International comparisons of 'big' health record data: application to cardiovascular diseases

Lead Research Organisation: University College London
Department Name: Epidemiology and Public Health

Abstract

Cardiovascular diseases (CVD) remain the leading cause of death in the UK and worldwide. With medical advancement in drug treatment and revascularization intervention, the acute hospital treatment phase shortens and the care for CVD has gradually shifted to primary care and community services. International comparisons can provide evidence of performance of health system in CVD care between countries, and thus facilitate learning from better performing systems.

One of the near-term grand challenges is to exploit international structured coded data arising from primary and secondary care to address the gap of putting scientific evidence on prevention and treatment into clinical practice to improve population health. While the quality and comprehensiveness of UK healthcare data is exceptional in world, there are remarkably few instances of UK health records being used in international research contexts. A central bottleneck is knowing what electronic health records (EHR) sources are available for research, and their strengths and weakness. There has been no concerted effort to make such data sources 'discoverable,' shareable or accessible to the international research community. Even the most simple questions (e.g. which countries have primary care data available for research, and which of these can provide meaningful data on smoking, blood pressure and cholesterol) do not have readily accessible answers.

With the support from the MRC Population Health Scientist Fellowship, in close collaboration with the Farr institute, I will expand international collaboration on linked population health records to investigate important research questions on cardiac care, and address some of the barriers in the field of health informatics. I will do this by addressing two interwoven aims:

(i) Clinical research: to address research questions in the prevention and progression of cardiovascular diseases across two or more countries, which can only be tackled using electronic health record data.

(ii) Informatics methods: To facilitate the discovery and documentation of contemporary EHR data sources relevant to cardiovascular disease research in countries with diverse healthcare systems by working in close collaboration with health informatics experts across the Farr Institute.

OBJECTIVES
(i) Clinical research objectives will be first to compare the extent to which adherence to major new guideline recommendations might be associated with reduction in a wide range of CVD in two or more countries. Second, to compare the incidence of CVD, such as heart failure in the short and long term after acute myocardial infarction between two or more countries.

(ii) Informatics method objectives will be first to build an inter-disciplinary, international network of investigators and resources seeking to make EHR data sources discoverable and sharable for cardiovascular research. Second, to facilitate the creation of an international searchable meta-data catalogue of EHR data from different health care settings through the Farr Institute and the Health Informatics Network.

Potential applications and benefits
By focused on CVD, research results are expected to provide insights on effective health system and care strategies to contribute to the health and wellness of the population. The research may contribute to knowledge by firstly providing the unique understanding the quality and outcome consequences of preventive and treatment care across countries. Secondly, and tightly interwoven with the substantive clinical questions, I will be able to contribute to the knowledge of methods by making complex data sources across countries more 'discoverable', and provide the contextual and metadata information required in order to scale replicable research using these data sources. The research will contribute to our knowledge on research collaboration, study coordination and information governance for international health informatics studies.

Technical Summary

Aims and objectives
(i) Clinical research: to address research questions in the prevention and progression of cardiovascular diseases across two or more countries.
(ii) Informatics methods: To facilitate the discovery and documentation of contemporary electronic health records (HER) sources for cardiovascular disease (CVD) research in different.

Methodology
In clinical investigation, I will define strategies of handling data quality and comparability issues, harmonize patient inclusion/exclusion criteria, disease ascertainment, study variables, missing data and analytical protocol across different countries. Statistical analyses steps include: 1) descriptive statistics, 2) survival analysis and longitudinal analyses for observed and adjusted risk estimates, 3) prognosis analysis, 4) estimating missed opportunities burden and its association with excess adverse outcomes between countries. Between country analyses could be implemented via a) secure remote access, b) site visit, and c) a common protocol. Computationally intense analyses, including imputation and multi-level approaches will exploit the Farr high performance computing infrastructure.

In contributing to informatics method, I will be first to build an interdisciplinary, international network of investigators and resources seeking to make EHR data sources discoverable and sharable for cardiovascular research. Second, to contribute to the creation of an international searchable meta-data catalogue of EHR data from different health care settings through the Farr Institute and the Health Informatics Network.

Impact
By focused on CVD, research results may provide insights on effective health system and care strategies for better health and wellness of the population in the UK and worldwide. In methodology, the research will contribute to our knowledge on research collaboration, study coordination and information governance for international studies based on linked electronic health records.

Planned Impact

According to the Chancellor of the Exchequer the UK has the 'world's best and most complete healthcare records'. An overarching impact of my fellowship is to illustrate specific examples of where this may be usefully true and where it is not. The research contributes to the UK's global leadership in EHR research and facilitates the shaping of EHR scientific agenda. By focused on CVD, the area with high burden, the research may contribute to the economic and societal gain of the UK through improving the health and wellness of the population. Individuals can fully engage in life and work with minimum absence or compromise of their capabilities due to diseases. The sharing, learning and transfer of innovations among countries may facilitate the funding leveraged from international partners to support scientists in the UK and worldwide.

By giving greater visibility to the types of data available, their quality and accessibility in different countries, and by working with colleagues in EHR4CR and other international initiatives, my fellowship will impact pharmaceutical industries in their trial pipelines at multiple steps, from initial lower cost feasibility estimates right through to real world evidence studies increasingly required for regulatory approval. The international collaboration established in the proposed research may strengthen the links with industrial partners of the Farr Institute, London (AstraZeneca for example) for novel national and international projects involving industry, funders and researchers across health sectors. I will ensure that my work is aligned with initiatives arising out of the Farr-ABPI (Association of the British Pharmaceutical Industry) forum.

Computing, internet and health record vendor industries: my approach - a 'bottom up' single fellowship involving close clinical collaboration can provide much needed insights for blue chip, small and medium enterprises wanting to develop products in different international markets.

Policy-makers nationally: I seek to leverage the close links with NHS England to inform NHS policy. Specifically the national cardiovascular intelligence network will be directly impacted by my results. With Farr Investigator Deanfield (NICOR) lead and Farr Cardiovascular lead I will seek to ensure that my findings are used to inform quality improvements in the prevention and treatment of CVD as well as initiatives to improve the quality of data collection (e.g. RCP Professional Standards).

International policy: my findings should inform international guidelines for CVD care and data collection standards (for example, the Cardiology Audit and Registration Data Standards).

