectiveness of Statins on Outcomes After Stroke?

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.

Real-World Effectiveness of Lipid-Lowering Medications on Outcomes after Stroke: Potential Implications of the New-User Design.

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.

Treatment with Multiple Therapeutic Classes of Medication Is Associated with Survival after 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.

Towards better reporting of the proportion of days covered method in cardiovascular medication adherence: A scoping review and new tool TEN-SPIDERS.

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.

The Allure of Big Data to Improve Stroke Outcomes: Review of Current Literature.

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. 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.

Utility of the Hospital Frailty Risk Score Derived From Administrative Data and the Association With Stroke Outcomes.

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 (2009­2013) 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 (1­5), intermediate-risk (5­15), 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 (ORadjusted, 1.05 [95% CI, 1.04 to 1.06), 90-day mortality (HRadjusted, 1.04 [95% CI, 1.03 to 1.05]), readmissions (ORadjusted, 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.

Greater Adherence to Secondary Prevention Medications Improves Survival After Stroke or Transient Ischemic Attack: A Linked Registry Study.

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 2010­June 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, 0.81­0.95]), 13% for statins (hazard ratio, 0.87 [95% CI, 0.80­0.95]), and 15% for nonaspirin antithrombotic agents (hazard ratio, 0.85 [95% CI, 0.79­0.93]). 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.

Assuming one dose per day yields a similar estimate of medication adherence in patients with stroke: An exploratory analysis using linked registry data.

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.

Factors Associated With 90-Day Readmission After Stroke or Transient Ischemic Attack: Linked Data From the Australian Stroke Clinical Registry.

Background and Purpose- Readmissions after stroke are common and appear to be associated with comorbidities or disability-related characteristics. In this study, we aimed to determine the patient and health-system level factors associated with all-cause and unplanned hospital readmission within 90 days after acute stroke or transient ischemic attack (TIA) in Australia. Methods- We used person-level linkages between data from the Australian Stroke Clinical Registry (2009-2013), hospital admissions data and national death registrations from 4 Australian states. Time to first readmission (all-cause or unplanned) for discharged patients was examined within 30, 90, and 365 days, using competing risks regression to account for deaths postdischarge. Covariates included age, stroke severity (ability to walk on admission), stroke type, admissions before stroke/TIA and the Charlson Comorbidity Index (derived from International Statistical Classification of Diseases and Related Health Problems, Tenth Revision, [Australian modified] coded hospital data in the preceding 5 years). Results- Among the 13 594 patients discharged following stroke/TIA (45% female; 65% ischemic stroke; 11% intracerebral hemorrhage; 4% undetermined stroke; and 20% TIA), 25% had an all-cause readmission and 15% had an unplanned readmission within 90 days. In multivariable analyses, the factors independently associated with a greater risk of unplanned readmission within 90 days were being female (subhazard ratio, 1.13 [95% CI, 1.03-1.24]), greater Charlson Comorbidity Index scores (subhazard ratio, 1.11 [95% CI, 1.09-1.12]) and having an admission ≤90 days before the index event (subhazard ratio, 1.85 [95% CI, 1.59-2.15]). Compared with being discharged to rehabilitation or aged care, those who were discharged directly home were more likely to have an unplanned readmission within 90 days (subhazard ratio, 1.44 [95% CI, 1.33-1.55]). These factors were similar for readmissions within 30 and 365 days. Conclusions- Apart from comorbidities and patient-level characteristics, readmissions after stroke/TIA were associated with discharge destination. Greater support for transition to home after stroke/TIA may be needed to reduce unplanned readmissions.

Disparities in Antihypertensive Prescribing After Stroke: Linked Data From the Australian Stroke Clinical Registry.

Background and Purpose- Despite evidence to support the prescription of antihypertensive medications before hospital discharge to promote medication adherence and prevent recurrent events, many patients with stroke miss out on these medications at discharge. We aimed to examine patient, clinical, and system-level differences in the prescription of antihypertensive medications at hospital discharge after stroke. Methods- Adults with acute ischemic stroke or intracerebral hemorrhage alive at discharge were included (years 2009-2013) from 39 hospitals participating in the Australian Stroke Clinical Registry. Patient comorbidities were identified using the International Statistical Classification of Diseases and Related Health Problems (Tenth Edition, Australian Modification) codes from the hospital admissions and emergency presentation data. The outcome variable and other system factors were derived from the Australian Stroke Clinical Registry dataset. Multivariable, multilevel logistic regression was used to examine factors associated with the prescription of antihypertensive medications at hospital discharge. Results- Of the 10 315 patients included, 79.0% (intracerebral hemorrhage, 74.1%; acute ischemic stroke, 79.8%) were prescribed antihypertensive medications at discharge. Prescription varied between hospital sites, with 6 sites >2 SDs below the national average for provision of antihypertensives at discharge. Prescription was also independently associated with patient and clinical factors including history of hypertension, diabetes mellitus, management in an acute stroke unit, and discharge to rehabilitation. In patients with acute ischemic stroke, females (odds ratio, 0.85; 95% CI, 0.76-0.94), those who had greater stroke severity (odds ratio, 0.81; 95% CI 0.72-0.92), or dementia (odds ratio, 0.65; 95% CI, 0.52-0.81) were less likely to be prescribed. Conclusions- Prescription of antihypertensive medications poststroke varies between hospitals and according to patient factors including age, sex, stroke severity, and comorbidity profile. Implementation of targeted quality improvement initiatives at local hospitals may help to reduce the variation in prescription observed.

Factors associated with mental health service access among Australian community-dwelling survivors of stroke.

PURPOSE: To describe types of mental health treatment accessed by community-based stroke survivors and factors associated with access. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.

Antihypertensive Medication Adherence and the Risk of Vascular Events and Falls After Stroke: A Real-World Effectiveness Study Using Linked Registry Data.

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 <80%. 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.