Comprehensive quality assessment for aphasia rehabilitation after stroke: protocol for a multicentre, mixed-methods study.

INTRODUCTION: People with aphasia following stroke experience disproportionally poor outcomes, yet there is no comprehensive approach to measuring the quality of aphasia services. The Meaningful Evaluation of Aphasia SeRvicES (MEASuRES) minimum dataset was developed in partnership with people with lived experience of aphasia, clinicians and researchers to address this gap. It comprises sociodemographic characteristics, quality indicators, treatment descriptors and outcome measurement instruments. We present a protocol to pilot the MEASuRES minimum dataset in clinical practice, describe the factors that hinder or support implementation and determine meaningful thresholds of clinical change for core outcome measurement instruments. METHODS AND ANALYSIS: This research aims to deliver a comprehensive quality assessment toolkit for poststroke aphasia services in four studies. A multicentre pilot study (study 1) will test the administration of the MEASuRES minimum dataset within five Australian health services. An embedded mixed-methods process evaluation (study 2) will evaluate the performance of the minimum dataset and explore its clinical applicability. A consensus study (study 3) will establish consumer-informed thresholds of meaningful change on core aphasia outcome constructs, which will then be used to establish minimal important change values for corresponding core outcome measurement instruments (study 4). ETHICS AND DISSEMINATION: Studies 1 and 2 have been registered with the Australian and New Zealand Clinical Trial Registry (ACTRN12623001313628). Ethics approval has been obtained from the Royal Brisbane and Women's Hospital (HREC/2023/MNHB/95293) and The University of Queensland (2022/HE001946 and 2023/HE001175). Study findings will be disseminated through peer-reviewed publications, conference presentations and engagement with relevant stakeholders including healthcare providers, policy-makers, stroke and rehabilitation audit and clinical quality registry custodians, consumer support organisations, and individuals with aphasia and their families.

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.

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.

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.

Costs of acute hospitalisation for stroke and transient ischaemic attack in Australia.

BACKGROUND: Stroke is a high-cost condition. Detailed patient-level assessments of the costs of care received and outcomes achieved provide useful information for organisation and optimisation of the health system. OBJECTIVES: To describe the costs of hospital care for stroke and transient ischaemic attack (TIA) and investigate factors associated with costs. METHODS: Retrospective cohort study using data from the Australian Stroke Clinical Registry (AuSCR) collected between 2009 and 2013 linked to hospital administrative data and clinical costing data in Queensland. Clinical costing data include standardised assignment of costs from hospitals that contribute to the National Hospital Costing programme. Patient-level costs for each hospital admission were described according to the demographic, clinical and treatment characteristics of patients. Multivariable median regression with clustering by hospital was used to determine factors associated with greater costs. RESULTS: Among 22 hospitals, clinical costing data were available for 3909 of 5522 patient admissions in the AuSCR (71%). Compared to those without clinical costing data, patients with clinical costing data were more often aged <65 years (30% with cost data vs 24% without cost data, p < 0.001) and male (56% with cost data vs 49% without cost data, p < 0.001). Median cost of an acute episode was $7945 (interquartile range $4176 to $14970) and the median length of stay was 5 days (interquartile range 2 to 10 days). The most expensive cost buckets were related to medical (n = 3897, median cost $1577), nursing (n = 3908, median cost $2478) and critical care (n = 434, median cost $3064). Factors associated with greater total costs were a diagnosis of intracerebral haemorrhage, greater socioeconomic position, in-hospital stroke and prior history of stroke. CONCLUSION: Medical and nursing costs were incurred by most patients admitted with stroke or TIA, and were relatively more expensive on average than other cost buckets such as imaging and allied health. IMPLICATIONS: Scaling this data linkage to national data collections may provide valuable insights into activity-based funding at public hospitals. Regular report of these costs should be encouraged to optimise economic evaluations.

Protocol of a randomized controlled trial investigating the effectiveness of Recovery-focused Community support to Avoid readmissions and improve Participation after Stroke (ReCAPS).

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.

Pilot randomised clinical trial of an eHealth, self-management support intervention (iVERVE) for stroke: feasibility assessment in survivors 12-24 months post-event.