The third sector: I will seek to work with the British Heart Foundation to complement and modernize their 'Health Statistics' using new opportunities from health record data.

The wider public, patients and their family may be the largest partners in the health system, and the largest long-term beneficiaries of the research. Study results may help to form training for patients or family to understand their health records, and engaging them in the design of better utilisation of care services for managing their health.

Healthcare professionals: I anticipate that my findings will encourage clinicians to develop and share best practice in a 'quality cycle' informed by a 'data cycle' so that improvements in the quality and outcomes of care go hand in hand with improvements in data quality and the way data are used to generate knowledge for decision support.

Timeline and assessment
Year 1: establishment of framework for investigator network, and meta-data for describing data within and across countries. Finalisation of which countries and which datasets will be analysed.
Year 2: completion of first international comparison analysis and manuscript submission.
Year 3: completion of further international comparison publications, communications to all beneficiaries.

Organisations

Publications

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Chung SC (2015) Authors' reply to Gupta. in BMJ (Clinical research ed.)

 
Description UCL Global Engagement Funds
Amount £2,000 (GBP)
Organisation University College London 
Sector Academic/University
Country United Kingdom
Start 08/2018 
End 07/2019
 
Description China and the UK collaboration between national clinical registry for acute myocardial infarction. 
Organisation Brigham and Women's Hospital
Country United States 
Sector Hospitals 
PI Contribution The collaboration is among three nations - the US, China and the UK, where US researchers formed research partnership with the Chinese investigators and together collaborate with our research group in the UK. The objective of the collaboration is to form an international comparison study on the care for acute myocardial infarction (AMI) based on the national representative data from China and the UK. Data in China is the China PEACE-Retrospective AMI study used a two-staged sampling design to produce a nationally-representative cohort of patients treated for AMI in 2001, 2006, and 2011. Hospitals were randomly sampled within five predefined economic-geographic regions, and for each sampled hospital, all AMI cases were identified from patient databases using International Classification of Disease - Clinical Modification codes, or identified by manually reviewing the hospital logbook for patients with an appropriate discharge diagnosis. MINAP is an ongoing nationwide registry of acute coronary syndrome (ACS) hospitalisations in England and Wales. Hospitals are required to report standardised demographic and clinical information to this registry, which allows the pre-hospital course and in-hospital care of ACS patients to be characterised at the national level. The contributions made by me is to liaise with the US and Chinese researchers to form the collaboration through regular discussion on the design and implementation of the collaborative research projects. I am responsible for the UK data and its output to the study, and contribute to ensured the comparability of the data through harmonised approach for data management and analysis in China and the UK. The UK research team provides guidance in the collective leadership and oversees the progress of collaborative project.
Collaborator Contribution The US research team facilitates the collaboration through coordinating the research project, and contributes to its shared leadership with Chinese and UK investigators. The Chines team is responsible for the input from the Chinese PEACE data to the collaborative study. Both the US and Chinese team have engaged in all coordination and communication throughout the collaboration.
Impact The manuscript of study results is submitted for publication: Downing N, Chung SC, Li J, Wang Y, Gale CP, Xi L, Masoudi FA, Weston CF, Timmis A, Hemingway H, Jiang L, Krumholz HM. A Comparison of Hospital Care and Outcomes for ST-Segment Elevation Myocardial Infarction in China and the United Kingdom (submitted to Circulation: Cardiovascular Quality and Outcomes).
Start Year 2015
 
Description China and the UK collaboration between national clinical registry for acute myocardial infarction. 
Organisation Chinese Academy of Medical Sciences (CAMS)
Country China 
Sector Academic/University 
PI Contribution The collaboration is among three nations - the US, China and the UK, where US researchers formed research partnership with the Chinese investigators and together collaborate with our research group in the UK. The objective of the collaboration is to form an international comparison study on the care for acute myocardial infarction (AMI) based on the national representative data from China and the UK. Data in China is the China PEACE-Retrospective AMI study used a two-staged sampling design to produce a nationally-representative cohort of patients treated for AMI in 2001, 2006, and 2011. Hospitals were randomly sampled within five predefined economic-geographic regions, and for each sampled hospital, all AMI cases were identified from patient databases using International Classification of Disease - Clinical Modification codes, or identified by manually reviewing the hospital logbook for patients with an appropriate discharge diagnosis. MINAP is an ongoing nationwide registry of acute coronary syndrome (ACS) hospitalisations in England and Wales. Hospitals are required to report standardised demographic and clinical information to this registry, which allows the pre-hospital course and in-hospital care of ACS patients to be characterised at the national level. The contributions made by me is to liaise with the US and Chinese researchers to form the collaboration through regular discussion on the design and implementation of the collaborative research projects. I am responsible for the UK data and its output to the study, and contribute to ensured the comparability of the data through harmonised approach for data management and analysis in China and the UK. The UK research team provides guidance in the collective leadership and oversees the progress of collaborative project.
Collaborator Contribution The US research team facilitates the collaboration through coordinating the research project, and contributes to its shared leadership with Chinese and UK investigators. The Chines team is responsible for the input from the Chinese PEACE data to the collaborative study. Both the US and Chinese team have engaged in all coordination and communication throughout the collaboration.
Impact The manuscript of study results is submitted for publication: Downing N, Chung SC, Li J, Wang Y, Gale CP, Xi L, Masoudi FA, Weston CF, Timmis A, Hemingway H, Jiang L, Krumholz HM. A Comparison of Hospital Care and Outcomes for ST-Segment Elevation Myocardial Infarction in China and the United Kingdom (submitted to Circulation: Cardiovascular Quality and Outcomes).
Start Year 2015
 
