High-Intensity Aphasia Therapy Is Cost-Effective in People With Poststroke Aphasia: Evidence From the COMPARE Trial.

BACKGROUND: Evidence from systematic reviews confirms that speech and language interventions for people with aphasia during the chronic phase after stroke (>6 months) improve word retrieval, functional communication, and communication-related quality of life. However, there is limited evidence of their cost-effectiveness. We aimed to estimate the cost per quality-adjusted life year gained from 2 speech and language therapies compared with usual care in people with aphasia during the chronic phase (median, 2.9 years) after stroke. METHODS: A 3-arm, randomized controlled trial compared constraint-induced aphasia therapy plus (CIAT-Plus) and multimodality aphasia therapy (M-MAT) with usual care in 216 people with chronic aphasia. Participants were administered a standardized questionnaire before intervention and at 12 weeks after the 2-week intervention/control period to ascertain health service utilization, employment changes, and informal caregiver burden. Unit prices from Australian sources were used to estimate costs in 2020. Quality-adjusted life years were estimated using responses to the EuroQol-5 Dimension-3 Level questionnaire. To test uncertainty around the differences in costs and outcomes between groups, bootstrapping was used with the cohorts resampled 1000 times. RESULTS: Overall 201/216 participants were included (mean age, 63 years, 29% moderate or severe aphasia, 61 usual care, 70 CIAT-Plus, 70 M-MAT). There were no statistically significant differences in mean total costs ($13 797 usual care, $17 478 CIAT-Plus, $11 113 M-MAT) and quality-adjusted life years (0.19 usual care, 0.20 CIAT-Plus, 0.20 M-MAT) between groups. In bootstrapped analysis of CIAT-Plus, 21.5% of iterations were likely to result in better outcomes and be cost saving (dominant) compared with usual care. In contrast, 72.4% of iterations were more favorable for M-MAT than usual care. CONCLUSIONS: We observed that both treatments, but especially M-MAT, may result in better outcomes at an acceptable additional cost, or potentially with cost savings. These findings are relevant in advocating for the use of these therapies for chronic aphasia after stroke.

High-Intensity Aphasia Intervention Is Minimally Fatiguing in Chronic Aphasia: An Analysis of Participant Self-Ratings From a Large Randomized Controlled Trial.

BACKGROUND: High-intensity therapy is recommended in current treatment guidelines for chronic poststroke aphasia. Yet, little is known about fatigue levels induced by treatment, which could interfere with rehabilitation outcomes. We analyzed fatigue experienced by people with chronic aphasia (>6 months) during high-dose interventions at 2 intensities. METHODS: A retrospective observational analysis was conducted on self-rated fatigue levels of people with chronic aphasia (N=173) collected during a previously published large randomized controlled trial of 2 treatments: constraint-induced aphasia therapy plus and multi-modality aphasia therapy. Interventions were administered at a higher intensity (30 hours over 2 weeks) or lower intensity (30 hours over 5 weeks). Participants rated their fatigue on an 11-point scale before and after each day of therapy. Data were analyzed using Bayesian ordinal multilevel models. Specifically, we considered changes in self-rated participant fatigue across a therapy day and over the intervention period. RESULTS: Data from 144 participants was analyzed. Participants were English speakers from Australia or New Zealand (mean age, 62 [range, 18-88] years) with 102 men and 42 women. Most had mild (n=115) or moderate (n=52) poststroke aphasia. Median ratings of the level of fatigue by people with aphasia were low (1 on a 0-10-point scale) at the beginning of the day. Ratings increased slightly (+1.0) each day after intervention, with marginally lower increases in the lower intensity schedule. There was no evidence of accumulating fatigue over the 2- or 5-week interventions. CONCLUSIONS: Findings suggest that intensive intervention was not associated with large increases in fatigue for people with chronic aphasia enrolled in the COMPARE trial (Constraint-Induced or Multimodality Personalised Aphasia Rehabilitation). Fatigue did not change across the course of the intervention. This study provides evidence that intensive treatment was minimally fatiguing for stroke survivors with chronic aphasia, suggesting that fatigue is not a barrier to high-intensity treatment.

Learning together for better health using an evidence-based Learning Health System framework: a case study in stroke.

