Data Linkage Research Articles

Second Primary Cancer Risks After Breast Cancer in BRCA1 and BRCA2 Pathogenic Variant Carriers.

Second primary cancer (SPC) risks after breast cancer (BC) in BRCA1/BRCA2 pathogenic variant (PV) carriers are uncertain. We estimated relative and absolute risks using a novel linkage of genetic testing data to population-scale National Disease Registration Service and Hospital Episode Statistics electronic health records. We followed 25,811 females and 480 males diagnosed with BC and tested for germline BRCA1/BRCA2 PVs in NHS Clinical Genetics centers in England between 1995 and 2019 until SPC diagnosis, death, migration, contralateral breast/ovarian surgery plus 1 year, or the 31st of December 2020. We estimated standardized incidence ratios (SIRs) using English population incidences, hazard ratios (HRs) comparing carriers to noncarriers using Cox regression, and Kaplan-Meier 10-year cumulative risks. There were 1,840 BRCA1 and 1,750 BRCA2 female PV carriers. Compared with population incidences, BRCA1 carriers had elevated contralateral BC (CBC; SIR, 15.6 [95% CI, 11.8 to 20.2]), ovarian (SIR, 44.0 [95% CI, 31.4 to 59.9]), combined nonbreast/ovarian (SIR, 2.18 [95% CI, 1.59 to 2.92]), colorectal (SIR, 4.80 [95% CI, 2.62 to 8.05]), and endometrial (SIR, 2.92 [95% CI, 1.07 to 6.35]) SPC risks. BRCA2 carriers had elevated CBC (SIR, 7.70 [95% CI, 5.45 to 10.6]), ovarian (SIR, 16.8 [95% CI, 10.3 to 26.0]), pancreatic (SIR, 5.42 [95% CI, 2.09 to 12.5]), and combined nonbreast/ovarian (SIR, 1.68 [95% CI, 1.24 to 2.23]) SPC risks. Compared with females without BRCA1/BRCA2 PVs on testing, BRCA1 carriers had elevated CBC (HR, 3.60 [95% CI, 2.65 to 4.90]), ovarian (HR, 33.0 [95% CI, 19.1 to 57.1]), combined nonbreast/ovarian (HR, 1.45 [95% CI, 1.05 to 2.01]), and colorectal (HR, 2.93 [95% CI, 1.53 to 5.62]) SPC risks. BRCA2 carriers had elevated CBC (HR, 2.40 [95% CI, 1.70 to 3.40]), ovarian (HR, 12.0 [95% CI, 6.70 to 21.5]), and pancreatic (HR, 3.56 [95% CI, 1.34 to 9.48]) SPC risks. Ten-year cumulative CBC, ovarian, and combined nonbreast/ovarian cancer risks were 16%/6.3%/7.8% (BRCA1 carriers), 12%/3.0%/6.2% (BRCA2 carriers), and 3.6%/0.4%/4.9% (noncarriers). Male BRCA2 carriers had higher CBC (HR, 13.1 [95% CI, 1.19 to 146]) and prostate (HR, 5.61 [95% CI, 1.96 to 16.0]) SPC risks than noncarriers. Survivors of BC carrying BRCA1 and BRCA2 PVs are at high SPC risk. They may benefit from enhanced surveillance and risk-reduction measures.

11.A. Scientific session: Overcoming Real-World Challenges in Setting up Health Data Linkages for Public Health Policy

Abstract Background Linking available administrative data has gained momentum in the last years to enhance public health research and public health formulation. Linkage of diverse data sources can be leveraged to understand social-determinants of health, the cost-effectiveness of an intervention, and to evaluate impact of policies. For instance, data linkage has been proven to be a powerful approach to periodically analyze real-world progress of the COVID-19 pandemic. Today, we are witnessing an unparalleled increase in electronic health data stemming from citizens who interact with services such as healthcare providers, employers, sick funds, and other governmental structures. This enormous amount of data opens many innovative possibilities in epidemiological research. The main advantages of the secondary use of data are the following: 1) it is enriching for new collected data (e.g. survey study), 2) it provides comprehensive information of the target population, and 3) it is cheaper than new data collection. Data linkage between data sources is, however, often a herculean task, and it comes with considerable challenges such as: 1) juridical complexity related to intra-national and cross-border data governance procedures, 2) fragmented data integration, 3) data delivery delays. Addressing these challenges is essential to unlocking the true potential of data linkages for timely responses to emerging public health questions, thereby contributing to evidence-based policy and care and transforming our health research into a One Health approach. Objectives The workshop’s main aim is to present the researcher’s lessons-learned and approaches in applying data linkage from an European, and a country-level perspective through case-studies while creating a space for the public to share their own view. In this workshop we aim to 1) provide a helicopter overview of current data linkages approaches in Europe, 2) illustrate this with case studies from an international, and a country-level perspective, and 3) emphasize the challenges and disadvantages of those data linkages, while sharing potential solutions. Workshop outline The workshop is divided into a knowledge translation, and an interactive part. In the first part of the workshop, three speakers will give a presentation of each 10 minutes with a Q&A of 5 minutes between each presentation where data linkage will be introduced, and three case studies on how data linkage can be used will be presented. The first presentation will introduce approaches to data linkages in Europe, and will delve into how AI can be used during routine data linkage. The second presentation will show a case-study on how an international data linkages can be done in an European federated manner. The third presentation will further illustrate how nationally data can be linked to investigate health inequalities. In the second part of the workshop, the audience will be invited to interact with the speakers and share their experiences. Key messages • A comprehensive overview of different current data linkages approaches are provided, setting the stage for discussions on methods and best practices. • Administrative data linkages are a powerful tool to answer important public health challenges, but important challenges related to data governance need to be addressed to realize the full potential.