Description China and the UK collaboration between national clinical registry for acute myocardial infarction. 
Organisation Fuwai Cardiovascular Hospital
Country China 
Sector Hospitals 
PI Contribution The collaboration is among three nations - the US, China and the UK, where US researchers formed research partnership with the Chinese investigators and together collaborate with our research group in the UK. The objective of the collaboration is to form an international comparison study on the care for acute myocardial infarction (AMI) based on the national representative data from China and the UK. Data in China is the China PEACE-Retrospective AMI study used a two-staged sampling design to produce a nationally-representative cohort of patients treated for AMI in 2001, 2006, and 2011. Hospitals were randomly sampled within five predefined economic-geographic regions, and for each sampled hospital, all AMI cases were identified from patient databases using International Classification of Disease - Clinical Modification codes, or identified by manually reviewing the hospital logbook for patients with an appropriate discharge diagnosis. MINAP is an ongoing nationwide registry of acute coronary syndrome (ACS) hospitalisations in England and Wales. Hospitals are required to report standardised demographic and clinical information to this registry, which allows the pre-hospital course and in-hospital care of ACS patients to be characterised at the national level. The contributions made by me is to liaise with the US and Chinese researchers to form the collaboration through regular discussion on the design and implementation of the collaborative research projects. I am responsible for the UK data and its output to the study, and contribute to ensured the comparability of the data through harmonised approach for data management and analysis in China and the UK. The UK research team provides guidance in the collective leadership and oversees the progress of collaborative project.
Collaborator Contribution The US research team facilitates the collaboration through coordinating the research project, and contributes to its shared leadership with Chinese and UK investigators. The Chines team is responsible for the input from the Chinese PEACE data to the collaborative study. Both the US and Chinese team have engaged in all coordination and communication throughout the collaboration.
Impact The manuscript of study results is submitted for publication: Downing N, Chung SC, Li J, Wang Y, Gale CP, Xi L, Masoudi FA, Weston CF, Timmis A, Hemingway H, Jiang L, Krumholz HM. A Comparison of Hospital Care and Outcomes for ST-Segment Elevation Myocardial Infarction in China and the United Kingdom (submitted to Circulation: Cardiovascular Quality and Outcomes).
Start Year 2015
 
Description China and the UK collaboration between national clinical registry for acute myocardial infarction. 
Organisation Peking Union Medical College
Country China 
Sector Academic/University 
PI Contribution The collaboration is among three nations - the US, China and the UK, where US researchers formed research partnership with the Chinese investigators and together collaborate with our research group in the UK. The objective of the collaboration is to form an international comparison study on the care for acute myocardial infarction (AMI) based on the national representative data from China and the UK. Data in China is the China PEACE-Retrospective AMI study used a two-staged sampling design to produce a nationally-representative cohort of patients treated for AMI in 2001, 2006, and 2011. Hospitals were randomly sampled within five predefined economic-geographic regions, and for each sampled hospital, all AMI cases were identified from patient databases using International Classification of Disease - Clinical Modification codes, or identified by manually reviewing the hospital logbook for patients with an appropriate discharge diagnosis. MINAP is an ongoing nationwide registry of acute coronary syndrome (ACS) hospitalisations in England and Wales. Hospitals are required to report standardised demographic and clinical information to this registry, which allows the pre-hospital course and in-hospital care of ACS patients to be characterised at the national level. The contributions made by me is to liaise with the US and Chinese researchers to form the collaboration through regular discussion on the design and implementation of the collaborative research projects. I am responsible for the UK data and its output to the study, and contribute to ensured the comparability of the data through harmonised approach for data management and analysis in China and the UK. The UK research team provides guidance in the collective leadership and oversees the progress of collaborative project.
Collaborator Contribution The US research team facilitates the collaboration through coordinating the research project, and contributes to its shared leadership with Chinese and UK investigators. The Chines team is responsible for the input from the Chinese PEACE data to the collaborative study. Both the US and Chinese team have engaged in all coordination and communication throughout the collaboration.
Impact The manuscript of study results is submitted for publication: Downing N, Chung SC, Li J, Wang Y, Gale CP, Xi L, Masoudi FA, Weston CF, Timmis A, Hemingway H, Jiang L, Krumholz HM. A Comparison of Hospital Care and Outcomes for ST-Segment Elevation Myocardial Infarction in China and the United Kingdom (submitted to Circulation: Cardiovascular Quality and Outcomes).
Start Year 2015
 
Description China and the UK collaboration between national clinical registry for acute myocardial infarction. 
Organisation University of Colorado
Department Division of Cardiology
Country United States 
Sector Hospitals 
PI Contribution The collaboration is among three nations - the US, China and the UK, where US researchers formed research partnership with the Chinese investigators and together collaborate with our research group in the UK. The objective of the collaboration is to form an international comparison study on the care for acute myocardial infarction (AMI) based on the national representative data from China and the UK. Data in China is the China PEACE-Retrospective AMI study used a two-staged sampling design to produce a nationally-representative cohort of patients treated for AMI in 2001, 2006, and 2011. Hospitals were randomly sampled within five predefined economic-geographic regions, and for each sampled hospital, all AMI cases were identified from patient databases using International Classification of Disease - Clinical Modification codes, or identified by manually reviewing the hospital logbook for patients with an appropriate discharge diagnosis. MINAP is an ongoing nationwide registry of acute coronary syndrome (ACS) hospitalisations in England and Wales. Hospitals are required to report standardised demographic and clinical information to this registry, which allows the pre-hospital course and in-hospital care of ACS patients to be characterised at the national level. The contributions made by me is to liaise with the US and Chinese researchers to form the collaboration through regular discussion on the design and implementation of the collaborative research projects. I am responsible for the UK data and its output to the study, and contribute to ensured the comparability of the data through harmonised approach for data management and analysis in China and the UK. The UK research team provides guidance in the collective leadership and oversees the progress of collaborative project.
Collaborator Contribution The US research team facilitates the collaboration through coordinating the research project, and contributes to its shared leadership with Chinese and UK investigators. The Chines team is responsible for the input from the Chinese PEACE data to the collaborative study. Both the US and Chinese team have engaged in all coordination and communication throughout the collaboration.
Impact The manuscript of study results is submitted for publication: Downing N, Chung SC, Li J, Wang Y, Gale CP, Xi L, Masoudi FA, Weston CF, Timmis A, Hemingway H, Jiang L, Krumholz HM. A Comparison of Hospital Care and Outcomes for ST-Segment Elevation Myocardial Infarction in China and the United Kingdom (submitted to Circulation: Cardiovascular Quality and Outcomes).
Start Year 2015
 
