Linkage Of Administrative Data Research Articles

Public and patient perspectives on the use of clinical and administrative health data to identify and contact people at risk of future illness-The case of chronic kidney disease.

For decades, researchers have used linkable administrative health data for evaluating the health care system, subject to local privacy legislation. In Ontario, Canada, the relevant privacy legislation permits some organizations (prescribed entities) to conduct this kind of research but is silent on their ability to identify and contact individuals in those datasets. Following consultation with the Office of the Information and Privacy Commissioner of Ontario, we developed a pilot study to identify and contact by mail a sample of people at high risk for kidney failure within the next 2 years, based on laboratory and administrative data from provincial datasets held by ICES, to ensure they receive needed kidney care. Before proceeding, we conducted six focus groups to understand the acceptability to the public and people living with chronic kidney disease of direct mail outreach to people at high risk of developing kidney failure. While virtually all participants indicated they would likely participate in the study, most felt strongly that the message should come directly from their primary care provider or whoever ordered the laboratory tests, rather than from an unknown organization. If this is not possible, they felt the health care provider should be made aware of the concern related to their kidney health. Most agreed that, if health authorities could identify people at high risk of a treatable life-threatening illness if caught early enough, there is a social responsibility to notify people. While privacy laws allow for free flow of health information among health care providers who provide direct clinical care, the proposed case-finding and outreach falls outside that model. Enabling this kind of information flow will require greater clarity in existing laws or revisions to these laws. This also requires adequate notification and culture change for health care providers and the public around information uses and flows.

After School: An Examination of the Career Paths and Earnings of Former Teachers

We use a novel linkage of school district administrative data to Internal Revenue Service records to study educators’ post-exit career outcomes. The majority of leavers remain in education and mean earnings are slightly below pre-exit earnings even 8 years later. However, these average changes conceal wide variation in outcomes. Roughly 20% of leavers are unemployed, and the bottom quartile of employed leavers earn less than $20,000 annually. At the same time, earnings among the top quartile of employed leavers are higher than those of nearly all stayers, sometimes exceeding $100,000. Post-exit employment and earnings declines are associated with the presence of children or a high-earning spouse for voluntary female leavers, suggesting a role for family-conscious policies for teacher retention.

Quantifying the Association Between Family Homelessness and School Absence in Wales, UK

Using administrative data linkage, this paper sought to quantify the impacts of family homelessness on pupil absence from school. It addresses a gap in United Kingdom (UK) homelessness research, which draws predominantly on qualitative methods and where there is a greater focus on people who fall outside of the statutory system, i.e., single people living on the streets, rather than families. Education records for the academic years 2012/13 to 2015/16 relating to pupils aged 5 to 15 years old living in a coastal city in Wales, UK, were linked to data on households assessed by the statutory housing service operating across the same region. Analysis of mean half-day sessions absent from school, and Poisson panel regression were used to explore associations between absenteeism (authorised, unauthorised, and total), and whether pupils were living in a household making a statutory homelessness application, i.e., experiencing family homelessness. On average, in any given academic year, pupils experiencing family homelessness (PEFH) missed 5 days more of school than pupils not experiencing family homelessness (PnEFH). Adjusted regression analysis found that the rate of total absence was 7% higher amongst PEFH compared to PnEFH, whilst for unauthorised absence it was 13% higher. When a student experienced family homelessness, this led to an increase in their rate of total absences by 5%—adjusting for other factors—compared to when they were not homeless. Findings have implications for statutory education and housing provision, specifically the need for greater cross-disciplinary working to prevent and alleviate the harms caused when families experience homelessness.

Impact of the COVID-19 pandemic on prescription drug use and costs in British Columbia: a retrospective interrupted time series study

ObjectivesTo assess the impact of the COVID-19 pandemic on prescription drug use and costs.DesignInterrupted time series analysis of comprehensive administrative health data linkages in British Columbia, Canada, from 1 January...