Unraveling Social Health Inequalities during COVID-19 in Belgium: The Vital Role of Data Linkages

Abstract Background During the COVID-19 crisis, data linkages were set up to efficiently monitor the outbreak and identify vulnerable population groups. Yet, considerable technical, administrative and data security issues have hindered the effectiveness of data linkages as a critical instrument during public health emergencies. This workshop aims to provide a practical demonstration of the challenges encountered in a Belgian data linkage during the COVID-19 crisis, along with the strategies implemented to overcome these challenges. This case study offers insights into the development of a highly sensitive linkage between COVID-19 hospital data and information related to social and health use in Belgium. Methods The HELICON data linkage is developed at the individual level to investigate the risk of COVID-19 hospitalization and the influence of various social and biomedical factors during and after the crisis. Data are drawn from data collections on hospitalization from the COVID-19 health surveillance (Sciensano), on the socioeconomic and sociodemographic context (Statistics Belgium), and on healthcare use and reimbursement (InterMutualistic Agency). Results A representative case-cohort study is established comprising 1,149,264 million randomly selected Belgians and 44,508 hospitalized patients. Annual follow-up is scheduled over a four-year span, allowing the investigation of pre- and post-pandemic health data from July 2020 to January 2026. Conclusions The HELICON data linkage took 3.5 years to complete. Among the many challenges, we were faced with complicated approval procedures, ambiguous data security guidelines, unclear cost estimates, and technical issues related to the analysis environment. Building on these experiences, we explore the strengths and weaknesses of data linkages as a research instrument during the COVID-19 pandemic and discuss which lessons should be drawn to for the post-pandemic era.

A cross-sectional study of data linkage and artificial intelligence practices across European countries

Abstract Background The availability of different data sources is increasing with the possibility to link them with each other. However, linked administrative data can be complex to use and may require advanced expertise and skills in statistical analysis. The main objectives of this study were to describe the use of data linkage and artificial intelligence (AI) in routine public health activities and the constraints to linking different data sources. Methods A cross-sectional survey was performed across European countries to explore the current practices applied by national institutes of public health, health information and statistics for innovative use of data sources (i.e., the use of data linkage and/or AI). Results In Europe, the use of data linkage and AI at national institutes of public health, health information and statistics varies. The use data linkage in routine by applying a deterministic method or a combination of two types of linkages (i.e., deterministic & probabilistic) for public health surveillance and research purposes is common in majority of European countries. The use of AI to estimate health indicators is not frequent among these institutes. The complex data regulation laws, lack of human resources, skills and problems with data governance, were reported by European countries as main constraints to routine data linkage for public health surveillance and research. Conclusions Our study showed that the majority of European countries have integrated data linkage in their routine public health activities but only a few use AI. A sustainable national health information system allowing to link different data sources are essential to contribute to public health research. Moreover, it supports evidence-informed health policy making processes with an overview of various aspects affecting population health and may contribute to European pandemic preparedness.

An interdisciplinary approach: Exploring the five dimensions of the tools deployed by EUVABECO

Abstract To effectively address the complexities of vaccination across the EU, EUVABECO’s 14 partners are implementing a comprehensive, interdisciplinary approach. Twelve pilot projects will be implemented from September 2024 to August 2025 in six MS (BE, DE, EL, LV, LU, PL, PT). These pilots will test innovative tools across five domains-medical, social, industrial, modelling and forecasting, and digital-to optimize vaccination outcomes: Medical/Clinical Tool: A decision support system that aids patients and healthcare professionals by providing current, evidence-based information tailored to individuals, thereby facilitating informed vaccination decisions. Social Tool: Data linkage on an individual level, to enhance the targeting and monitoring of vaccine campaigns, and ensuring equitable access to vaccines, especially for vulnerable populations. Industrial Tool: An electronic vaccine leaflet that boosts the flexibility and responsiveness of vaccine distribution by offering dynamic, real-time information in local languages to both healthcare providers and patients - regardless of the source and point of use of the vaccine. Modelling and Forecasting Tool: A disease simulator that models infection dynamics and evaluates the impact of public health interventions, crucial for strategic planning and resource allocation. Digital Tool: A citizen-held digital vaccination card that enables individuals to maintain a comprehensive, accessible record of their own vaccination histories, enhancing continuity of care across borders.