Description China and the UK collaboration between national clinical registry for acute myocardial infarction. 
Organisation Yale New Haven Hospital
Country United States 
Sector Hospitals 
PI Contribution The collaboration is among three nations - the US, China and the UK, where US researchers formed research partnership with the Chinese investigators and together collaborate with our research group in the UK. The objective of the collaboration is to form an international comparison study on the care for acute myocardial infarction (AMI) based on the national representative data from China and the UK. Data in China is the China PEACE-Retrospective AMI study used a two-staged sampling design to produce a nationally-representative cohort of patients treated for AMI in 2001, 2006, and 2011. Hospitals were randomly sampled within five predefined economic-geographic regions, and for each sampled hospital, all AMI cases were identified from patient databases using International Classification of Disease - Clinical Modification codes, or identified by manually reviewing the hospital logbook for patients with an appropriate discharge diagnosis. MINAP is an ongoing nationwide registry of acute coronary syndrome (ACS) hospitalisations in England and Wales. Hospitals are required to report standardised demographic and clinical information to this registry, which allows the pre-hospital course and in-hospital care of ACS patients to be characterised at the national level. The contributions made by me is to liaise with the US and Chinese researchers to form the collaboration through regular discussion on the design and implementation of the collaborative research projects. I am responsible for the UK data and its output to the study, and contribute to ensured the comparability of the data through harmonised approach for data management and analysis in China and the UK. The UK research team provides guidance in the collective leadership and oversees the progress of collaborative project.
Collaborator Contribution The US research team facilitates the collaboration through coordinating the research project, and contributes to its shared leadership with Chinese and UK investigators. The Chines team is responsible for the input from the Chinese PEACE data to the collaborative study. Both the US and Chinese team have engaged in all coordination and communication throughout the collaboration.
Impact The manuscript of study results is submitted for publication: Downing N, Chung SC, Li J, Wang Y, Gale CP, Xi L, Masoudi FA, Weston CF, Timmis A, Hemingway H, Jiang L, Krumholz HM. A Comparison of Hospital Care and Outcomes for ST-Segment Elevation Myocardial Infarction in China and the United Kingdom (submitted to Circulation: Cardiovascular Quality and Outcomes).
Start Year 2015
 
Description China and the UK collaboration between national clinical registry for acute myocardial infarction. 
Organisation Yale University
Department Department of Internal Medicine
Country United States 
Sector Academic/University 
PI Contribution The collaboration is among three nations - the US, China and the UK, where US researchers formed research partnership with the Chinese investigators and together collaborate with our research group in the UK. The objective of the collaboration is to form an international comparison study on the care for acute myocardial infarction (AMI) based on the national representative data from China and the UK. Data in China is the China PEACE-Retrospective AMI study used a two-staged sampling design to produce a nationally-representative cohort of patients treated for AMI in 2001, 2006, and 2011. Hospitals were randomly sampled within five predefined economic-geographic regions, and for each sampled hospital, all AMI cases were identified from patient databases using International Classification of Disease - Clinical Modification codes, or identified by manually reviewing the hospital logbook for patients with an appropriate discharge diagnosis. MINAP is an ongoing nationwide registry of acute coronary syndrome (ACS) hospitalisations in England and Wales. Hospitals are required to report standardised demographic and clinical information to this registry, which allows the pre-hospital course and in-hospital care of ACS patients to be characterised at the national level. The contributions made by me is to liaise with the US and Chinese researchers to form the collaboration through regular discussion on the design and implementation of the collaborative research projects. I am responsible for the UK data and its output to the study, and contribute to ensured the comparability of the data through harmonised approach for data management and analysis in China and the UK. The UK research team provides guidance in the collective leadership and oversees the progress of collaborative project.
Collaborator Contribution The US research team facilitates the collaboration through coordinating the research project, and contributes to its shared leadership with Chinese and UK investigators. The Chines team is responsible for the input from the Chinese PEACE data to the collaborative study. Both the US and Chinese team have engaged in all coordination and communication throughout the collaboration.
Impact The manuscript of study results is submitted for publication: Downing N, Chung SC, Li J, Wang Y, Gale CP, Xi L, Masoudi FA, Weston CF, Timmis A, Hemingway H, Jiang L, Krumholz HM. A Comparison of Hospital Care and Outcomes for ST-Segment Elevation Myocardial Infarction in China and the United Kingdom (submitted to Circulation: Cardiovascular Quality and Outcomes).
Start Year 2015
 
Description China and the UK collaboration between national clinical registry for acute myocardial infarction. 
Organisation Yale University
Department School of Public Health
Country United States 
Sector Hospitals 
PI Contribution The collaboration is among three nations - the US, China and the UK, where US researchers formed research partnership with the Chinese investigators and together collaborate with our research group in the UK. The objective of the collaboration is to form an international comparison study on the care for acute myocardial infarction (AMI) based on the national representative data from China and the UK. Data in China is the China PEACE-Retrospective AMI study used a two-staged sampling design to produce a nationally-representative cohort of patients treated for AMI in 2001, 2006, and 2011. Hospitals were randomly sampled within five predefined economic-geographic regions, and for each sampled hospital, all AMI cases were identified from patient databases using International Classification of Disease - Clinical Modification codes, or identified by manually reviewing the hospital logbook for patients with an appropriate discharge diagnosis. MINAP is an ongoing nationwide registry of acute coronary syndrome (ACS) hospitalisations in England and Wales. Hospitals are required to report standardised demographic and clinical information to this registry, which allows the pre-hospital course and in-hospital care of ACS patients to be characterised at the national level. The contributions made by me is to liaise with the US and Chinese researchers to form the collaboration through regular discussion on the design and implementation of the collaborative research projects. I am responsible for the UK data and its output to the study, and contribute to ensured the comparability of the data through harmonised approach for data management and analysis in China and the UK. The UK research team provides guidance in the collective leadership and oversees the progress of collaborative project.
Collaborator Contribution The US research team facilitates the collaboration through coordinating the research project, and contributes to its shared leadership with Chinese and UK investigators. The Chines team is responsible for the input from the Chinese PEACE data to the collaborative study. Both the US and Chinese team have engaged in all coordination and communication throughout the collaboration.
Impact The manuscript of study results is submitted for publication: Downing N, Chung SC, Li J, Wang Y, Gale CP, Xi L, Masoudi FA, Weston CF, Timmis A, Hemingway H, Jiang L, Krumholz HM. A Comparison of Hospital Care and Outcomes for ST-Segment Elevation Myocardial Infarction in China and the United Kingdom (submitted to Circulation: Cardiovascular Quality and Outcomes).
Start Year 2015
 
