Suchergebnisse

Background: Health data sharing is important for monitoring diseases, policy and practice, and planning health services. If health data are used for secondary purposes, information needs to be provided to assist in reuse. Objectives: To review government health information asset websites to ascertain the extent of readily available, explanatory documentation for researcher sharing and reuse of these data. Method: Documentary analysis was undertaken on selected Victorian Government health information assets' websites in Australia. Data were obtained on nine information-categories: data custodian; data context; data dictionary; quality controls; data quality; limitations; access process; privacy/confidentiality/security and research requests/outputs. Information-categories were compared by dataset type (administrative or population-health) and by curating organisation (government or other agency). Descriptive statistics were used. Results: The majority of the 25 websites examined provided information on data custodian (96%) and data context (92%). Two-thirds reported access process (68%) and privacy/confidentiality/security information (64%). Compared with population-health websites, administrative dataset websites were more likely to provide access to a data dictionary (67% vs 50%) and information on quality controls (56% vs 44%), but less likely to provide information on the access process (56% vs 75%) and on research requests/outputs (0% vs 56%, p = 0.024). Compared with government-curated websites, other agency websites were more likely to provide information on research requests/outputs (80% vs 7%, p < 0.001). Conclusion: There is inconsistent explanatory documentation available for researchers for reuse of Victorian Government health datasets. Importantly, there is insufficient information on data quality or dataset limitations. Research-curated dataset websites are significantly more transparent in displaying research requests or outputs.

Background Governments have responsibility for ensuring the quality and fitness-for-purpose of personal health data provided to them. While these health information assets are used widely for research, this secondary usage has received minimal research attention. Objective This study aimed to investigate the secondary uses, in research, of population health and administrative datasets (information assets) of the Department of Health (DoH), Victoria, Australia. The objectives were to (i) identify research based on these datasets published between 2008 and 2020; (ii) describe the data quality studies published between 2008 and 2020 for each dataset and (iii) evaluate "fitness-for-purpose" of the published research. Method Using a modified scoping review, research publications from 2008 to 2020 based on information assets related to health service provision and containing person-level data were reviewed. Publications were summarised by data quality and purpose-categories based on a taxonomy of data use. Fitness-for-purpose was evaluated by comparing the publicly stated purpose(s) for which each information asset was collected, with the purpose(s) assigned to the published research. Results Of the >1000 information assets, 28 were utilised in 756 publications: 54% were utilised for general research purposes, 14% for patient safety, 10% for quality of care and 39% included data quality-related publications. Almost 85% of publications used information assets that were fit-for-purpose. Conclusion The DoH information assets were used widely for secondary purposes, with the majority identified as fit-for-purpose. We recommend that data custodians, including governments, provide information on data quality and transparency on data use of their health information assets.

IntroductionStroke is a leading cause of death and disability. Since 2012, our innovative national data linkage program, has enabled the successful linkage of data from the Australian Stroke Clinical Registry (AuSCR) with national and state-based datasets to investigate the continuum of stroke care and associated outcomes.
Objectives and ApproachUsing stroke as a case study, in this symposium we will describe the use of linked data to undertake clinical and economic evaluations and contribute new knowledge for policy and practice. We have undertaken a range of iterative and innovative projects linking the AuSCR (used now in >80 public hospitals across Australia with follow-up survey of patients between 90-180 days) with various administrative datasets. Linkages with the National Death Index, inpatient admissions and emergency presentations, Pharmaceutical Benefits Scheme (PBS), Medicare Benefits Schedule (MBS), Aged Care services; Ambulance Victoria, Australian Rehabilitation Outcomes Centre and general practice network datasets (POLAR) have been achieved.
ResultsThe symposium will provide case studies and results from four data linkage projects involving the AuSCR: 1) Stroke123 (NHMRC: #1034415), a study to investigate the impact of quality of acute care on admission/emergency presentations and survival; 2) PRECISE (NHMRC:#1141848), a study to evaluate models of primary care involving linkages with PBS/MBS, aged care services and admissions/emergency data; 3) AMBULANCE: a study to investigate how pre-hospital care affects acute stroke care involving linkages with the ambulance and admissions/emergency datasets; and 4) POLAR: a study to understand the long-term management of stroke involving linkages with primary health data.
Conclusion / ImplicationsThe National Stroke Data Linkage Program has been visionary and remains highly contemporary in the field of linked data. A unique feature of this program is the active participation of clinicians and policy-makers to ensure the evidence generated have direct benefits for accelerating change in practice and informing policy.

