ArticleInternational journal of population data science2019
Protocol for evaluation of enhanced models of primary care in the management of stroke and other chronic disease (PRECISE): A data linkage healthcare evaluation study.
Article in International journal of population data science, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
7 citing papers in PubMed, 14 citations in OpenAlex.
- General Practitioner Coordinated Multidisciplinary Care Improves Long-Term Survival following Stroke with Variation by Impairment.Neuroepidemiology · 2026Observational
- Chronic Disease Management to Enhance Medication Adherence Trajectories in Long-Term Survivors of Stroke: A Population-Based Cohort Study.Pharmacoepidemiology and drug safety · 2025Observational
- Protocol for a feasibility registry-based randomised controlled trial investigating a tailored follow-up service for stroke (A-LISTS).Pilot and feasibility studies · 2024Article
- Learning together for better health using an evidence-based Learning Health System framework: a case study in stroke.BMC medicine · 2024Article
- Cost-Effectiveness of a Government Policy to Incentivise Chronic Disease Management following Stroke: A Modelling Study.Neuroepidemiology · 2024Article
- Developing a linked electronic health record derived data platform to support research into healthy ageing.International journal of population data science · 2023Article
- Are Medicare Funded Multidisciplinary Care Policies Being Claimed in accordance to Rehabilitation Needs in Patients with Stroke?Reviews in cardiovascular medicine · 2022Article
Corrections and comments
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Authors and funding
10 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionThe growing burden of chronic diseases means some governments have been providing financial incentives for multidisciplinary care and self-management support delivered within primary care. Currently, population-based evaluations of the effectiveness of these policies are lacking.
aimTo outline the methodological approach for our study that is designed to evaluate the effectiveness (including cost) of primary care policies for chronic diseases in Australia using stroke as a case study.
methodsPerson-level linkages will be undertaken between registrants from the Australian Stroke Clinical Registry (AuSCR) and (i) Government-held Medicare Australia claims data, to identify receipt or not of chronic disease management and care coordination primary care items; (ii) state government-held hospital data, to define outcomes; and (iii) government-held pharmaceutical and aged care claims data, to define covariates. N=1500 randomly selected AuSCR registrants will be sent surveys to obtain patient experience information. In Australia, unique identifiers are unavailable. Therefore, personal-identifiers will be submitted to government data linkage units. Researchers will merge the de-identified datasets for analysis using a project identifier. An economic evaluation will also be undertaken. ANALYSIS: The index event will be the first stroke recorded in the AuSCR. Multivariable competing risks Poisson regression for multiple events, adjusted by a propensity score, will be used to test for differences in the rates of hospital presentations and medication adherence for different care (policy) types. Our estimated sample size of 25,000 patients will provide 80% estimated power (ɑ>0.05) to detect a 6-8% difference in rates. The incremental costs per Quality-adjusted life years gained of community-based care following the acute event will be estimated from a health sector perspective.
conclusionCompletion of this study will provide a novel and comprehensive evaluation of the effectiveness and cost-effectiveness of Australian primary care policies. Its success will enable us to highlight the value of data-linkage for this type of research.
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