BACKGROUND: In the context of expanding digital health tools, the health system is ready for Learning Health System (LHS) models. These models, with proper governance and stakeholder engagement, enable the integration of digital infrastructure to provide feedback to all relevant parties including clinicians and consumers on performance against best practice standards, as well as fostering innovation and aligning healthcare with patient needs. The LHS literature primarily includes opinion or consensus-based frameworks and lacks validation or evidence of benefit. Our aim was to outline a rigorously codesigned, evidence-based LHS framework and present a national case study of an LHS-aligned national stroke program that has delivered clinical benefit. MAIN TEXT: Current core components of a LHS involve capturing evidence from communities and stakeholders (quadrant 1), integrating evidence from research findings (quadrant 2), leveraging evidence from data and practice (quadrant 3), and generating evidence from implementation (quadrant 4) for iterative system-level improvement. The Australian Stroke program was selected as the case study as it provides an exemplar of how an iterative LHS works in practice at a national level encompassing and integrating evidence from all four LHS quadrants. Using this case study, we demonstrate how to apply evidence-based processes to healthcare improvement and embed real-world research for optimising healthcare improvement. We emphasize the transition from research as an endpoint, to research as an enabler and a solution for impact in healthcare improvement. CONCLUSIONS: The Australian Stroke program has nationally improved stroke care since 2007, showcasing the value of integrated LHS-aligned approaches for tangible impact on outcomes. This LHS case study is a practical example for other health conditions and settings to follow suit.

How Much Does Dysphagia Cost? Understanding the Additional Costs of Dysphagia for New Zealand in Patients Hospitalised with Stroke.

INTRODUCTION: Dysphagia (i.e., disordered swallowing) is a consequence of stroke. Existing literature on the marginal cost of dysphagia after stroke is limited and ignores long-term impacts. Our aim was to determine the marginal 12-month cost attributable to dysphagia, including health-related quality of life (HRQoL) impacts, among patients hospitalised with stroke in New Zealand. METHODS: Secondary analysis of observational data from the REGIONS Care study, a national study from New Zealand of consecutively hospitalised patients with acute stroke between May 1, 2018, and October 30, 2018, including an outcome survey at 12 months among those who provided consent. Patients were identified as dysphagic if they received a swallow screen in hospital resulting in a speech language therapist review. Patients that required a nasogastric feeding tube in hospital were classified as "severe." Optimal linear propensity score matching was utilised to provide a group of patients to compare with stroke and dysphagia. All costs were converted to 2021NZD. RESULTS: Overall, of the 2,379 patients in the REGIONS cohort (51% male, median age: 78), 40% (944/2,379) were dysphagic (52% male, median age: 78), and 5% (111/2,379) were classified as severely dysphagic. Within 12 months of hospital discharge, dysphagia reduced HRQoL overall by 0.06 index points (95% CI: 0.028-0.100), and severe dysphagia by 0.12 index points (95% CI: 0.03-0.20). The estimated marginal 12-month cost attributable to stroke-related dysphagia was NZD 24,200 on average per patient. This estimate includes the additional hospitalisation costs (NZD 16,100), community rehabilitation services (NZD 570), hospital level aged residential care (NZD 4,030), and reduced HRQoL (NZD 3,470) over a 12-month period post-hospital discharge. The overall total marginal cost for those with severe dysphagia was NZD 34,000 per patient. CONCLUSION: We report cost estimates to 12 months from a national perspective on the additional costs and HRQoL outcomes of dysphagia for people hospitalised with stroke in New Zealand. Findings provide a novel contribution internationally since few prior studies have extended beyond the acute hospital phase of care. By quantifying the economic burden, we provide information to decision makers to improve dysphagia management strategies and ultimately enhance the overall HRQoL for people with stroke and dysphagia.

Cost-Effectiveness of an Individualised Management Program after Stroke: A Trial-Based Economic Evaluation.