Developing regional Diabetes Registries in Italy: pilot projects implementation within JACARDI

Abstract Issue/Problem In Italy a National Diabetes registry is planned but not yet set up at the Ministry; JACARDI is contributing to speed up the process so that critical gaps in health data availability can be filled. While some regional registries exist, the lack of cohesion and standardization hinders the tracking of prevalence, incidence, and sequelae, crucial for evidence-based policymaking amidst rising diabetes rates. Description of the Problem The JACARDI project, supported by EU funding and running for four years, engages 76 partners from 21 countries and includes 142 national-level projects. Among its focus areas is enhancing data availability, aiming to establish harmonized regional Diabetes registries in Italy to tackle this issue. These efforts aim to create a scalable model enabling data linkage, diabetes type differentiation, and socio-demographic integration. Collaboration with health authorities and societies, drawing insights from existing registries, informs the development process. Results A total of 11 regional Diabetes registries are currently in the design phase of implementation. They adhere to a clearly defined methodology, with established essential parameters and data linkage. Consensus on these parameters and linkage was reached through stakeholder discussions, drawing on past registry experiences. The primary goal of the registries is to monitor diabetes prevalence, stratify incidence by demographics, and track sequelae to inform targeted interventions and resource allocation. While scalability beyond Italy may encounter administrative challenges, standardized protocols facilitate transferability. Data Protection stands out as a significant implementation obstacle. Lessons Standardized data collection, stakeholder collaboration, and sustainability are vital in registry development. Leveraging data availability for surveillance demonstrates adaptability and scalability, offering valuable insights for enhancing diabetes management. Key messages • Standardized data collection and stakeholder collaboration are pivotal in establishing effective diabetes registries, fostering equity and improving health outcomes. • Leveraging data availability for surveillance offers a scalable and sustainable approach to diabetes management, facilitating informed policymaking and interventions.

Ultra-processed food consumption and risk of cardiovascular mortality in Australia: preliminary results from prospective observational study

Abstract Background/Introduction A large proportion of the Australian population emigrated from countries where traditional dietary patterns are protective of cardiovascular health. Yet, recent evidence suggests that 42% of a modern Australian diet's total energy intake is comprised of ultra-processed foods. This is concerning as previous meta-analyses and umbrella reviews based on population studies have found an association between ultra-processed food consumption and adverse health outcomes, including cardiovascular disease and mortality. However, this has yet to be explored in an Australian population. Purpose To determine the association between ultra-processed food consumption and the risk of cardiovascular mortality in an Australian cohort. Methods Prospective data from the Melbourne Collaborative Cohort Study (MCCS; n = 38054) were analysed. UPF consumption at baseline (1990 to 1994) was assessed in accordance with the NOVA food classification system using data from a 121-item food frequency questionnaire. Energy-adjusted ultra-processed food consumption was then categorised into quartiles. Cardiovascular mortality was obtained through data linkage with national and local registries up to 2015 and 2019, respectively. This was done using the International Classification of Diseases (ICD) codes (390-459 and I00-I99). Unadjusted and adjusted multivariate logistic regression models were fitted to estimate associations between ultra-processed food consumption (exposure) and cardiovascular mortality (outcome). Results A total of 4,242 incident cardiovascular deaths occurred (2,272 for males and 1,970 for females) during the follow-up period. After adjusting for sociodemographic characteristics and lifestyle and health-related behaviours, higher UPF consumption was associated with a higher risk of cardiovascular mortality (aOR high (quartile 4) vs. low (quartile 1) category = 1.26, 95%CIs 1.14 to 1.39, ptrend < 0.001). Conclusion(s) In this large prospective cohort of Australian adults, higher ultra-processed food consumption was associated with an increased risk of cardiovascular mortality. These findings support previous research and guidelines recommending the reduction of ultra-processed food consumption as part of a heart-healthy diet.

Environmental Public Health Tracking in England- support for Health Impact Assessments

Abstract Environmental epidemiology is a key function for the public health service with regards to investigating the public health effects of environmental hazards, monitoring the public health efforts to control the environmental risks, and providing the evidence that informs decisions making and preparedness. At the United Kingdom Health Security Agency (UKHSA), the Environmental Public Health Tracking (EPHT) Programme, initiated in 2010, has developed a number of data streams to help link environment and health data, to support Health Impact Assessment (HIA). The main aims of the EPHT programme in England are to: 1. Identify populations at risk from exposure to significant environmental and chemical hazards 2. Investigate relationships between hazard and disease 3. Inform public health policy making 4. Optimise intervention and prevention strategies 5. Generate hypotheses for further research. Such EPHT functions are based on three key components: a) by building a national EPHT program that integrates surveillance of environmental hazards, exposures and related health outcomes, to allow data linkage and assessment of environmental and health information; b) strengthening the epidemiology science, by conducting research and training of the workforce and c) developing strategies for response to immediate risks, incidents and preparing for future risks. Examples to support HIA include a) developing an air pollution exposure surveillance work programme, that has designed a pilot population vulnerability indicator; b) developing indicators for climate change impacts for public health, c) reporting regularly on the health impacts of public fluoridation water supply schemes (as mandated by Government) and d) exploring risk factors associated with elevated blood lead concentration in children, through laboratory reporting to surveillance systems. The talk will highlight some examples of practice and outline how the EPHT programme in England has supported HIA practices.