IntroductionImprovement in access to reperfusion therapy and reductions in treatment delays requires coordination of multiple systems and services including a well-organised and streamlined pre-hospital care system.
Objectives and ApproachOur objective is to examine pre-hospital and hospital factors that influence long-term outcomes in patients with stroke. We linked and merged patient-level data from the Australian Stroke Clinical Registry (AuSCR) to Ambulance Victoria (AV), hospital administrative datasets (Victorian Admitted Episodes Data; VAED) and emergency department data (Victorian Emergency Minimum Dataset; VEMD) using probabilistic, iterative methods. Logistic regression models were used to determine clinical factors associated with access to evidence-based treatments.
Results7,373 episodes in the AuSCR were available for linkage, of which 4,569 (62%) were matched with AV records (58% male, median age 72 years). Of these 4,569 matched records, 4,159 (58% male, median age 73 years) had a record in the VAED or VEMD. Stroke or transient ischaemic attack was suspected for 68% of patients by paramedics based on the AV data. Highest transport priority was used for 64% of patients. Patients suspected of stroke by paramedics were more likely to be treated in stroke unit (unadjusted odds ratio, 1.72; 1.47, 2.01) and more likely to receive thrombolysis if ischaemic stroke (unadjusted odd ratio: 4.64, 3.47, 6.20).
Conclusion/ImplicationsLinkage of these administrative data with the AuSCR provide the opportunity to interrogate a range of questions to inform policy and practice of acute stroke care. Future analyses will investigate patient (such as comorbidities), clinical and system factors that influence provision of evidence-based care for patients with stroke and whether these influence outcomes at 6 months after stroke.

Background Administrative data are used extensively for research purposes, but there remains limited information on the quality of these data for identifying comorbidities related to stroke. Objective To compare the prevalence of comorbidities of stroke identified using International Classification Diseases, Australian Modification (ICD-10-AM) or Anatomical Therapeutic Chemical codes, with those from (i) self-reported data and (ii) published studies. Method The cohort included patients with stroke or transient ischaemic attack admitted to hospitals (2012–2016; Victoria and Queensland) in the Australian Stroke Clinical Registry (N = 26,111). Data were linked with hospital and pharmaceutical datasets to ascertain comorbidities using published algorithms. The sensitivity, specificity, and positive predictive value of these comorbidities were compared with survey responses from 623 patients (reference standard). An indirect comparison was also performed with clinical data from published stroke studies. Results The sensitivity of hospital ICD-10-AM data was poor for most comorbidities, except for diabetes (93.0%). Specificity was excellent for all comorbidities (87–96%), except for hypertension (70.5%). Compared to published stroke studies (3 clinical trials and 1 incidence study), the prevalence of diabetes and atrial fibrillation in our cohort was similar using ICD-10-AM codes, but lower for dyslipidaemia and anxiety/depression. Whereas in the pharmaceutical dispensing data, the sensitivity was excellent for dyslipidaemia (94%) and modest for anxiety/depression (77%). In the pharmaceutical data, specificity was modest for hypertension (78%) and anxiety or depression (76%), but specificity was poor for dyslipidaemia (19%) and heart disease (46%). Conclusion Variation was observed in the reporting of comorbidities of stroke in administrative data, and consideration of multiple sources of data may be necessary for research. Further work is needed to improve coding and clinical documentation for reporting of comorbidities in administrative data.