INTRODUCTION: Evidence on the cost-effectiveness of comprehensive post-stroke programs is limited. We assessed the cost-effectiveness of an individualised management program (IMP) for stroke or transient ischaemic attack (TIA). METHODS: A cost-utility analysis alongside a randomised controlled trial with a 24-month follow-up, from both societal and health system perspectives, was conducted. Adults with stroke/TIA discharged from hospitals were randomised by primary care practice to receive either usual care (UC) or an IMP in addition to UC (intervention). An IMP included stroke-specific nurse-led education and a specialist review of care plans at baseline, 3 months, and 12 months, and telephone reviews by nurses at 6 months and 18 months. Costs were expressed in 2021 Australian dollars (AUD). Costs and quality-adjusted life years (QALYs) beyond 12 months were discounted by 5%. The probability of cost-effectiveness of the intervention was determined by quantifying 10,000 bootstrapped iterations of incremental costs and QALYs below the threshold of AUD 50,000/QALY. RESULTS: Among the 502 participants (65% male, median age 69 years), 251 (50%) were in the intervention group. From a health system perspective, the incremental cost per QALY gained was AUD 53,175 in the intervention compared to the UC group, and the intervention was cost-effective in 46.7% of iterations. From a societal perspective, the intervention was dominant in 52.7% of iterations, with mean per-person costs of AUD 49,045 and 1.352 QALYs compared to mean per-person costs of AUD 51,394 and 1.324 QALYs in the UC group. The probability of the cost-effectiveness of the intervention, from a societal perspective, was 60.5%. CONCLUSIONS: Care for people with stroke/TIA using an IMP was cost-effective from a societal perspective over 24 months. Economic evaluations of prevention programs need sufficient time horizons and consideration of costs beyond direct healthcare utilisation to demonstrate their value to society.

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.

Age and sex disparities in cardiovascular risk factor management prior to stroke: Linked registry and general practice data.

INTRODUCTION: There is limited evidence about the management of cardiovascular risk factors within 12 months before stroke/transient ischaemic attack (TIA) in Australian general practices. We evaluated whether age and sex disparities in cardiovascular risk factor management for primary prevention exist in general practice. METHODS: A retrospective cohort study using data from the Australian Stroke Clinical Registry (2014-2018) linked with general practice data from three primary health networks in Victoria, Australia. We included adults who had ≥2 encounters with a general practitioner within 12 months immediately before the first stroke/TIA. Cardiovascular risk factor management within 12 months before stroke/TIA was evaluated in terms of: assessment of risk factors (blood pressure [BP], serum lipids, blood glucose, body weight); prescription of prevention medications (BP, lipid-, glucose-lowering, antithrombotic agents); and attainment of risk factor targets. RESULTS: Of 2,880 patients included (median age 76.5 years, 48.4% women), 80.9% were assessed for BP, 49.9% serum lipids, 46.8% blood glucose, and 39.3% body weight. Compared to patients aged 65-84 years, those aged <65 or ≥85 years were less often assessed for risk factors, with women aged ≥85 years assessed for significantly fewer risk factors than their male counterparts. The most prescribed prevention medications were BP-lowering (64.9%) and lipid-lowering agents (42.0%). There were significant sex differences among those aged <65 years (34.7% women vs. 40.2% men) and ≥85 years (34.0% women vs. 44.3% men) for lipid-lowering agents. Risk factor target attainment was generally poorer in men than women, especially among those aged <65 years. CONCLUSION: Age-sex disparity exists in risk factor management for primary prevention in general practice, and this was more pronounced among younger patients and older women.

How registry data are used to inform activities for stroke care quality improvement across 55 countries: A cross-sectional survey of Registry of Stroke Care Quality (RES-Q) hospitals.

BACKGROUND AND PURPOSE: The Registry of Stroke Care Quality (RES-Q) is a worldwide quality improvement data platform that captures performance and quality measures, enabling standardized comparisons of hospital care. The aim of this study was to determine if, and how, RES-Q data are used to influence stroke quality improvement and identify the support and educational needs of clinicians using RES-Q data to improve stroke care. METHODS: A cross-sectional self-administered online survey was administered (October 2021-February 2022). Participants were RES-Q hospital local coordinators responsible for stroke data collection. Descriptive statistics are presented. RESULTS: Surveys were sent to 1463 hospitals in 74 countries; responses were received from 358 hospitals in 55 countries (response rate 25%). RES-Q data were used "always" or "often" to: develop quality improvement initiatives (n = 213, 60%); track stroke care quality over time (n = 207, 58%); improve local practice (n = 191, 53%); and benchmark against evidence-based policies, procedures and/or guidelines to identify practice gaps (n = 179, 50%). Formal training in the use of RES-Q tools and data were the most frequent support needs identified by respondents (n = 165, 46%). Over half "strongly agreed" or "agreed" that to support clinical practice change, education is needed on: (i) using data to identify evidence-practice gaps (n = 259, 72%) and change clinical practice (n = 263, 74%), and (ii) quality improvement science and methods (n = 255, 71%). CONCLUSION: RES-Q data are used for monitoring stroke care performance. However, to facilitate their optimal use, effective quality improvement methods are needed. Educating staff in quality improvement science may develop competency and improve use of data in practice.