Mother-to-child Transmission using the National HBV Perinatal Prevention Data in Korea, 2002-2021

Abstract Aims To define risk factors associated with mother-to-child transmission (MTCT) and to create supporting evidence for the National Hepatitis B Perinatal Prevention Program (HBPPP) in Korea. Methods We analyzed HBPPP mother-infant pair data enrolled from 2002 to 2021. The major outcome was the HBsAg status of the infant resulting from post-vaccination serological testing. Additionally, we used prescription records of antivirals against the hepatitis B virus (telbivudine, tenofovir disoproxil fumarate) from 2010 to 2021 by data linkage with the National Health Insurance claims data. To select significant risk factors by maternal HBeAg status based on the data from 34 to 42 weeks of pregnancy, multivariate logistic regression analysis was used. Results Data from 232,242 mother-infant pairs were analyzed. Among 154,331 (66.5%) infants with post-vaccination serological testing results, 3,620 (2.3%) were HBsAg-positive. The incidence of MTCT has shown a decreasing trend, from 4.1% in 2002 to 1.0% in 2021. However, the rate was high at 5.5% (1822/32986) for infants of HBeAg-positive mothers. Maternal antiviral prescription during the pregnancy period, old age, HBeAg negative, delivery type (C-section), and breastfeeding were significant factors in decreasing the risk of MTCT. Among the HBeAg-positive, there was a significant difference in the antiviral prescription 0.7% (11/1692) compared to the non-prescription 4.9% (789/16264) [aOR, 7.71; 95% CI, 4.24-14.02]. The result was similar for the HBeAg-negative group, 0.7% (302/44888). Conclusions To eradicate the hepatitis B virus on a national level, MTCT must be further reduced. To achieve this, it is necessary to introduce strong additional preventive measures, including quantitative HBV DNA testing for mothers with chronic hepatitis B and administering antiviral prophylaxis at the third trimester of pregnancy with HBV-DNA ≥200,000 IU/mL into the HBPPP. Key messages • The incidence of mother-to-child transmission has shown a decreasing trend, from 4.1% in 2002 to 1.0% in 2021. • Maternal antiviral prescription, old age, HBeAg negative, delivery type (C-section), and breastfeeding were significantly decrease the risk of mother-to-child transmission.

Independent and joint associations of urinary potassium excretion with cardiovascular death: a national population-based cohort study

Abstract Background Elevated potassium excretion is associated with lower blood pressure, as well as reduced risks of cardiovascular disease (CVD) death. However, the impact of varied sodium levels on this association remains a topic of debate, and the mediators of this association besides blood pressure remain uncertain. Purpose To examine the joint association of potassium and sodium with CVD mortality risk, and to identify potential mediating factors of this association. Methods Based on the ChinaHEART (China Health Evaluation And risk Reduction through nationwide Teamwork) project, participants aged 35-75 from 239 sites across all 31 provinces in the mainland of China were recruited from November 2014 to December 2022. We collected spot urine samples from participants and estimated 24-hour sodium and potassium excretion using the Kawasaki formula. Death records were captured through data linkage with the National Mortality Surveillance System and Vital Registration. Multiple regressions were used to analyze the association between potassium excretion and CVD death, as well as to examine the addictive interaction of potassium and sodium. Results This study included 270,991 participants with a mean age of 55.8±9.8 years, and 60.5% of them were female. The mean potassium excretion was 54.36±12.58 mmol/d , which was higher in males and people living in the north. Findings revealed a positive correlation between low urinary potassium levels and CVD death , and the lowest adjusted hazard rate for CVD mortality was 0.65 (95% CI: 0.58-0.73) in the group with the highest potassium excretion (i.e. ≥64.27 mmol/d) compared with the reference group (<43.79 mmol/d), after adjusting for sociodemographic characteristics, medical histories, and lifestyles. Age modified the association between potassium excretion and risk of CVD death (P for interaction=0.031). In addition to systolic blood pressure (16.6%), heart rate (2.2%) also served as the significant mediator between urinary potassium excretion and CVD death. The relative excess risk of interaction (RERI) of lower potassium excretion and lower sodium was significantly positive (RERI=0.22, 95% CI: 0.02-0.42), which implied the synergy effect. Conclusion Potassium intake in the Chinese population is evidently lower than the guideline recommendations, and increasing potassium intake, especially in the population aged <65 years, may reduce the risk and burden of cardiovascular and other diseases. Moreover, when sodium intake is insufficient, supplementation with both sodium and potassium salt can achieve greater health benefits.Graphic abstract