Description Collaboration in the European BigData@Heart Consortium, a research consortium of the Innovative Medicines Initiative (IMI), a public-private initiative between the European Union and the pharmaceutical industry association, the European Federation of Pharmaceutical Industries and Associations (EFPIA). 
Organisation Actelion Pharmaceuticals Ltd
Country United Kingdom 
Sector Private 
PI Contribution Collaborated with researchers from the University Medical Center Utrecht, we aim to contribute to the research consortium with the investigation on the differences in the heart failure treatment and survival: a comparison between Sweden, United Kingdom, Netherlands and Spain using Linked Electronic Health Care Records. Heart failure (HF) remains a major public health issue, resulting in substantial morbidity, mortality and considerable health care costs, and myocardial infarction (MI) is one of the leading causes of heart failure (HF). MI and HF together impose a major burden on health care systems worldwide. Attributes of health care systems, such as incidence, length of stay, outcomes of hospital admissions, medication or guideline adherence could be associated with disease outcome. Though, studies that examine both health care and disease outcomes are lacking. Consequently, recognition is growing for comparative effectiveness research to improve quality and outcomes of health care. International comparisons of whole healthcare systems might yield important knowledge of distinct differences in HF care. The objective of our investigation is thus to 1) compare HF care between UK, Sweden, Spain and the Netherlands using comparable cohorts of HF patients during similar time periods, and, 2) to study how MI and HF interplay in the modern era of coronary care units, PCI technology and effective therapy in different health care systems to further harness learning opportunities. Method Population data In the UK, information about HF care would be obtained from CALIBER (CArdiovascular research using LInked Bespoke studies and Electronic Health Records). This registry links three sources of electronic health records in England: primary care records in practices contributing to the Clinical Practice Research Datalink (CPRD), secondary care hospital discharges in Hospital Episodes Statistics (HES) and the national death registration in the Office for National Statistics (ONS) registry. In Sweden, the Swedish Heart Failure Registry (SwedeHF) for long-term follow-up of HF management would be used. In the Netherlands, a nationwide HF registry is available through linkage of the Population Register, Hospital Discharge Register, and cause of death register. Additional linkage with Vektis (insurance company data) provides information about prescriptions of medication and use of care. Lastly, in Spain ABUCASIS, an electronic centralized clinical record system for primary and secondary ambulatory care in the Valencia Community would be used for the international comparison of HF care. The common denominator of all four registries is patients hospitalised for HF. Our study focuses on the follow-up of these patients, with a common follow-time between the registries from 2008 - 2014. Patients are followed until death, as defined in the national mortality registrations of the participant countries. In collaboration with the Hyve, a company that specialises in data management, our team harmonises the data from all registries to create a common model which can be applied to all, Definition of heart failure and myocardial infarction Patients included in the study are 30 years and older and have been diagnosed with HF through an ICD-10/ICD-9 code for HF (ICD-10: I11.0, I13.0, I13.2, I26.0, I50/ ICD-9: 402.01, 402.11, 402.91, 428, 398.91). For the post-MI HF studies, early-onset (in-hospital HF identified by a set of clinical parameters that define it) and late-onset HF post-MI HF (from ICD-10/ICD 9 codes for HF) are studied. Clinical outcomes The primary endpoint is the short and long-term all-cause mortality patterns as well as differences in temporal trends. Short-term mortality is defined as 30-day and 1-year mortality, whereas long-term mortality is defined as 5-year mortality. Statistical analyses Baseline patient characteristics are summarised as mean (SD) or median [IQR] for continuous variables and percentages for categorical variables. A Chi-square test is used to compare data for categorical variables, a t-test to compare means, and the Kruskal-Wallis for medians. To compare the crude and case-mix adjusted mortality across countries, we compare the 30-day, 1-year and 5-year mortality outcomes with Kaplan-Meier analysis. Cox proportional hazard model is used to estimate the case-mix adjusted mortality. Variables for case-mix adjustment are age, sex, year of admission, length of hospital admission, obesity, smoking, history of diabetes, hypertension. The mortality and association between HF/MI care on mortality are compared across the health care systems of the four countries. Results and impact With this project we aim to give an overview of the status of heart failure care and myocardial infarction care as well as potential differences in patient characteristics in European countries and highlight differences could attribute to medication uptake and mortality. We hope to create insight in the burden of HF based on real-world evidence. Other important impacts of the study include the establishment of an international co-operation on HF research, development of the BigData@Heart network and fostering a collaboration between academia and industry in heart failure and myocardial infarction research.
Collaborator Contribution The partners have contributed to the collaboration in the following aspects: 1. Assemble a unique cross-European dataset of electronic health records. 2. Create systems to develop and test the methodology for high-power identification, harmonisation, access and analysis of the assembled data. 3. Provide clinical input for disease definitions and health system characterisation. 4. Leverage the access to other unique databases. 5. Provide technical input to establish a scalable method to maximise impact and speed at which the results will be broadly implemented in other EU and non-EU countries.
Impact The project is multi-disciplinary, including the training of information science, data science, cardiology, and clinical epidemiology. Since February 2018, it has been granted a € 135.000 grant from the IMI BigData@Heart, UMCU.
Start Year 2017
 