Abstract A128: A novel approach to understanding disparities in cancer clinical trial enrollment

Abstract Background: Cancer patients who participate in clinical trials have access to novel therapies, increased monitoring, and potentially improved survival. However, this access is not universal. Striking disparities in clinical trial enrollment have been linked to race, sex, and geography. However, studies on this topic are limited due to a lack of patient-specific socioeconomic data. Methods: This analysis used a novel linkage of administrative patient data from University Hospitals Seidman Cancer Center (Cleveland, Ohio) linked to the LexisNexis Socioeconomic Health Attributes, a robust dataset containing 442 patient-specific attributes gathered from public records regarding income, education, housing stability, property ownership and value, social support, and many others. We included cancer patients aged 18-75 years at the time of the latest cancer diagnosis (before trial enrollment if patient was enrolled) during 2007-2022. Because of the substantial differences in the demographic and clinical characteristics between the trial and non-trial patients, we applied the propensity score matching technique to one-to-one match all trial patients to non-trial patients by age, sex, race/ethnicity, cancer type, and year of the latest cancer diagnosis. Next, we applied the classification and regression tree (CART) machine learning algorithm to identify “phenotypes”, or combinations of patient socioeconomic characteristics that predict their trial enrollment status. We additionally performed the random forest algorithm to determine whether our CART model captured the most important variables in predicting trial enrollment. Results: We identified 28,671 cancer patients with a mean and median age of 60 and 62 years. Of those, 2,479 patients were enrolled in trials, and a corresponding 2,479 non-trial patients were matched. We identified 9 phenotypes of trial enrollment from the results of CART. The percentage of patients enrolled in trials ranges from 30% to 80%. Patients belonging to the highest-enrollment phenotype were identified by their estimated annual income exceeding $50,000, higher fraud-risk level, and age under 61 years. Patients falling into the lowest-enrollment phenotype were characterized by an estimated annual income below $30,000, an estimated home value below $243,000, and no college attendance. Variables identified by CART were also among the top-ranked variables in the random forest regarding their variable. Other important variables identified by random forest include, whether the patient ever registered to vote, risk of not being motivated to manage one's own health, and business records. Conclusion: Compared to community-level data, the use of patient-specific socioeconomic data provides a more granular understanding of clinical trial disparities. The use of machine learning methods of CART and random forest offers a promising avenue for future disparities research. This novel approach will deepen our understanding of cancer disparities and improve our ability to intervene and improve care for our most vulnerable patients. Citation Format: Weichuan Dong, Jamie Shoag, Tamila Kindwall-Keller, Ali Kara, John Shanahan, Debora Bruno, Johnie Rose, Siran Koroukian, Richard Hoehn. A novel approach to understanding disparities in cancer clinical trial enrollment [abstract]. In: Proceedings of the 16th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2023 Sep 29-Oct 2;Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2023;32(12 Suppl):Abstract nr A128.

Gesundheitsdaten: Von Nachbarländern lernen

Abstract The access and use of administrative health data in Germany is limited by several factors. Due to the large number and heterogeneity of data holders, data are usually only available in fragmented form, and access is often regulated in a non-transparent manner. Linkage of health data with other data sources is hardly possible for legal and logistic reasons. These limitations directly affect the ability of researchers in Germany to supply evidence-based policy advice and to conduct fundamental research. Against the backdrop of neighbouring countries, such as Denmark or Austria, giving access to and allowing the linkage of individual administrative data, we propose several measures to improve access to health data in Germany.

School performance trajectories and young adult offending: Findings from a national administrative data linkage, United Kingdom

School performance trajectories and young adult offending: Findings from a national administrative data linkage, United Kingdom

Methodological developments in administrative data linkage for cross cutting policy relevant research: Working towards a sustainable data pipeline