Comparing Italian hospital discharge and mortality data: implications for epidemiological research

Abstract Background In Italy, regional governments maintain data warehouses of linked administrative health data (AHD) linked to demographic information including mortality. Legal reporting pathways for death certificate detail bypass the Region, resulting in significant amounts of missing data on cause and location of death in regional AHD warehouses and limiting epidemiological research on mortality and incidence. In this study, we determine for the first time in Italy the degree of agreement between last hospital diagnosis and primary cause of death, and how that agreement changes over time. Previous studies have found agreement ranging from 40% to 60%. Methods The COV-CVD cohort is comprised of 7.3 million adults aged 30+ from the Lombardy region of northwest Italy, representing all Lombardy residents registered with the health system as of 31 December 2019. Concordance was assessed using the first three characters of the reported cause of death (ICD-10 codes) and primary diagnosis at last hospitalization (converted from ICD-9CM). Results In the COV-CVD cohort there were 401,085 deaths between 1 January 2020 and 23 June 2023. Cause and location of death is missing for 50% and 54% of these deaths, respectively. 60% of deceased individuals had a hospitalization in the year before their death. Agreement between primary diagnosis at last hospitalization and cause of death was 27% overall and 40.5% for deaths in hospital. Missing location of death was reduced from 54% to 26%. Conclusions When using AHD from Italy, primary diagnosis at last hospitalization prior to death is not an appropriate proxy for cause of death, even when the death occurred in hospital. Different coding systems (ICD-10, ICD-9CM) further complicate comparisons and definitions in observational studies. Key messages • In Italy, primary diagnosis at last hospitalization before death is not an appropriate proxy for cause of death. • Poor linkage of mortality and health data limits epidemiological research.

Long-term outcomes in women diagnosed with heart failure in connection to delivery

Abstract Background Heart failure (HF) among young patients may be from various causes, often triggered by heightened physical demands like pregnancy. Data regarding outcomes of women diagnosed with HF in conjunction to pregnancy and delivery are varied. There remains a notable gap in understanding the outcomes observed in women diagnosed with heart failure in conjunction with delivery. Also, long-term follow-up studies are crucial to elucidate the impact of pregnancy-associated HF on future cardiovascular. Purpose To study the interplay between pregnancy, HF, and subsequent cardiovascular risk. Method Using the personal identification numbers (PINs) that all individuals in Sweden have enables linkage of data between different registers. Data from the National Patient Register (NPR), Swedish Medical Birth Register (MBR) and the Cause of Death Register were also used. All women 18 to 50 years of age registered in the in MBR in the period 1st January 1997 to 31st December 2019 were included. Women with first-time HF in relation to delivery were identified using the international classification code for diseases (ICD-10) I50, I42, I43 and 090.3 together with co-morbidities. Every patient was compared with 5 controls without HF from the Total Population Register matched on age at delivery and calendar year of delivery. Outcomes: all-cause mortality, and any cardiovascular disease (CVD) diagnosed during the observation time. Results A total of 286 cases and 1,430 controls were included. The prevalence of comorbidities at baseline for both patients and controls was low; congenital heart disease (1.4%, vs. 0%), pulmonary hypertension (1.0% vs. 0%), valvular heart disease (5.9% vs. 0%), myocardial infarction 0.7% vs. 0%), arrhythmia (5.9% vs. 0%), hypertension (6.3 % vs. 0.1%), (all p<0.05). Preeclampsia prior to HF diagnosis had 31% of patients vs. 0.2% of controls (p<0.001). Patients exhibited higher mortality rates at 4.9% during median follow up 9.0 (IQR 5.6-13.0) years vs. 0.3%, median follow up 9.4 (6.2-13.5) years and hazard ratios (HR) for all-cause mortality HR (95% CI) of 18.20 (5.99 - 55.31) (p<0.001) compared to controls. During median follow up of 3.2 (0.0-9.2) years 60.1% of patients were diagnosed with CVD both at in-/out-patient settings compared with 4.1% in controls during 9.4 (5.8-13.5) years of follow up. Comparing patients with controls the HR (95% CI) was 22.24 (16.50 - 29.96) p<0.0001 for CVD diagnosis during follow-up, see Figure 1. Conclusion In conjunction with delivery, and in the years thereafter, women with heart failure diagnosis had more than eighteen times higher risk of mortality than women without heart failure. The risk of CVD event in the heart failure group is highest in conjunction with delivery. Figure 1. Cumulative incidence functions for all-cause mortality, CVD in- or out-patient visit adjusted for death as competing risk, comparing cases with controls.

What does international evidence tell us about the health of people with childhood social care (CSC) experiences?