BACKGROUND: Electronic communication is used in various populations to achieve health goals, but evidence in stroke is lacking. We pilot tested the feasibility and potential effectiveness of a novel personalised electronic self-management intervention to support person-centred goal attainment and secondary prevention after stroke. METHODS: A phase I, prospective, randomised controlled pilot trial (1:1 allocation) with assessor blinding, intention-to-treat analysis, and a process evaluation. Community-based survivors of stroke were recruited from participants in the Australian Stroke Clinical Registry (AuSCR) who had indicated their willingness to be contacted for research studies. Inclusion criteria include 1-2 years following hospital admission for stroke and living within 50 km of Monash University (Melbourne). Person-centred goals were set with facilitation by a clinician using a standardised template. The intervention group received electronic support messages aligned to their goals over 4 weeks. The control group received only 2-3 electronic administrative messages. Primary outcomes were study retention, goal attainment (assessed using Goal Attainment Scaling method) and satisfaction. Secondary outcomes were self-management (Health Education Impact Questionnaire: 8 domains), quality of life, mood and acceptability. RESULTS: Of 340 invitations sent from AuSCR, 73 responded, 68 were eligible and 57 (84%) completed the baseline assessment. At the goal-setting stage, 54/68 (79%) were randomised (median 16 months after stroke): 25 to intervention (median age 69 years; 40% female) and 29 to control (median age 68 years; 38% female). Forty-five (83%) participants completed the outcome follow-up assessment. At follow-up, goal attainment (mean GAS-T score ≥ 50) in the intervention group was achieved for goals related to function, participation and environment (control: environment only). Most intervention participants provided positive feedback and reported that the iVERVE messages were easy to understand (92%) and assisted them in achieving their goals (77%). We found preliminary evidence of non-significant improvements between the groups for most self-management domains (e.g. social integration and support: ß coefficient 0.34; 95% CI - 0.14 to 0.83) and several quality-of-life domains in favour of the intervention group. CONCLUSION: These findings support the need for further randomised effectiveness trials of the iVERVE program to be tested in people with new stroke. TRIAL REGISTRATION: ANZCTR, ACTRN12618001519246 . Registered on 11 September 2018-retrospectively registered.

Hospital Presentations in Long-Term Survivors of Stroke: Causes and Associated Factors in a Linked Data Study.

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

Maximising data value and avoiding data waste: a validation study in stroke research.

OBJECTIVES: To determine the feasibility of linking data from the Australian Stroke Clinical Registry (AuSCR), the National Death Index (NDI), and state-managed databases for hospital admissions and emergency presentations; to evaluate data completeness and concordance between datasets for common variables. DESIGN, SETTING, PARTICIPANTS: Cohort design; probabilistic/deterministic data linkage of merged records for patients treated in hospital for stroke or transient ischaemic attack from New South Wales, Queensland, Victoria, and Western Australia. MAIN OUTCOME MEASURES: Descriptive statistics for data matching success; concordance of demographic variables common to linked databases; sensitivity and specificity of AuSCR in-hospital death data for predicting NDI registrations. RESULTS: Data for 16 214 patients registered in the AuSCR during 2009-2013 were linked with one or more state datasets: 15 482 matches (95%) with hospital admissions data, and 12 902 matches (80%) with emergency department presentations data were made. Concordance of AuSCR and hospital admissions data exceeded 99% for sex, age, in-hospital death (each κ = 0.99), and Indigenous status (κ = 0.83). Of 1498 registrants identified in the AuSCR as dying in hospital, 1440 (96%) were also recorded by the NDI as dying in hospital. In-hospital death in AuSCR data had 98.7% sensitivity and 99.6% specificity for predicting in-hospital death in the NDI. CONCLUSION: We report the first linkage of data from an Australian national clinical quality disease registry with routinely collected data from several national and state government health datasets. Data linkage enriches the clinical registry dataset and provides additional information beyond that for the acute care setting and quality of life at follow-up, allowing clinical outcomes for people with stroke (mortality and hospital contacts) to be more comprehensively assessed.

The Quality of Discharge Care Planning in Acute Stroke Care: Influencing Factors and Association with Postdischarge Outcomes.