ObjectivesDevelop administrative linkages within a national Trusted Research Environment (TRE) that hosts Longitudinal Population Study (LPS) data for over 20 LPS. We will describe the methodological development carried out to enable linkage to administrative datasets. These linked administrative data will support research for public good, informing policy and practice.
 MethodsThe first sets of administrative data under consideration in this Feasibility Study are from the Department of Work and Pensions (DWP), the Department for Education (DfE) and HM Revenue and Customs (HMRC). Working with UK Government departments through a Task & Finish group we have gathered input from DWP, HMRC and DfE and Office for National Statistics (ONS) data sharing experts. The Task & Finish group identified three pragmatic data linkage and data sharing models, that would enable data to be linked via a newly designed secure data pipeline in a legal, secure, and trustworthy manner for all stakeholders.
 ResultsTo encourage sustainability and acceptability, a model designed to be maintained over a long period is based on the re-use of Departmental Personal Identifiable Information (PII) – i.e., name, date of birth, gender, National Insurance number - and attribute data already deposited by the Departments into ONS. ONS will develop for the linkage and extraction of ONS Data into the TRE a system which conducts, and quality assesses the linkage; minimises the Departmental data to participants within the TRE only and the variables specified in the agreements; and, de-identifies the data to their DEA processing standards. The minimised and functionally anonymous data extract will be securely transferred for ingest and integration into the TRE enabling researchers to address a wider range of questions for public benefit.
 ConclusionThis is a model for efficient and low-burden linkages to inform cross cutting research. It will form part of a responsive UK data science capability which can inform government research needs and be used to meet future crisis e.g. new pandemics, the impacts of climate change or economic shocks.

Education and social care predictors of offending trajectories: A UK administrative data linkage study

ObjectivesThe age-crime curve indicates that criminal behaviour peaks in adolescence and decreases in adulthood, but longitudinal studies suggest that this curve conceals distinct patterns of (re)-offending or trajectories. Some trajectories (e.g., life course persistent offenders) are reported to have distinct risk factors and more negative outcomes than others (e.g., adolescent limited offenders).
 MethodsThe current study had two main objectives: (1) To use UK administrative crime data to identify trajectories of (re)-offending; and (2) To prospectively identify (re)-offending trajectories using longitudinal administrative education and social care data. This project uses linked UK administrative data containing the anonymised education and social care records for individuals born between September 1985 and August 1999, which have been linked to later official crime records up to the end of 2017. To identify offending trajectories, we used information on offence type, age of first conviction/caution, age of last recorded conviction/caution and offending history at three age points (Juvenile: 10-17 years; Young adult: 18-20 years; Adult: 21-32 years).
 ResultsLatent Class Analyses with and without ‘Gender’ and ‘Ever served a custodial sentence’ as covariates was conducted to identify trajectories of (re)-offending. We are currently developing statistical models to see if we can use prospective longitudinal education and social care factors to discriminate between these trajectories. In my talk, I will share findings on the offending trajectories identified and present some early results on the key education and social care drivers of the offending trajectories.
 ConclusionFindings from this study has the potential to provide deeper insights into how these education and social care factors might affect (re)-offending patterns. This could inform education, social care and criminal justice system responses to offending behaviours which seek to reduce offending and its associated social and economic costs.

Who are Pacific peoples in terms of ethnicity and country of birth? A cross sectional study of 2,238,039 adults in Aotearoa New Zealand's Integrated Data Infrastructure

BackgroundThe aggregation of Indigenous peoples from Pacific Island nations as ‘Pacific peoples’ in literature may mask diversity in the health needs of these different groups. The aim of this study was to examine the heterogeneity of Pacific groups according to ethnicity and country of birth. MethodsAnonymised individual-level linkage of administrative data identified all NZ residents aged 30–74 years on 31 March 2013 with known ethnicity and country of birth. All participants were described according to ethnicity and country of birth. Pacific participants were also described according to the number of ethnicities they identified. FindingsA total of 2,238,039 NZ residents were included, of whom 117,957 (5·0%) were Pacific. Nearly two-thirds of Pacific peoples (65·7%) were born overseas, ranging from 45·3% (Cook Islands Māori) to 82·7% (Fijian) (Māori 2·3%, non-Māori non-Pacific 28·9%). Among NZ-born Pacific peoples, 46·9% (Samoan) to 81·9% (Fijian) were multi-ethnic; the proportion was much lower for overseas-born Pacific peoples (ranging from 3·7% [Tongan] to 23·9% [Tokelauan]). InterpretationThere is substantial heterogeneity among Pacific peoples in their country of birth and identification with sole or multiple ethnicities. Assumptions regarding homogeneity in the needs of Pacific peoples are not appropriate and government statistics should therefore disaggregate Pacific peoples whenever possible. FundingSupported by the Health Research Council of New Zealand and a part of Manawataki Fatu Fatu, a programme of research funded by the National Heart Foundation of New Zealand and Healthier Lives – He Oranga Hauora – National Science Challenge of New Zealand.