Abstract International research into the health of people with childhood social care (CSC) experiences has found evidence of worse mental health and emotional-behavioural wellbeing, higher rates of substance use, neurodevelopmental conditions, and avoidable mortality. Lower vaccination rates and worse dental health among those in care has also been reported in few countries. However, research results have been more mixed with regard to some physical health conditions, with higher prevalence of asthma and respiratory ill health among foster children reported in the US but no obvious differences found in the UK. Are there countries where these inequalities are less pronounced, and can we draw such conclusions based on available evidence? When making international comparisons or aiming to give policy advice, we also need to consider the quality of our evidence. Has this been based on small sample sizes or without comparison to other children and adjusting for relevant (socioeconomic) confounders? Most of our current knowledge is also cross-sectional and we do not know if some health conditions precede entry to care and may even be risk-factors for entering social care. Recent longitudinal and cross-sectoral data linkage programmes in many nations (Australia, UK, Canada) have a potential to change this and provide a foundation for evidence-based recommendations for policy and practice.

Distal ascending aortic dilatation portends a near 2-fold greater risk of cardiovascular mortality than proximal enlargement: results from 120,000 patients in a nationwide echocardiographic database

Abstract Background The management of thoracic aortic dilatation is clinically challenging and acute aortic dissection (AD) is under-recognised as a primary cause of death. Despite the majority of AD occurring in non-severely dilated aortas, absolute aortic diameter remains the most utilised criterion for adjudging preventative surgical correction. In order to improve outcomes and guide management, greater prognostic understanding is needed. Purpose We examined a nationwide echocardiographic dataset linked to mortality outcomes to determine how ascending thoracic aortic dilatation and its site affects cardiovascular disease (CVD) mortality over time. Methods The National Echocardiography Database Australia (NEDA) was examined for aortic dimensions at the sinuses of Valsalva (SoV), sinotubular junction (STJ) and ascending aorta (AscAo) in patients who had undertaken >1 echocardiographic study. Following separation of those who had undergone corrective aortic surgery, patients were stratified according to absolute aortic diameters and grouped as normal (<4cm), mild (4.0-4.5cm), moderate (4.5-5cm) and severely (>5cm) dilated at the prescribed thoracic aortic sites. Mortality data was then linked from the National Death Index (NDI). Results 398,905 echocardiographs from 121,115 patients with a mean age of 62.6±16.2 years were included. At the time of mortality data linkage, 38,681 (32%) had died, of whom 13,292 (34%) died from CVD causes and only 276 (0.007%) had aortic dissection recorded as their primary cause of death. Severe aortic dilatation at any site increased the likelihood of 10-year CVD mortality (29% vs. 15% in those with normal diameters; HR 3.00; CI 1.60-5.63; p<0.0001), with an incremental increase in the probability of CVD death when moving from the proximal to distal ascending aorta; 10-year CVD mortality at the SoV 26% (HR 1.93; CI 1.29-2.87; p<0.001), STJ 39% (HR 2.82; CI 1.64-4.86; p<0.001) and AscAo 44% (HR 4.74; CI 2.46-9.13; p<0.001) respectively (Figure 1). When examining those patients who had undergone corrective aortic surgery, the likelihood of 10-year CVD mortality was comparable to the population with normal aortic diameters (17 vs. 15%, HR 1.1; CI 0.9-1.36; p=0.3) (Figure 2). Conclusion Severe aortic dilatation increases the probability of 10-year cardiovascular mortality. Interestingly, there is an incremental increase in the likelihood of CVD mortality when moving from the proximal to distal ascending aorta, with severe AscAo dilatation conferring a near 2-fold greater risk of CVD mortality compared with severe SoV aneurysms. Additionally, surgical aortic intervention nearly normalises survival probability to the population with healthy aortic diameters. These results identify new considerations for prognostication, risk stratification and surgical guidance of aortic repair.CVD mortality by aortic dilatationCVD mortality after aortic intervention

Geographic variation in kidney failure and transplantation in Aotearoa New Zealand: A population-based data linkage study.

This study aimed to describe the epidemiology of kidney replacement therapy (KRT) in Aotearoa New Zealand and assess the impact of residential location on access to kidney transplantation. AcceSS and Equity in Transplantation (ASSET), a health-linked data platform, was used to identify people commencing KRT in New Zealand from 2006 to 2019 and analyse regional epidemiology. Health services were classified as 'transplanting', 'intermediate' or 'remote' depending on their degree of separation from a transplant centre. Multiple logistic regression modelling was used to assess the predictors of deceased donor waitlisting or living donor transplantation within 6 months after starting KRT. Web-based mapping software was used to develop interactive geospatial maps. The cohort was 7704 people newly starting KRT. Living in an intermediate [odds ratio (OR): 0.73 (95% confidence interval (CI): 0.61-0.88)] or remote [OR: 0.38 (95% CI: 0.27-0.54)) region and Māori (OR: 0.35 (95% CI: 0.28-0.44)], Pacific [OR: 0.32 (95% CI: 0.24-0.42)) and Asian (OR: 0.66 (95% CI: 0.50-0.87)] ethnicity were associated with a decreased likelihood of timely waitlisting or transplantation. Regional maps can be explored here. There is marked geospatial and ethnic variation in the epidemiology of kidney failure and access to kidney transplantation across New Zealand. Geospatial mapping of kidney failure epidemiology and transplantation outcomes can provide opportunities to direct resources towards populations at greatest need.