Background Historically, national programs for collecting stroke data in Australia required the use of multiple online tools. Clinicians were required to enter overlapping variables for the same patient in the different databases. From 2013 to 2016, the Australian Stroke Data Tool (AuSDaT) was built as an integrated data management solution. Objective In this article, we have described the development, implementation, and evaluation phases of establishing the AuSDaT. Method In the development phase, a governance structure with representatives from different data collection programs was established. Harmonisation of data variables, drawn from six programs used in hospitals for monitoring stroke care, was facilitated through creating a National Stroke Data Dictionary. The implementation phase involved a staged deployment for two national programs over 12 months. The evaluation included an online survey of people who had used the AuSDaT between March 2018 and May 2018. Results By July 2016, data entered for an individual patient was, for the first time, shared between national programs. Overall, 119/422 users (90% female, 61% aged 30–49 years, 57% nurses) completed the online evaluation survey. The two most positive features reported about the AuSDaT were (i) accessibility of the system (including simultaneous user access), and (ii) the ability to download reports to benchmark local data against peer hospitals or national performance. More than three quarters of respondents ( n = 92, 77%) reported overall satisfaction with the data collection tool. Conclusion The AuSDaT reduces duplication and enables users from different national programs for stroke to enter standardised data into a single system. Implications This example may assist others who seek to establish a harmonised data management solution for different disease areas where multiple programs of data collection exist. The importance of undertaking continuous evaluation of end-users to identify preferences and aspects of the tool that are not meeting current requirements were illustrated. We also highlighted the opportunities to increase interoperability, utility, and facilitate the exchange of accurate and meaningful data.

IntroductionRecent advances in Australia mean that it is possible to link national clinical registries with government held administrative datasets. However, formal evaluations of such activities and the potential impact for research are lacking.
Objectives and ApproachWe aimed to assess the feasibility and accuracy of linking registrants from the Australian Stroke Clinical Registry (AuSCR) with the Medicare enrolment file. Following data custodian and ethics approvals, personal linkage identifiers were submitted to the Australian Institute of Health and Welfare (AIHW). De-identified data from AuSCR and the AIHW were submitted into the Secure Unified Research Environment and merged using project specific person-based IDs. We calculated the proportion of patients linked with the Medicare enrolment file that were present in the associated Medicare and medication dispensing datasets and the proportion with claims after their date of death. Logistic regression was used to identify factors associated with a non-merged patient.
Results17,980 AuSCR registrants (January 2010-July 2014) were submitted for linkage (median age 76 years; 46% female; 67% ischaemic stroke; 16% TIA). Of these, 93% were merged with Medicare (N=16,648) and 95% with subsidised medication dispensing claims data (N=17,079). In those who died, 127 (0.8%) had one or more Medicare claim and 411 (2.4%) had one or more medications dispensed after their death date. Asian born registrants were less likely to be merged with Medicare (adjusted Odds Ratio [aOR]: 0.54; 95% Confidence Interval [CI]: 0.40, 0.72) than Australian born registrants. Those aged ≥85 years were less likely to be merged with Medicare data than those aged <65 years (aOR 0.24; 95% CI: 0.19, 0.29) but were more likely to be merged with dispensing data (aOR: 2.22 (95% CI: 1.73, 2.84).
Conclusion/ImplicationsLinkage between a national clinical quality registry and the Medicare spine is feasible. These linkages will provide novel insights into post-stroke care.

IntroductionDespite being recommended in clinical guidelines for secondary prevention of stroke, there are limited real-world data on outcomes associated with use of statins post-stroke.
Objectives and ApproachWe aimed to investigate the association between statin use and cardiovascular mortality post-stroke. We conducted a retrospective cohort study using prospectively collected data from the Australian Stroke Clinical Registry (2010-2014), linked with national medication dispensing and mortality data. We observed adult patients with first-ever ischaemic stroke or transient ischaemic attack (TIA) for 1-year following hospital discharge, or until their date of death, whichever occurred first. Statin use, defined as having an available statin dispensing, was assessed daily and treated as a time-varying exposure to account for patients who discontinued or reinitiated statins during follow-up. Multivariable, competing-risks regression, with non-cardiovascular death as the competing risk, was used to investigate the association between statin use and 1-year cardiovascular mortality.
ResultsAmong 8363 patients discharged following first-ever ischaemic stroke or TIA (48% aged ≥75 years, 45% female, 20% TIA, median length-of-stay 5 days), 945 died within 1 year, with 763 deaths being cardiovascular-related. The proportion of statin users was 65% at 90 days, 64% at 180 days, and 62% at 1 year. Groups least likely to be statin users at 1-year were women (odds ratio [OR]: 0.75; 95% CI: 0.67-0.85), patients aged <65 years (OR: 0.80; 95% CI: 0.69-0.92), and those discharged directly home (OR: 0.77; 95% CI: 0.67-0.88). Compared to non-use, use of statins was associated with a reduced risk of cardiovascular mortality within 1 year overall (sub-distribution hazard ratio [SHR]: 0.40; 95% CI: 0.34-0.46), and in sub-groups of patients with TIA, severe stroke, and advanced age.
Conclusion / Implications:Our preliminary data provide evidence of survival benefits associated with post-stroke statin use. Interventions to improve medication adherence may assist in reducing post-stroke mortality.