The impact of polysubstance use patterns on engagement of substance use disorder treatment among emergency department patients at high risk of opioid overdose

BackgroundSubstance use patterns are diverse, and multiple substances are often involved in fatal and nonfatal overdoses. Additionally, polysubstance use is associated with greater difficulty accessing and remaining in substance use disorder (SUD) treatment. The aim of this study was to identify substance use patterns and determine their association with SUD treatment engagement among emergency department (ED) patients at risk of opioid overdose. MethodsThis was a sub-analysis of a randomized controlled trial comparing two behavioral interventions for individuals at two EDs in Rhode Island from 2018 to 2021. Past six-month substance use frequency for eight substances plus injection drug use was self-reported at trial enrollment, and SUD treatment engagement within 90 days after enrollment was obtained using administrative data linkages. Latent class analysis identified substance use patterns and multivariable log-binomial models estimated the association with SUD treatment engagement. ResultsAmong 607 participants, there were four substance use patterns: 1) low reported use (n = 295), 2) frequent injection and heroin use (n = 131), 3) high frequency broad polysubstance use (n = 62), and 4) low frequency broad polysubstance use (n = 119). Compared to participants with the low reported use pattern, those with the frequent injection and heroin pattern had a greater likelihood of SUD treatment engagement (adjusted risk ratio = 1.28; 95% confidence interval = 1.02–1.61). ConclusionsDistinct and meaningful polysubstance use patterns showed differential SUD treatment engagement after ED discharge. Nuanced relationships between substance use patterns and treatment highlight the necessity for tailored harm reduction, treatment, and recovery services.

Health utilities and health‐related quality of life of patients with keratinocyte skin cancers

AbstractBackgroundHealth utilities and health‐related quality of life (HRQoL) have not been adequately examined in patients with basal and squamous cell carcinomas (or keratinocyte skin cancers KCs) repeatedly treated for multiple skin cancers and who require ongoing medical surveillance.ObjectivesOur aim was to assess whether health utilities and HRQoL in an Australian population‐based sample of patients recently treated for multiple KCs were poorer compared to patients with single or no KCs.MethodsSelected from the QSkin Study, a cross‐sectional analysis of 680 patients was undertaken involving data linkage of survey and administrative claims data. Health utility was measured using the EuroQol‐5D 5‐level (EQ‐5D‐5L) while HRQoL was assessed using the Basal and Squamous Cell Carcinoma Quality of Life (BaSQoL) instrument. Scores were summarised by sociodemographic and skin cancer profiles and stratified by skin cancer group (i.e., naïve or zero, single, multiple KCs). Generalised linear models with Poisson family and log link functions were used for multivariate analyses.ResultsThe mean EQ‐5D‐5L score was slightly worse for people with multiple KCs (mean: 0.88, SD: 0.14) versus single KCs (mean: 0.90, SD: 0.16) versus none (mean: 0.91, SD: 0.11). Mean scores were not significantly different across skin cancer group after adjustment for number of comorbidities and self‐reported health. BaSQoL domain scores indicated having KCs had little impact on quality of life with mean total scores ranging from 0.27 for the ‘appearance’ domain to 1.15 for the ‘other people’ domain out of a maximum (worst) score of 3.ConclusionsEven among persons chronically afflicted with multiple KCs and ongoing surgical and nonsurgical treatments, health utility and HRQoL losses were minimal and similar to those people without KCs.

Linkage of whole genome sequencing and administrative health data in autism: A proof of concept study.