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.

The Quality in Acute Stroke Care (QASC) global scale-up using a cascading facilitation framework: a qualitative process evaluation.

BACKGROUND: Variation in hospital stroke care is problematic. The Quality in Acute Stroke (QASC) Australia trial demonstrated reductions in death and disability through supported implementation of nurse-led, evidence-based protocols to manage fever, hyperglycaemia (sugar) and swallowing (FeSS Protocols) following stroke. Subsequently, a pre-test/post-test study was conducted in acute stroke wards in 64 hospitals in 17 European countries to evaluate upscale of the FeSS Protocols. Implementation across countries was underpinned by a cascading facilitation framework of multi-stakeholder support involving academic partners and a not-for-profit health organisation, the Angels Initiative (the industry partner), that operates to promote evidence-based treatments in stroke centres. .We report here an a priori qualitative process evaluation undertaken to identify factors that influenced international implementation of the FeSS Protocols using a cascading facilitation framework. METHODS: The sampling frame for interviews was: (1) Executives/Steering Committee members, consisting of academics, the Angels Initiative and senior project team, (2) Angel Team leaders (managers of Angel Consultants), (3) Angel Consultants (responsible for assisting facilitation of FeSS Protocols into multiple hospitals) and (4) Country Co-ordinators (senior stroke nurses with country and hospital-level responsibilities for facilitating the introduction of the FeSS Protocols). A semi-structured interview elicited participant views on the factorsthat influenced engagement of stakeholders with the project and preparation for and implementation of the FeSS Protocol upscale. Interviews were recorded, transcribed verbatim and analysed inductively within NVivo. RESULTS: Individual (n = 13) and three group interviews (3 participants in each group) were undertaken. Three main themes with sub-themes were identified that represented key factors influencing upscale: (1) readiness for change (sub-themes: negotiating expectations; intervention feasible and acceptable; shared goal of evidence-based stroke management); (2) roles and relationships (sub-themes: defining and establishing roles; harnessing nurse champions) and (3) managing multiple changes (sub-themes: accommodating and responding to variation; more than clinical change; multi-layered communication framework). CONCLUSION: A cascading facilitation model involving a partnership between evidence producers (academic partners), knowledge brokers (industry partner, Angels Initiative) and evidence adopters (stroke clinicians) overcame multiple challenges involved in international evidence translation. Capacity to manage, negotiate and adapt to multi-level changes and strategic engagement of different stakeholders supported adoption of nurse-initiated stroke protocols within Europe. This model has promise for other large-scale evidence translation programs.

Care Transition Interventions to Improve Stroke Outcomes: Evidence Gaps in Underserved and Minority Populations.

In many countries hospital length of stay after an acute stroke admission is typically just a few days, therefore, most of a person's recovery from stroke occurs in the community. Care transitions, which occur when there is a change in, or handoff between 2 different care settings or providers, represent an especially vulnerable period for patients and caregivers. For some patients with stroke the return home is associated with substantial practical, psychosocial, and health-related challenges leading to substantial burden for the individual and caregiver. Underserved and minority populations, because of their exposure to poor environmental, social, and economic conditions, as well as structural racism and discrimination, are especially vulnerable to the problems of complicated care transitions which in turn, can negatively impact stroke recovery. Overall, there remain significant unanswered questions about how to promote optimal recovery in the post-acute care period, particularly for those from underserved communities. Evidence is limited on how best to support patients after they have returned home where they are required to navigate the chronic stages of stroke with little direct support from health professionals.

Stroke Learning Health Systems: A Topical Narrative Review With Case Examples.

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.

A Scoping Review of mHealth Interventions for Secondary Prevention of Stroke: Implications for Policy and Practice.

Secondary prevention is a major priority for those living with stroke and may be improved through the use of mobile Health (mHealth) interventions. While evidence for the effectiveness of mHealth interventions for secondary prevention of stroke is growing, little attention has been given to the translation of these interventions into real-world use. In this review, we aimed to provide an update on the effectiveness of mHealth interventions for secondary prevention of stroke, and investigate their translation into real-world use. Four electronic databases and the gray literature were searched for randomized controlled trials of mHealth interventions for secondary prevention of stroke published between 2010 and 2023. Qualitative and mixed-methods evaluations of the trials were also included. Data were extracted regarding study design, population, mHealth technology involved, the intervention, and outcomes. Principal researchers from these trials were also contacted to obtain further translational information. From 1151 records, 13 randomized controlled trials and 4 evaluations were identified; sample sizes varied widely (median, 56; range, 24-4298). Short message service messages (9/13) and smartphone applications (6/13) were the main technologies used to deliver interventions. Primary outcomes of feasibility of the intervention were achieved in 4 trials, and primary outcomes of changes in risk factors, lifestyle behaviors, and adherence to medication improved in 6 trials. Only 1 trial had a hard end point (ie, stroke recurrence) as a primary outcome, and no significant differences were observed between groups. There was evidence for only 1 intervention being successfully translated into real-world use. Further evidence is required on the clinical effectiveness of mHealth interventions for preventing recurrent stroke, and the associated delivery costs and cost-effectiveness, before adoption into real-world settings.