3.Y.2. Road traffic injuries, disability burden and implications for compensation schemes in Europe

Abstract Reducing traffic fatalities and injuries is a complex challenge, but it is one that is of paramount importance for public health and safety worldwide. In recent years, there have been improvements in trauma care and injury prevention efforts, which reduced mortality rates and increased survival after serious injury. However, an increased heterogeneity in recovery times is observed with survivors of road traffic injuries differing in their adjustment compared to other traumas in terms of symptoms’ onset, variability and chronicity. The recovery trajectory seems to vary widely with a large percentage of survivors in need of extensive time periods for full recovery. Attention has now been shifted towards the adverse effects of non-fatal injuries on functional, mental health, economic and societal outcomes. The capacity of a person to continue functioning, inability to work, sickness absence and reliance on welfare benefits to compensate for loss of income are some of the injury-related long-term consequences, causing great concern for health and social security systems across Europe, as they have been shown to account for more than one third of total road traffic incident costs. These figures fail to include individuals who sustain “minor” injuries, which do not require hospitalisation, yet still impair their ability to work. Despite the rapidly growing epidemiological and clinical attention, there are still several issues missing from research, policy and practice. A universal definition of recovery after a road traffic injury is still missing, and this has been seen as critical for improved understanding of risk factors of poor recovery as well as improved identification of those in need of welfare benefits. Furthermore, long-term sickness absence and disability following road traffic injury in Europe is still understudied and evidence on the different return to work pathways and compensation schemes is scarce. Evidence is still limited on the context in which return to work occurs, the injury profiles most dependent on long term compensation schemes and the policy settings of injury compensation schemes that impact return to work outcomes post injury. Data availability and data linkage issues often cause misclassification errors when granting disability pensions and this remains unattended long after an injury. Welfare benefits are often poorly connected with the injury or other medical diagnoses and this makes it difficult to assess the contribution of injuries on disability pensions and other welfare benefits, especially in comorbid and multimorbid conditions. The current workshop aims to improve our understanding of the long-term consequences and the challenges faced by those injured in road traffic injuries and aid the development of interventions that seek to enable sustained recovery, and help inform policy and practice of healthcare and injury compensation systems. Key messages • Timely access to quality healthcare, rehabilitation therapies, and assistive technologies can significantly improve outcomes and reduce the strain on social security and compensation systems. • Ensuring equitable access to social security benefits for injured individuals, requires efficient compensation schemes that recognize the full impact of the disability on individuals’ life.

System-wide health needs segmentation: innovating integrated care for complex needs households

Abstract Background Health needs segmentation is increasingly used in healthcare delivery and health policy planning to cater for diverse population groups and develop effective and equitable health policies. But existing models often lack a systemic approach, focusing instead on single conditions or settings. This leads to fragmentation, gaps and inefficiencies in service provision and inequities in health outcomes, particularly when addressing complexity, and specifically for children, as adversity clusters in families. Aims To develop a household health needs segmentation model to identify those households with children with high levels of complex cross-sectoral needs, to plan for integrated care services. Methods Data linkage of primary, secondary, mental, community and social care services, mortality records, residential information, and small-area multiple deprivation measures was used to design a rule-based model to identifying households with children with the most complex needs in the UK region of Cheshire and Merseyside (C&M), with large variation in demography, (human) geography, and deprivation. Results Of 2,645,329 individuals in C&M (97% of the registered population in 2021), 1,022,840 lived in 266,939 households with children aged 0-16: 21,527 households had complex needs. This 8% of families accounted for an estimated 34% of health and social care costs for families, £362 million in total, 42% of which spent on children in care of local authorities. Implications The model identified a specific group of families with complex service use patterns, high mental and physical comorbidity and socioeconomic vulnerabilities. These exhibit potential for improved outcomes through better integration of services and targeting of community building and family support resources. Conclusions Our model represents a significant innovation in health needs segmentation. By using whole system linked data, it provides a pragmatic way of profiling complexity for proactive care. Key messages • Complex health and social problems in children cluster in families with adults also having complex needs, so we need to transform fragmented services to support the whole family to improve outcomes. • Household level segmentation using cross-sectoral, whole system data is an innovation to identify households with complex needs with respect to their locality to improve integration of support.