Whether genetic testing in autism can help understand longitudinal health outcomes and health service needs is unclear. The objective of this study was to determine whether carrying an autism-associated rare genetic variant is associated with differences in health system utilization by autistic children and youth. This retrospective cohort study examined 415 autistic children/youth who underwent genome sequencing and data collection through a translational neuroscience program (Province of Ontario Neurodevelopmental Disorders Network). Participant data were linked to provincial health administrative databases to identify historical health service utilization, health care costs, and complex chronic medical conditions during a 3-year period. Health administrative data were compared between participants with and without a rare genetic variant in at least 1 of 74 genes associated with autism. Participants with a rare variant impacting an autism-associated gene (n = 83, 20%) were less likely to have received psychiatric care (at least one psychiatrist visit: 19.3% vs. 34.3%, p = 0.01; outpatient mental health visit: 66% vs. 77%, p = 0.04). Health care costs were similar between groups (median: $5589 vs. $4938, p = 0.4) and genetic status was not associated with odds of being a high-cost participant (top 20%) in this cohort. There were no differences in the proportion with complex chronic medical conditions between those with and without an autism-associated genetic variant. Our study highlights the feasibility and potential value of genomic and health system data linkage to understand health service needs, disparities, and health trajectories in individuals with neurodevelopmental conditions.

Incidence of and Risk Factors for Active Tuberculosis Disease in Individuals With Glomerular Disease: A Canadian Cohort Study

Kidney failure is an established risk factor for active tuberculosis (TB) but the risk of TB has not been reported in specific kidney diseases. We sought to determine the incidence of and risk factors for active TB in patients with glomerular disease. Observational cohort study. A provincial kidney pathology registry (2000-2012) was used to identify 3,079 adult patients with IgA nephropathy, focal segmental glomerulosclerosis (FSGS), antineutrophil cytoplasmic antibody (ANCA)-related glomerulonephritis, lupus nephritis, membranous nephropathy, minimal change disease, or "other" glomerular diseases in British Columbia, Canada. Predictors included demographics, immigration status, comorbidities, immunosuppression use, estimated glomerular filtration rate (eGFR), and proteinuria. A diagnosis of active TB was ascertained using administrative data linkages and defined based on (1) the dispensation of 1 or more unique combinations of medications used to treat active TB, or (2) physician or hospital visits for active TB. The definition of TB was validated in an external cohort linked to the Provincial TB registry at the BC Centre for Disease Control (BCCDC). Standardized incidence ratios were calculated using the age-matched general population. Risk factors for active TB were identified using Cox proportional hazards regression analysis. The sensitivity and specificity of the outcome definition of active TB were 87.6% and 99.5%, respectively. During a median follow-up of 6.2 years, 41 patients developed active TB with an incidence of 197 of 100,000 person-years, approximately 23 times as high as the general population and>6 times higher than the threshold of 30 per 100,000 used to define high TB incidence. A high incidence was observed in all glomerular diseases (range, 110-403 per 100,000), in both Canadian- and foreign-born patients (range, 124-424 per 100,000), and in patients exposed or not to immunosuppression (282 vs 147 per 100,000). Factors associated with higher TB risk included immigration from a high-incidence country (HR, 3.90 [95% CI, 1.75-8.68]), diminished eGFR (HR, 2.81 [95% CI, 1.18-6.69]), higher levels of proteinuria (HR, 1.15 [95% CI, 1.04-1.27]), lupus nephritis (HR, 2.79 [95% CI, 1.37-5.68]), and immunosuppression use (HR, 2.13 [95% CI, 1.13-4.03]). A relatively low number of events contributed to uncertainty in risk estimates. Patients with glomerular disease have a high incidence of active TB irrespective of disease type, demographics, or use of immunosuppression. Prospective studies are needed to evaluate the utility of screening for latent TB infection in this population. Patients with kidney failure are at high risk of developing tuberculosis (TB), a major infection that can be prevented by identifying and treating patients who have had prior exposure to TB. The risk of TB in specific kidney diseases is unknown. In this Canadian study of 3,079 patients with glomerular disease, a group of autoimmune kidney conditions, the rate of TB was 23 times higher than in the general population. The rate was high irrespective of the use of immunosuppressive drugs or whether patients had immigrated to Canada from another country. These findings suggest that screening patients with glomerular disease for prior TB exposure may be beneficial; however, this needs to be evaluated in a prospective study.