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.

Comparison of Stroke Care Costs in Urban and Nonurban Hospitals and Its Association With Outcomes in New Zealand: A Nationwide Economic Evaluation.

BACKGROUND: Although geographical differences in treatment and outcomes after stroke have been described, we lack evidence on differences in the costs of treatment between urban and nonurban regions. Additionally, it is unclear whether greater costs in one setting are justified given the outcomes achieved. We aimed to compare costs and quality-adjusted life years in people with stroke admitted to urban and nonurban hospitals in New Zealand. METHODS: Observational study of patients with stroke admitted to the 28 New Zealand acute stroke hospitals (10 in urban areas) recruited between May and October 2018. Data were collected up to 12 months poststroke including treatments in hospital, inpatient rehabilitation, other health service utilization, aged residential care, productivity, and health-related quality of life. Costs in New Zealand dollars were estimated from a societal perspective and assigned to the initial hospital that patients presented to. Unit prices for 2018 were obtained from government and hospital sources. Multivariable regression analyses were conducted when assessing differences between groups. RESULTS: Of 1510 patients (median age 78 years, 48% female), 607 presented to nonurban and 903 to urban hospitals. Mean hospital costs were greater in urban than nonurban hospitals ($13 191 versus $11 635, P=0.002), as were total costs to 12 months ($22 381 versus $17 217, P<0.001) and quality-adjusted life years to 12 months (0.54 versus 0.46, P<0.001). Differences in costs and quality-adjusted life years remained between groups after adjustment. Depending on the covariates included, costs per additional quality-adjusted life year in the urban hospitals compared to the nonurban hospitals ranged from $65 038 (unadjusted) to $136 125 (covariates: age, sex, prestroke disability, stroke type, severity, and ethnicity). CONCLUSIONS: Better outcomes following initial presentation to urban hospitals were associated with greater costs compared to nonurban hospitals. These findings may inform greater targeted expenditure in some nonurban hospitals to improve access to treatment and optimize outcomes.

Interventions for the uptake of evidence-based recommendations in acute stroke settings.