Description Collaboration in the European BigData@Heart Consortium, a research consortium of the Innovative Medicines Initiative (IMI), a public-private initiative between the European Union and the pharmaceutical industry association, the European Federation of Pharmaceutical Industries and Associations (EFPIA). 
Organisation Bayer
Country Germany 
Sector Private 
PI Contribution Collaborated with researchers from the University Medical Center Utrecht, we aim to contribute to the research consortium with the investigation on the differences in the heart failure treatment and survival: a comparison between Sweden, United Kingdom, Netherlands and Spain using Linked Electronic Health Care Records. Heart failure (HF) remains a major public health issue, resulting in substantial morbidity, mortality and considerable health care costs, and myocardial infarction (MI) is one of the leading causes of heart failure (HF). MI and HF together impose a major burden on health care systems worldwide. Attributes of health care systems, such as incidence, length of stay, outcomes of hospital admissions, medication or guideline adherence could be associated with disease outcome. Though, studies that examine both health care and disease outcomes are lacking. Consequently, recognition is growing for comparative effectiveness research to improve quality and outcomes of health care. International comparisons of whole healthcare systems might yield important knowledge of distinct differences in HF care. The objective of our investigation is thus to 1) compare HF care between UK, Sweden, Spain and the Netherlands using comparable cohorts of HF patients during similar time periods, and, 2) to study how MI and HF interplay in the modern era of coronary care units, PCI technology and effective therapy in different health care systems to further harness learning opportunities. Method Population data In the UK, information about HF care would be obtained from CALIBER (CArdiovascular research using LInked Bespoke studies and Electronic Health Records). This registry links three sources of electronic health records in England: primary care records in practices contributing to the Clinical Practice Research Datalink (CPRD), secondary care hospital discharges in Hospital Episodes Statistics (HES) and the national death registration in the Office for National Statistics (ONS) registry. In Sweden, the Swedish Heart Failure Registry (SwedeHF) for long-term follow-up of HF management would be used. In the Netherlands, a nationwide HF registry is available through linkage of the Population Register, Hospital Discharge Register, and cause of death register. Additional linkage with Vektis (insurance company data) provides information about prescriptions of medication and use of care. Lastly, in Spain ABUCASIS, an electronic centralized clinical record system for primary and secondary ambulatory care in the Valencia Community would be used for the international comparison of HF care. The common denominator of all four registries is patients hospitalised for HF. Our study focuses on the follow-up of these patients, with a common follow-time between the registries from 2008 - 2014. Patients are followed until death, as defined in the national mortality registrations of the participant countries. In collaboration with the Hyve, a company that specialises in data management, our team harmonises the data from all registries to create a common model which can be applied to all, Definition of heart failure and myocardial infarction Patients included in the study are 30 years and older and have been diagnosed with HF through an ICD-10/ICD-9 code for HF (ICD-10: I11.0, I13.0, I13.2, I26.0, I50/ ICD-9: 402.01, 402.11, 402.91, 428, 398.91). For the post-MI HF studies, early-onset (in-hospital HF identified by a set of clinical parameters that define it) and late-onset HF post-MI HF (from ICD-10/ICD 9 codes for HF) are studied. Clinical outcomes The primary endpoint is the short and long-term all-cause mortality patterns as well as differences in temporal trends. Short-term mortality is defined as 30-day and 1-year mortality, whereas long-term mortality is defined as 5-year mortality. Statistical analyses Baseline patient characteristics are summarised as mean (SD) or median [IQR] for continuous variables and percentages for categorical variables. A Chi-square test is used to compare data for categorical variables, a t-test to compare means, and the Kruskal-Wallis for medians. To compare the crude and case-mix adjusted mortality across countries, we compare the 30-day, 1-year and 5-year mortality outcomes with Kaplan-Meier analysis. Cox proportional hazard model is used to estimate the case-mix adjusted mortality. Variables for case-mix adjustment are age, sex, year of admission, length of hospital admission, obesity, smoking, history of diabetes, hypertension. The mortality and association between HF/MI care on mortality are compared across the health care systems of the four countries. Results and impact With this project we aim to give an overview of the status of heart failure care and myocardial infarction care as well as potential differences in patient characteristics in European countries and highlight differences could attribute to medication uptake and mortality. We hope to create insight in the burden of HF based on real-world evidence. Other important impacts of the study include the establishment of an international co-operation on HF research, development of the BigData@Heart network and fostering a collaboration between academia and industry in heart failure and myocardial infarction research.
Collaborator Contribution The partners have contributed to the collaboration in the following aspects: 1. Assemble a unique cross-European dataset of electronic health records. 2. Create systems to develop and test the methodology for high-power identification, harmonisation, access and analysis of the assembled data. 3. Provide clinical input for disease definitions and health system characterisation. 4. Leverage the access to other unique databases. 5. Provide technical input to establish a scalable method to maximise impact and speed at which the results will be broadly implemented in other EU and non-EU countries.
Impact The project is multi-disciplinary, including the training of information science, data science, cardiology, and clinical epidemiology. Since February 2018, it has been granted a € 135.000 grant from the IMI BigData@Heart, UMCU.
Start Year 2017
 