Housing tenure and acute lower respiratory tract infection admissions in two Scottish birth cohorts

Abstract Introduction Early-life acute lower respiratory tract infections (LRTI) have been associated with increased morbidity and mortality. Despite young children spending much of their time at home, the contribution of home ownership status, on LRTI hospital admissions is unknown. Objectives To estimate the association between housing tenure and the odds of LRTI hospitalization in children <2 years in two birth cohorts. Methods De-identified Scottish birth records were linked to maternal Census data (2001 and 2011) and to hospital admission data to construct two birth cohorts (Cohort 1 (C1), born 2000-2002; Cohort 2 (C2), 2010-2012). Using logistic regression we estimated the association of housing tenure (owned, social rented, private rented, rent-free) with the odds of LRTI hospital admission, before and after adjustment for maternal age, residential area, and maternal qualification level. Results Over the 2-year follow-up, there were 14,833 LRTI admissions in 12,527 children (10,832 children had 1 LRTI admission and 1,695 >1 LRTI admission). 75.6 % of all LRTI admissions were due to bronchiolitis. In C1 and C2, 4.0% and 5.3% children, respectively, had one or more LRTI admission. Compared to children living in owned housing, the odds of LRTI admission were higher in children living in social rented housing (C1: Odds ratio=1.40, 95% confidence interval: 1.31-1.49; C2: 1.23, 1.16-1.31), private rented (C1:1.24, 1.11,1.39; C2: 1.14, 1.06-1.21), and rent-free housing (C1: 1.53, 1.35,1.74; C2: 1.04, 0.80-1.36) after confounder adjustment. Conclusions We found an association between non-owned housing and higher odds of LRTI admission which was more marked in C1 than in C2. Further research is warranted to unpick the mechanisms underlying the association between housing tenure and LRTI admission. Interventions to prevent LRTI admissions could usefully target children living in non-owned housing. Key messages • This study demonstrates the value of administrative and health data linkage in improving our understanding of how socio-environmental factors might impact children’s respiratory health. • Children living in social and private rented housing (compared to owned housing) have a higher risk of LRTI hospital admission and could benefit the most from LRTI-lowering interventions.

Administrative data for public health: a regional data warehouse applied to dementia epidemiology

Abstract Administrative data can represent valuable sources of information for researchers seeking to advise policymakers. Several countries have established population-based data warehouses (DWH), integrating multiple data sources in single repositories through data linkage techniques. In Lombardy (Italy), a regional population-based DWH was established in the 1980s. It collects data about citizens from multiple sources in the social and health sectors, anonymising them immediately after their acquisition. Lombardy Region signed a specific agreement with the University of Pavia to investigate the epidemiology and access to care among people living with dementia (PLWD), using the DWH. A retrospective cohort study was conducted on hospitalised PLWD, including people aged ≥ 65 years with diagnoses of dementia at discharge from 2002 to 2020. The aim was to study the trends of hospitalisations among PLWD, computing these by calendar year, age, sex and cause of hospitalisation. A total of 340,144 hospital discharges were registered, of which 211,709 (63.0%) were women and 124,195 (37.0%) were men. The rate of hospitalisation decreased over the study period, ranging from 100.6/10,000 in 2002 to 65.1/10,000 in 2020. The average age at hospitalisation increased for men and women from 78.9 and 81.8 years in 2002 to 82.0 years and 84.2 years, respectively, in 2020. Respiratory diseases caused 10.4% of all hospitalisations in 2002 and grew steadily to 26.8% in 2020, becoming the leading cause of hospital admissions since 2017. Results allowed us to elaborate epidemiological measures and to characterise our population in a wide temporal trend, quantifying access to acute care by leading causes of hospitalisation. However, the analysis of administrative data comes along with several challenges, such as data incompleteness and biases. Researchers should take advantage of these data sources while keeping in mind the limitations and constraints related to data quality.

Algorithm for forming hospital care episodes by combining attendance contacts in the Danish National Patient Register: A methodological consensus-driven study.

Studying complete hospital care episodes from register data, for instance when assessing length of stay, discharges and readmissions, can cause methodological difficulties due to the lack of a contact linkage identifier. We aimed to develop an algorithm combining sequential attendance contacts in the Danish National Patient Register (DNPR) into hospital care episodes, spanning the entire duration and all contacts from hospital arrival to departure. The algorithm was developed under the consensus of experts from research institutions across Denmark. It reads in second and third version DNPR data, deletes contacts without attendance, duplicates elective outpatient contacts corresponding to attendance dates and modifies contact types (e.g. repeated acute contacts), among others. Thereafter, sequential contacts within 4 h are marked as the same hospital care episode, consisting of one or more DNPR contact. We tested the algorithm in a data set of adults living in Denmark during 2013-2021 and compared different hourly cut-offs. For the demonstration, we included 120.2 m contacts from 5.7 m persons, combined into 105.9 m hospital care episodes. Of the hospital care episodes, 6.4% were acute inpatients, 8.3% were acute outpatients, 2.0% were elective inpatients and 83.3% were elective outpatients. Using 4 h as our recommendation, 3-h, 5-h and 6-h cut-offs for contact combining revealed only minor differences in the number of hospital care episodes (<0.4%), whereas 12-h (<1.7%) and 24-h cut-offs (<43.1%) had a larger impact. The algorithm automates data reading, modification and linkage of sequential attendance contacts. The algorithm can be initiated as a SAS macro and is available from an online repository.