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.
AnalysisThe 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 (α >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.

Objective: In Australia, approximately 3 in 4 people with acute stroke use an ambulance. Few examples of merging ambulance clinical records, hospital government data, and national registry data for stroke exist. We sought to understand the advantages of using linked datasets for describing the full clinical journey of people with stroke and the possibility of investigating their long-term outcomes based on pre-hospital management of stroke. Method: Patient-level data from the Australian Stroke Clinical Registry (AuSCR) (January 2013-October 2017) were linked with Ambulance Victoria (AV) records and Victorian Emergency Minimum Dataset (VEMD). Probabilistic iterative matching on personal identifiers were used and records merged with a project specific identification number. Results: Of the 7,373 episodes in the AuSCR and 6,001 in the AV dataset; 4,569 (62%) were matched. Unmatched records that were positive for "arrival by ambulance" in the AuSCR and VEMD (no corresponding record in AV) were submitted to AV. AV were able to identify 148/435 additional records related to these episodes. The final cohort included 4,717 records (median age: 73 years, female 42%, ischemic stroke 66%). Conclusion: The results of the data linkage provides greater confidence for use of these data for future research related to pre-hospital management of stroke.

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.

ObjectivesData linkage can provide sufficient breadth and size of data, to draw reliable estimates of effectiveness, at a population level using real-world data. We compared differences in survival and hospital presentations following stroke or transient ischaemic attack (TIA), based on whether a Medicare funded chronic disease management plan was claimed.
ApproachA population-based, comparative effectiveness study of Victorian and Queensland Australian Stroke Clinical Registrants (January 2012-June 2015), using the emulated target trial approach, was performed. Chronic disease management items were identified from Medicare claims in the 6-18 months post-stroke (exposure period). Data on covariates for model adjustment were obtained from hospital, pharmacy and aged care datasets. Outcomes at 19-30 months post-stroke were determined using the national death registry and state hospital data. Cox regression, adjusted using propensity score methods with inverse probability treatment weights was used to determine the effect of receipt of chronic disease management claims on outcomes.
ResultsOf 28,775 AuSCR registrants, 27,435 (95.3%) were linked across the Medicare, pharmacy and hospital datasets. Following exclusions, 11,574 registrants from 42 hospitals (42% female, median age 70 years, 27% TIA) were eligible for the study. Overall, 45% of participants received chronic disease management during the exposure period. After propensity score weighting, there was excellent balance between groups across 35 baseline variables (standardised differences <0.1). Receipt of chronic disease management (vs non-receipt) was associated with a 30% reduced hazard of death (adjusted Hazard Ratio [aHR]: 0.70, 95%CI: 0.57, 0.87) but a 17% increase in hospital presentations (aHR: 1.17, 95%CI: 1.12, 1.23). Variation was observed between planned (aHR: 1.21, 95%CI: 1.10, 1.33) and unplanned (aHR: 1.15, 95%CI: 1.07, 1.23) presentations.
ConclusionWe provide an evaluation of the effectiveness of Medicare funded chronic disease management within "real world" healthcare provision, thereby demonstrating the value of linked population data in health services research. Further work is underway to examine causal mechanisms.