A guide to navigating administrative data linkage for research.

Data linkage brings together information from various sources, including routinely collected administrative data or data from different research studies, to create a new, richer dataset. It provides insights into complex relationships between health and outcomes and evidence pathways to good health. However, when considering data linkage, there are several processes and practicality aspects that need to be explored. Some of these include understanding the costs, complexity of linkage, data storage requirements, required applications, and time lags. Taking these practicalities into consideration will lead to a more efficient process for data linkage.

Survey Consent to Administrative Data Linkage: Five Experiments on Wording and Format

Abstract To maximize the value of the data while minimizing respondent burden, survey data are increasingly linked to administrative records. Record linkage often requires the informed consent of survey respondents and failure to obtain consent reduces sample size and may lead to selection bias. Relatively little is known about how best to word and format consent requests in surveys. We conducted a series of experiments in a probability household panel and an online access panel to understand how various features of the design of the consent request can affect informed consent. We experimentally varied: (i) the readability of the consent request, (ii) placement of the consent request in the survey, (iii) consent as default versus the standard opt-in consent question, (iv) offering additional information, and (v) a priming treatment focusing on trust in the data holder. For each experiment, we examine the effects of the treatments on consent rates, objective understanding of the consent request (measured with knowledge test questions), subjective understanding (how well the respondent felt they understood the request), confidence in their decision, response times, and whether they read any of the additional information materials. We find that the default wording and offering additional information do not increase consent rates. Improving the readability of the consent question increases objective understanding but does not increase the consent rate. However, asking for consent early in the survey and priming respondents to consider their trust in the administrative data holder both increase consent rates without negatively affecting understanding of the request.

Research and Evaluation in a Child-Focused Place-Based Initiative: West Philly Promise Neighborhood.

Place-based initiatives attempt to reduce persistent health inequities through multisectoral, cross-system collaborations incorporating multiple interventions targeted at varying levels from individuals to systems. Evaluations of these initiatives may be thought of as part of the community change process itself with a focus on real-time learning and accountability. We described the design, implementation, challenges, and initial results of an evaluation of the West Philly Promise Neighborhood, which is a comprehensive, child-focused place-based initiative in Philadelphia, Pennsylvania. Priorities for the evaluation were to build processes for and a culture of ongoing data collection, monitoring, and communication, with a focus on transparency, accountability, and data democratization; establish systems to collect data at multiple levels, with a focus on multiple uses of the data and future sustainability; and adhere to grant requirements on data collection and reporting. Data collection activities included the compilation of neighborhood-level indicators; the implementation of a program-tracking system; administrative data linkage; and neighborhood, school, and organizational surveys. Baseline results pointed to existing strengths in the neighborhood, such as the overwhelming majority of caregivers reporting that they read to their young children (86.9%), while other indicators showed areas of need for additional supports and were programmatic focuses for the initiative (e.g., about one-quarter of young children were not engaged in an early childhood education setting). Results were communicated in multiple formats. Challenges included aligning timelines, the measurement of relationship-building and other process-focused outcomes, data and technology limitations, and administrative and legal barriers. Evaluation approaches and funding models that acknowledge the importance of capacity-building processes and allow the development and measurement of population-level outcomes in a realistic timeframe are critical for measuring the success of place-based approaches.

Birth Spacing and Child Maltreatment: Population-Level Estimates for North Carolina.

We examine population-level associations between birth spacing and child maltreatment using birth records and child welfare records for 1,099,230 second or higher parity children born in North Carolina between 1997 and 2013. Building upon previous research, administrative data linkages were used to address out-of-state migration and family-level heterogeneity in birth spacing and child maltreatment risk factors. Findings provide the strongest evidence to date that very short birth spacing of zero through 6 months from last birth to the index child's conception is a prenatal predictor of child maltreatment (indexed as child welfare involvement) throughout early childhood. Consequently, information about optimal family planning during the postpartum period should become a standard component of universal and targeted child maltreatment prevention programs. However, challenging previous empirical evidence, this study reports inconsistent results for benefits of additional spacing delay beyond 6months with regard to child maltreatment risk reduction, especially for children of racial and ethnic minorities. These findings call for further inquiry about the mechanisms driving the connections between birth spacing and Child Protective Services assessments.