BACKGROUND: There is a growing body of research evidence to guide acute stroke care. Receiving care in a stroke unit improves access to recommended evidence-based therapies and patient outcomes. However, even in stroke units, evidence-based recommendations are inconsistently delivered by healthcare workers to patients with stroke. Implementation interventions are strategies designed to improve the delivery of evidence-based care. OBJECTIVES: To assess the effects of implementation interventions (compared to no intervention or another implementation intervention) on adherence to evidence-based recommendations by health professionals working in acute stroke units. Secondary objectives were to assess factors that may modify the effect of these interventions, and to determine if single or multifaceted strategies are more effective in increasing adherence with evidence-based recommendations. SEARCH METHODS: We searched CENTRAL, MEDLINE, Embase, CINAHL, Joanna Briggs Institute and ProQuest databases to 13 April 2022. We searched the grey literature and trial registries and reviewed reference lists of all included studies, relevant systematic reviews and primary studies; contacted corresponding authors of relevant studies and conducted forward citation searching of the included studies. There were no restrictions on language and publication date. SELECTION CRITERIA: We included randomised trials and cluster-randomised trials. Participants were health professionals providing care to patients in acute stroke units; implementation interventions (i.e. strategies to improve delivery of evidence-based care) were compared to no intervention or another implementation intervention. We included studies only if they reported on our primary outcome which was quality of care, as measured by adherence to evidence-based recommendations, in order to address the review aim. DATA COLLECTION AND ANALYSIS: Two review authors independently selected studies for inclusion, extracted data and assessed risk of bias and certainty of evidence using GRADE. We compared single implementation interventions to no intervention, multifaceted implementation interventions to no intervention, multifaceted implementation interventions compared to single implementation interventions and multifaceted implementation interventions to another multifaceted intervention. Our primary outcome was adherence to evidence-based recommendations. MAIN RESULTS: We included seven cluster-randomised trials with 42,489 patient participants from 129 hospitals, conducted in Australia, the UK, China, and the Netherlands. Health professional participants (numbers not specified) included nursing, medical and allied health professionals. Interventions in all studies included implementation strategies targeting healthcare workers; three studies included delivery arrangements, no studies used financial arrangements or governance arrangements. Five trials compared a multifaceted implementation intervention to no intervention, two trials compared one multifaceted implementation intervention to another multifaceted implementation intervention. No included studies compared a single implementation intervention to no intervention or to a multifaceted implementation intervention. Quality of care outcomes (proportions of patients receiving evidence-based care) were included in all included studies. All studies had low risks of selection bias and reporting bias, but high risk of performance bias. Three studies had high risks of bias from non-blinding of outcome assessors or due to analyses used. We are uncertain whether a multifaceted implementation intervention leads to any change in adherence to evidence-based recommendations compared with no intervention (risk ratio (RR) 1.73; 95% confidence interval (CI) 0.83 to 3.61; 4 trials; 76 clusters; 2144 participants, I2 =92%, very low-certainty evidence). Looking at two specific processes of care, multifaceted implementation interventions compared to no intervention probably lead to little or no difference in the proportion of patients with ischaemic stroke who received thrombolysis (RR 1.14, 95% CI 0.94 to 1.37, 2 trials; 32 clusters; 1228 participants, moderate-certainty evidence), but probably do increase the proportion of patients who receive a swallow screen within 24 hours of admission (RR 6.76, 95% CI 4.44 to 10.76; 1 trial; 19 clusters; 1,804 participants; moderate-certainty evidence). Multifaceted implementation interventions probably make little or no difference in reducing the risk of death, disability or dependency compared to no intervention (RR 0.93, 95% CI 0.85 to 1.02; 3 trials; 51 clusters ; 1228 participants; moderate-certainty evidence), and probably make little or no difference to hospital length of stay compared with no intervention (difference in absolute change 1.5 days; 95% CI -0.5 to 3.5; 1 trial; 19 clusters; 1804 participants; moderate-certainty evidence). We do not know if a multifaceted implementation intervention compared to no intervention result in changes to resource use or health professionals' knowledge because no included studies collected these outcomes. AUTHORS' CONCLUSIONS: We are uncertain whether a multifaceted implementation intervention compared to no intervention improves adherence to evidence-based recommendations in acute stroke settings, because the certainty of evidence is very low.

The Excess Costs of Hospitalization for Acute Stroke in People With Communication Impairment: A Stroke123 Data Linkage Substudy.

OBJECTIVE: To describe the costs of hospital care for acute stroke for patients with aphasia or dysarthria. DESIGN: Observational study from the Stroke123 project. SETTING: Data from patients admitted with stroke (2009-2013) from 22 hospitals in Queensland participating in the Australian Stroke Clinical Registry (AuSCR) were linked to administrative datasets. PARTICIPANTS: Communication impairments were identified using International Classification of Diseases, 10th Revision, Australian Modification codes. Overall, 1043 of 4195 (25%) patients were identified with aphasia (49% were women; median age 78 years; 83% with ischemic stroke), and 1005 (24%) with dysarthria (42% were women; median age 76 years; 85% with ischemic stroke). INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Linked patient-level, hospital clinical costing related to the stroke, were adjusted to 2013/2014 Australian dollars (AU$, US$ conversion x 0.691) using recommended national price indices and multivariable regression analysis with clustering by hospital performed. RESULTS: Compared with patients without aphasia, the median hospital costs/patient were greater for those with aphasia for medical (aphasia AU$2273 vs AU$1727, P<.001), nursing (aphasia AU$3829 vs AU$2748, P<.001) and allied health services (aphasia AU$1138 vs AU$720, P<.001). Similarly, costs were greater for patients with dysarthria compared with those without dysarthria. Adjusted median total costs were AU$2882 greater for patients with aphasia compared with patients without aphasia (95% confidence interval, AU$1880-3884), and AU$843 greater for patients with dysarthria compared with those without dysarthria (95% confidence interval, AU$-301 to 1987). CONCLUSIONS: People with communication impairment after stroke incur greater hospital costs, in particular for medical, allied health, and nursing resources.