Description Collaboration in the European BigData@Heart Consortium, a research consortium of the Innovative Medicines Initiative (IMI), a public-private initiative between the European Union and the pharmaceutical industry association, the European Federation of Pharmaceutical Industries and Associations (EFPIA). 
Organisation European Heart Network EHN
Country Belgium 
Sector Charity/Non Profit 
PI Contribution Collaborated with researchers from the University Medical Center Utrecht, we aim to contribute to the research consortium with the investigation on the differences in the heart failure treatment and survival: a comparison between Sweden, United Kingdom, Netherlands and Spain using Linked Electronic Health Care Records. Heart failure (HF) remains a major public health issue, resulting in substantial morbidity, mortality and considerable health care costs, and myocardial infarction (MI) is one of the leading causes of heart failure (HF). MI and HF together impose a major burden on health care systems worldwide. Attributes of health care systems, such as incidence, length of stay, outcomes of hospital admissions, medication or guideline adherence could be associated with disease outcome. Though, studies that examine both health care and disease outcomes are lacking. Consequently, recognition is growing for comparative effectiveness research to improve quality and outcomes of health care. International comparisons of whole healthcare systems might yield important knowledge of distinct differences in HF care. The objective of our investigation is thus to 1) compare HF care between UK, Sweden, Spain and the Netherlands using comparable cohorts of HF patients during similar time periods, and, 2) to study how MI and HF interplay in the modern era of coronary care units, PCI technology and effective therapy in different health care systems to further harness learning opportunities. Method Population data In the UK, information about HF care would be obtained from CALIBER (CArdiovascular research using LInked Bespoke studies and Electronic Health Records). This registry links three sources of electronic health records in England: primary care records in practices contributing to the Clinical Practice Research Datalink (CPRD), secondary care hospital discharges in Hospital Episodes Statistics (HES) and the national death registration in the Office for National Statistics (ONS) registry. In Sweden, the Swedish Heart Failure Registry (SwedeHF) for long-term follow-up of HF management would be used. In the Netherlands, a nationwide HF registry is available through linkage of the Population Register, Hospital Discharge Register, and cause of death register. Additional linkage with Vektis (insurance company data) provides information about prescriptions of medication and use of care. Lastly, in Spain ABUCASIS, an electronic centralized clinical record system for primary and secondary ambulatory care in the Valencia Community would be used for the international comparison of HF care. The common denominator of all four registries is patients hospitalised for HF. Our study focuses on the follow-up of these patients, with a common follow-time between the registries from 2008 - 2014. Patients are followed until death, as defined in the national mortality registrations of the participant countries. In collaboration with the Hyve, a company that specialises in data management, our team harmonises the data from all registries to create a common model which can be applied to all, Definition of heart failure and myocardial infarction Patients included in the study are 30 years and older and have been diagnosed with HF through an ICD-10/ICD-9 code for HF (ICD-10: I11.0, I13.0, I13.2, I26.0, I50/ ICD-9: 402.01, 402.11, 402.91, 428, 398.91). For the post-MI HF studies, early-onset (in-hospital HF identified by a set of clinical parameters that define it) and late-onset HF post-MI HF (from ICD-10/ICD 9 codes for HF) are studied. Clinical outcomes The primary endpoint is the short and long-term all-cause mortality patterns as well as differences in temporal trends. Short-term mortality is defined as 30-day and 1-year mortality, whereas long-term mortality is defined as 5-year mortality. Statistical analyses Baseline patient characteristics are summarised as mean (SD) or median [IQR] for continuous variables and percentages for categorical variables. A Chi-square test is used to compare data for categorical variables, a t-test to compare means, and the Kruskal-Wallis for medians. To compare the crude and case-mix adjusted mortality across countries, we compare the 30-day, 1-year and 5-year mortality outcomes with Kaplan-Meier analysis. Cox proportional hazard model is used to estimate the case-mix adjusted mortality. Variables for case-mix adjustment are age, sex, year of admission, length of hospital admission, obesity, smoking, history of diabetes, hypertension. The mortality and association between HF/MI care on mortality are compared across the health care systems of the four countries. Results and impact With this project we aim to give an overview of the status of heart failure care and myocardial infarction care as well as potential differences in patient characteristics in European countries and highlight differences could attribute to medication uptake and mortality. We hope to create insight in the burden of HF based on real-world evidence. Other important impacts of the study include the establishment of an international co-operation on HF research, development of the BigData@Heart network and fostering a collaboration between academia and industry in heart failure and myocardial infarction research.
Collaborator Contribution The partners have contributed to the collaboration in the following aspects: 1. Assemble a unique cross-European dataset of electronic health records. 2. Create systems to develop and test the methodology for high-power identification, harmonisation, access and analysis of the assembled data. 3. Provide clinical input for disease definitions and health system characterisation. 4. Leverage the access to other unique databases. 5. Provide technical input to establish a scalable method to maximise impact and speed at which the results will be broadly implemented in other EU and non-EU countries.
Impact The project is multi-disciplinary, including the training of information science, data science, cardiology, and clinical epidemiology. Since February 2018, it has been granted a € 135.000 grant from the IMI BigData@Heart, UMCU.
Start Year 2017
 
Description Collaboration in the European BigData@Heart Consortium, a research consortium of the Innovative Medicines Initiative (IMI), a public-private initiative between the European Union and the pharmaceutical industry association, the European Federation of Pharmaceutical Industries and Associations (EFPIA). 
Organisation European Society of Cardiology (ESC)
Country European Union (EU) 
Sector Charity/Non Profit 
PI Contribution Collaborated with researchers from the University Medical Center Utrecht, we aim to contribute to the research consortium with the investigation on the differences in the heart failure treatment and survival: a comparison between Sweden, United Kingdom, Netherlands and Spain using Linked Electronic Health Care Records. Heart failure (HF) remains a major public health issue, resulting in substantial morbidity, mortality and considerable health care costs, and myocardial infarction (MI) is one of the leading causes of heart failure (HF). MI and HF together impose a major burden on health care systems worldwide. Attributes of health care systems, such as incidence, length of stay, outcomes of hospital admissions, medication or guideline adherence could be associated with disease outcome. Though, studies that examine both health care and disease outcomes are lacking. Consequently, recognition is growing for comparative effectiveness research to improve quality and outcomes of health care. International comparisons of whole healthcare systems might yield important knowledge of distinct differences in HF care. The objective of our investigation is thus to 1) compare HF care between UK, Sweden, Spain and the Netherlands using comparable cohorts of HF patients during similar time periods, and, 2) to study how MI and HF interplay in the modern era of coronary care units, PCI technology and effective therapy in different health care systems to further harness learning opportunities. Method Population data In the UK, information about HF care would be obtained from CALIBER (CArdiovascular research using LInked Bespoke studies and Electronic Health Records). This registry links three sources of electronic health records in England: primary care records in practices contributing to the Clinical Practice Research Datalink (CPRD), secondary care hospital discharges in Hospital Episodes Statistics (HES) and the national death registration in the Office for National Statistics (ONS) registry. In Sweden, the Swedish Heart Failure Registry (SwedeHF) for long-term follow-up of HF management would be used. In the Netherlands, a nationwide HF registry is available through linkage of the Population Register, Hospital Discharge Register, and cause of death register. Additional linkage with Vektis (insurance company data) provides information about prescriptions of medication and use of care. Lastly, in Spain ABUCASIS, an electronic centralized clinical record system for primary and secondary ambulatory care in the Valencia Community would be used for the international comparison of HF care. The common denominator of all four registries is patients hospitalised for HF. Our study focuses on the follow-up of these patients, with a common follow-time between the registries from 2008 - 2014. Patients are followed until death, as defined in the national mortality registrations of the participant countries. In collaboration with the Hyve, a company that specialises in data management, our team harmonises the data from all registries to create a common model which can be applied to all, Definition of heart failure and myocardial infarction Patients included in the study are 30 years and older and have been diagnosed with HF through an ICD-10/ICD-9 code for HF (ICD-10: I11.0, I13.0, I13.2, I26.0, I50/ ICD-9: 402.01, 402.11, 402.91, 428, 398.91). For the post-MI HF studies, early-onset (in-hospital HF identified by a set of clinical parameters that define it) and late-onset HF post-MI HF (from ICD-10/ICD 9 codes for HF) are studied. Clinical outcomes The primary endpoint is the short and long-term all-cause mortality patterns as well as differences in temporal trends. Short-term mortality is defined as 30-day and 1-year mortality, whereas long-term mortality is defined as 5-year mortality. Statistical analyses Baseline patient characteristics are summarised as mean (SD) or median [IQR] for continuous variables and percentages for categorical variables. A Chi-square test is used to compare data for categorical variables, a t-test to compare means, and the Kruskal-Wallis for medians. To compare the crude and case-mix adjusted mortality across countries, we compare the 30-day, 1-year and 5-year mortality outcomes with Kaplan-Meier analysis. Cox proportional hazard model is used to estimate the case-mix adjusted mortality. Variables for case-mix adjustment are age, sex, year of admission, length of hospital admission, obesity, smoking, history of diabetes, hypertension. The mortality and association between HF/MI care on mortality are compared across the health care systems of the four countries. Results and impact With this project we aim to give an overview of the status of heart failure care and myocardial infarction care as well as potential differences in patient characteristics in European countries and highlight differences could attribute to medication uptake and mortality. We hope to create insight in the burden of HF based on real-world evidence. Other important impacts of the study include the establishment of an international co-operation on HF research, development of the BigData@Heart network and fostering a collaboration between academia and industry in heart failure and myocardial infarction research.
Collaborator Contribution The partners have contributed to the collaboration in the following aspects: 1. Assemble a unique cross-European dataset of electronic health records. 2. Create systems to develop and test the methodology for high-power identification, harmonisation, access and analysis of the assembled data. 3. Provide clinical input for disease definitions and health system characterisation. 4. Leverage the access to other unique databases. 5. Provide technical input to establish a scalable method to maximise impact and speed at which the results will be broadly implemented in other EU and non-EU countries.
Impact The project is multi-disciplinary, including the training of information science, data science, cardiology, and clinical epidemiology. Since February 2018, it has been granted a € 135.000 grant from the IMI BigData@Heart, UMCU.
Start Year 2017
 