The impact of cross-jurisdictional patient flows on ascertainment of hospitalisations and cardiac procedures for ST-segment-elevation myocardial infarction in an Australian population.

The patient journey for residents of New South Wales (NSW) Australia with ST-elevation myocardial infarction (STEMI) often involves transfer between hospitals and these can include stays in hospitals in other jurisdictions. To estimate the change in enumeration of STEMI hospitalisations and time to subsequent cardiac procedures for NSW residents using cross-jurisdictional linkage of administrative health data. Records for NSW residents aged 20 years and over admitted to hospitals in NSW and four adjacent jurisdictions (Australian Capital Territory, Queensland, South Australia, and Victoria) between 1 July 2013 and 30 June 2018 with a principal diagnosis of STEMI were linked with records of the Australian Government Medicare Benefits Schedule (MBS). The number of STEMI hospitalisations, and rates of angiography, percutaneous coronary intervention and coronary artery bypass graft were compared for residents of different local health districts within NSW with and without inclusion of cross-jurisdictional data. Inclusion of cross-jurisdictional hospital and MBS data increased the enumeration of STEMI hospitalisations for NSW residents by 8% (from 15,420 to 16,659) and procedure rates from 85.6% to 88.2%. For NSW residents who lived adjacent to a jurisdictional border, hospitalisation counts increased by up to 210% and procedure rates by up to 70 percentage points. Cross-jurisdictional linked hospital data is essential to understand patient journeys of NSW residents who live in border areas and to evaluate adherence to treatment guidelines for STEMI. MBS data are useful where hospital data are not available and for procedures that may be conducted in out-patient settings.

Occurrence of cardiovascular events within a large population of patients affected by rheumatoid arthritis with or without diabetes.

Rheumatoid arthritis (Ra) and diabetes are often associated with chronic multimorbidity and share the high risk of development of major cardiovascular events (Mace). This study aimed to identify and analyse patients with only Ra, Ra + diabetes, and only diabetes, in terms of comorbidities and new occurrence of Cv events, from the perspective of the Italian national health service (Inhs). Starting from the Fondazione ricerca e salute (ReS)'s database, through the record linkage of administrative healthcare data, cohorts with only Ra, Ra + diabetes and only diabetes have been selected, characterized (age and sex), and analysed by comorbidity (depression, dyslipidemia, hypertension, hemorrhagic stroke and ischemic stroke/transient ischemic attack - Tia, coronary artery disease - Cad, heart failure - Hf, chronic liver disease, periphery artery disease - Pad, chronic kidney disease, asthma/chronic obstructive pulmonary disease - Copd, neoplasia) and by new Cv events (Hf, Cad and ischemic stroke/Tia) within two follow-up years (Kaplan-Meier curves). A logistic regression model defined contribution and type of association of some variables on new Cv events. In 2018, from 5.375.531 Inhs beneficiaries in the ReS database, 13.698 (0.25%) were affected by only Ra, 1728 (0.03%) by Ra + diabetes, 347,659 (6.8%) by only diabetes. The only Ra cohort was composed by more females, younger and with less comorbidities patients. Proportions of 79.3%, 70.8% and 38.5% of patients with Ra + diabetes, only diabetes and only Ra were affected by 2 to ≥4 comorbidities: among patients with Ra + diabetes, comorbidities showed the highest frequencies, mainly hypertension, dyslipidemia and asthma/Copd. Within two follow-up years, about 8% of patients with diabetes with/without Ra developed a new Cv event (vs 3% with only Ra). The presence of Ra/diabetes or Ra + diabetes, male sex, older age and comorbidities of interest resulted significantly (p<0.01) associated with a higher Cv risk. Comorbidities and the co-presence of diabetes in patients with Ra determine a complicated framework with high risk of Cv events. It is worthy include more complex patients in clinical trials, in order to generate evidence useful for even more multidisciplinary medical teams.