BACKGROUND: Comprehensive discharge planning is important for successful transitions from hospital to home after stroke. The aim of this study was to describe the quality of discharge planning received by patients discharged home from acute care, identify factors associated with a positive discharge experience, and assess the influence of discharge quality on outcomes. METHOD: Patients discharged to the community and registered in the Australian Stroke Clinical Registry in 2014 were invited to participate. Patient-perceived discharge quality was evaluated using the Prescriptions, Ready to re-enter community, Education, Placement, Assurance of safety, Realistic expectations, Empowerment, Directed to appropriate services questionnaire (recall at 3-9 months). Factors associated with higher discharge quality scores were identified and associations between quality scores of more than 80% and outcomes were investigated using multivariable, multilevel regression analyses. RESULTS: There were 200 of 434 eligible registrants who responded; responders and nonresponders were similar with respect to age, sex, and type of stroke. The average overall quality score was 73% (standard deviation: 21). However, only 18% received all aspects of discharge care planning. Quality scores of more than 80% were independently associated with receiving hospital specific information (odds ratio: 5.7, 95% confidence interval [CI]: 2.7, 12.4), and referral to a local support group (odds ratio: 2.5, 95% CI: 1.1, 5.9). Discharge quality scores of more than 80% were associated with higher European Quality of Life-5 Dimensions EQ-5D scores (coefficient: .1, 95% CI: .04, .2) and a reduction in the rate of unmet needs reported at 3-9 months postdischarge (incidence rate ratio: .5, 95% CI: .3, .7). CONCLUSION: We provide new information on the quality of discharge planning from acute care after stroke. Aspects of discharge planning that correlate with quality of care may reduce unmet needs and improve quality of life outcomes.

Influence of stroke coordinators on delivery of acute stroke care and hospital outcomes: An observational study.

Background Stroke coordinators have been inconsistently used in various countries to support stroke care in hospital. Aim To investigate the association between stroke coordinators and the provision of evidence-based care and patient outcomes in hospitals with acute stroke units. Methods Observational study using cross-sectional data from the 2015 National Acute Services Audit Program (Australia): including a retrospective medical record audit (40 records from each hospital) and a self-reported survey of organizational resources for stroke. Multilevel random effects logistic regression for patient outcomes including complications, independence on discharge, and death. Median regression for length of stay comparisons. Results A total of 109 hospitals submitted 4060 cases; 59 (54%) had a stroke coordinator. Compared with patients from stroke unit hospitals with no stroke coordinator ( N = 33, 1333 cases), patients in stroke unit hospitals with a stroke coordinator ( N = 53, 2072 cases) were more likely to receive clinical practices including rehabilitation therapy within 48 hours of initial assessment (88 vs. 82%, p < 0.001), risk factor modification advice (62 vs. 55%, p = 0.003) and receive a discharge care plan (65 vs. 48%, p < 0.001). No differences in complications, independence on discharge, or deaths were evident. Patients from hospitals with a stroke coordinator were more likely to access inpatient rehabilitation (adjusted odds ratio 1.8, 95% confidence interval 1.1-2.8) and have a reduced length of acute stay if discharged (median 14 h, p = 0.03). Conclusion Presence of stroke coordinators was associated with reduced length of stay and improved delivery of evidence-based care in hospitals with a stroke unit.

Evaluation of rural stroke services: does implementation of coordinators and pathways improve care in rural hospitals?

BACKGROUND AND PURPOSE: The quality of hospital care for stroke varies, particularly in rural areas. In 2007, funding to improve stroke care became available as part of the Rural Stroke Project (RSP) in New South Wales (Australia). The RSP included the employment of clinical coordinators to establish stroke units or pathways and protocols, and more clinical staff. We aimed to describe the effectiveness of RSP in improving stroke care and patient outcomes. METHODS: A historical control cohort design was used. Clinical practice and outcomes at 8 hospitals were compared using 2 medical record reviews of 100 consecutive ischemic or intracerebral hemorrhage patients ≥12 months before RSP and 3 to 6 months after RSP was implemented. Descriptive statistics and multivariable analyses of patient outcomes are presented. SAMPLE: pre-RSP n=750; mean age 74 (SD, 13) years; women 50% and post-RSP n=730; mean age 74 (SD, 13) years; women 46%. Many improvements in stroke care were found after RSP: access to stroke units (pre 0%; post 58%, P<0.001); use of aspirin within 24 hours of ischemic stroke (pre 59%; post 71%, P<0.001); use of care plans (pre 15%; post 63%, P<0.001); and allied health assessments within 48 hours (pre 65%; post 82% P<0.001). After implementation of the RSP, patients directly admitted to an RSP hospital were 89% more likely to be discharged home (adjusted odds ratio, 1.89; 95% confidence interval, 1.34-2.66). CONCLUSIONS: Investment in clinical coordinators who implemented organizational change, together with increased clinician resources, effectively improved stroke care in rural hospitals, resulting in more patients being discharged home.