IntroductionTo prevent further vascular events, prescribing of multiple classes of medications (antihypertensive, antithrombotic and lipid-lowering) is recommended in national clinical guidelines following ischaemic stroke.
Objectives and ApproachUsing real-world data, we determined the association between optimal combination pharmacotherapy (supply of all three classes, "optimal pharmacotherapy") and survival after stroke. We linked a cohort of patients with first-ever ischaemic stroke from the Australian Stroke Clinical Registry (2010-2014) with national pharmaceutical dispensing and national mortality data. Cox regression was used to determine associations between pharmacotherapy in the first 30 days of stroke with 1-year (from day 31 to 395) all-cause mortality. All analyses were adjusted for socio-demographic (age, sex) and clinical characteristics (stroke severity, discharge destination).
ResultsAmong 6684 patients discharged following first-ever ischaemic stroke (median length-of-stay 5 days), 6466 patients who survived to 30 days were included (44% female, median age 74 years). During the first 30 days from discharge, 71.4% received ≥1 medication class, and 32.9% (n=2125) received optimal pharmacotherapy. Patients with optimal pharmacotherapy were older (≥75 years 50.3% vs <75 years 44.5%; p<0.001), discharged directly home (home 58.5% vs other 40.3%; p<0.001) and experienced a less severe stroke (able to walk on admission 46.9% vs 36.4%; p<0.001), than those without optimal pharmacotherapy. Between day 31 and 395, there were 667 deaths; 530 related to cardiovascular disease. Compared to no medication, treatment with two medications was associated with a 42% lower risk of death (hazard ratio [HR]: 0.58; 95%CI: 0.45-0.73); and optimal pharmacotherapy had a 62% lower risk of death (HR: 0.38; 95% CI: 0.31-0.47). Survival was similar between those with one or no medication.
Conclusion / ImplicationsPatients with ischaemic stroke who received optimal pharmacotherapy within 30-days of admission had greater one-year-survival. Further research is required to understand reasons for sub-optimal pharmacotherapy in these patients.

IntroductionSurvivors of stroke have complex needs from ongoing disabilities and have increased risk of cardiovascular diseases. The societal costs are therefore substantial. Person-level longitudinal data on the longer-term hospital utilizations of patients with stroke in Australia, and the factors that may influence usage in this setting, are rarely reported.
Objectives and ApproachWe used person-level linkages between the Australian Stroke Clinical Registry (AuSCR: 2009-2013) and hospital admission and Emergency Department (ED) data from four states to examine determinants of hospital utilisation following stroke. The index event was the first event recorded in AuSCR. The rate of hospital contacts/person/year was calculated from contacts 30-365 days post-discharge. Disability was determined from responses to EQ-5D-3L data collected at 90-180 days post-stroke. Comorbidities were identified using ICD-10 discharge diagnosis codes (5 year look back including the index event). Negative binomial regression was used adjusting for patient clustering by hospital and pre-stroke contacts and stratified by disability.
ResultsAmong 10,082 adults with acute stroke (55% male, median age 74 years, 81% ischaemic, 14% hemorrhagic, 5% undetermined, 44% with disability) from 39 hospitals, 57% had a hospital admission or ED contact in the first 30-365 days post-hospital discharge, with median contacts/person/year post-stroke of 1.09 (Q1, Q3: 0, 3.27) compared to a pre-contact rate of 0 (Q1, Q3: 0, 2.18). The strongest associations with subsequent hospital contacts were prior contacts (IRR:1.10, 95%CI:1.07, 1.13), not able to walk on admission (stroke severity) (IRR:1.19, 95%CI 1.07, 1.31) and having a higher comorbidity index score (IRR:1.18, 95%CI:1.14, 1.22). Within stratified cohorts younger age was associated with increased contacts in those with disability (
Conclusion/ImplicationsIn a large linked cohort of patients we have demonstrated the substantial ongoing burden that stroke imposes on hospital systems, particularly regarding survivors with other comorbidities and younger survivors with disability. Knowledge of disability and comorbidity burden may assist with targeting community and hospital interventions to reduce post-stroke hospital usage.