Description Collaboration in the European BigData@Heart Consortium, a research consortium of the Innovative Medicines Initiative (IMI), a public-private initiative between the European Union and the pharmaceutical industry association, the European Federation of Pharmaceutical Industries and Associations (EFPIA). 
Organisation Fundacion Para La Investigacion Del Hospital Universitario La Fe De La Comunidad Valenciana
PI Contribution Collaborated with researchers from the University Medical Center Utrecht, we aim to contribute to the research consortium with the investigation on the differences in the heart failure treatment and survival: a comparison between Sweden, United Kingdom, Netherlands and Spain using Linked Electronic Health Care Records. Heart failure (HF) remains a major public health issue, resulting in substantial morbidity, mortality and considerable health care costs, and myocardial infarction (MI) is one of the leading causes of heart failure (HF). MI and HF together impose a major burden on health care systems worldwide. Attributes of health care systems, such as incidence, length of stay, outcomes of hospital admissions, medication or guideline adherence could be associated with disease outcome. Though, studies that examine both health care and disease outcomes are lacking. Consequently, recognition is growing for comparative effectiveness research to improve quality and outcomes of health care. International comparisons of whole healthcare systems might yield important knowledge of distinct differences in HF care. The objective of our investigation is thus to 1) compare HF care between UK, Sweden, Spain and the Netherlands using comparable cohorts of HF patients during similar time periods, and, 2) to study how MI and HF interplay in the modern era of coronary care units, PCI technology and effective therapy in different health care systems to further harness learning opportunities. Method Population data In the UK, information about HF care would be obtained from CALIBER (CArdiovascular research using LInked Bespoke studies and Electronic Health Records). This registry links three sources of electronic health records in England: primary care records in practices contributing to the Clinical Practice Research Datalink (CPRD), secondary care hospital discharges in Hospital Episodes Statistics (HES) and the national death registration in the Office for National Statistics (ONS) registry. In Sweden, the Swedish Heart Failure Registry (SwedeHF) for long-term follow-up of HF management would be used. In the Netherlands, a nationwide HF registry is available through linkage of the Population Register, Hospital Discharge Register, and cause of death register. Additional linkage with Vektis (insurance company data) provides information about prescriptions of medication and use of care. Lastly, in Spain ABUCASIS, an electronic centralized clinical record system for primary and secondary ambulatory care in the Valencia Community would be used for the international comparison of HF care. The common denominator of all four registries is patients hospitalised for HF. Our study focuses on the follow-up of these patients, with a common follow-time between the registries from 2008 - 2014. Patients are followed until death, as defined in the national mortality registrations of the participant countries. In collaboration with the Hyve, a company that specialises in data management, our team harmonises the data from all registries to create a common model which can be applied to all, Definition of heart failure and myocardial infarction Patients included in the study are 30 years and older and have been diagnosed with HF through an ICD-10/ICD-9 code for HF (ICD-10: I11.0, I13.0, I13.2, I26.0, I50/ ICD-9: 402.01, 402.11, 402.91, 428, 398.91). For the post-MI HF studies, early-onset (in-hospital HF identified by a set of clinical parameters that define it) and late-onset HF post-MI HF (from ICD-10/ICD 9 codes for HF) are studied. Clinical outcomes The primary endpoint is the short and long-term all-cause mortality patterns as well as differences in temporal trends. Short-term mortality is defined as 30-day and 1-year mortality, whereas long-term mortality is defined as 5-year mortality. Statistical analyses Baseline patient characteristics are summarised as mean (SD) or median [IQR] for continuous variables and percentages for categorical variables. A Chi-square test is used to compare data for categorical variables, a t-test to compare means, and the Kruskal-Wallis for medians. To compare the crude and case-mix adjusted mortality across countries, we compare the 30-day, 1-year and 5-year mortality outcomes with Kaplan-Meier analysis. Cox proportional hazard model is used to estimate the case-mix adjusted mortality. Variables for case-mix adjustment are age, sex, year of admission, length of hospital admission, obesity, smoking, history of diabetes, hypertension. The mortality and association between HF/MI care on mortality are compared across the health care systems of the four countries. Results and impact With this project we aim to give an overview of the status of heart failure care and myocardial infarction care as well as potential differences in patient characteristics in European countries and highlight differences could attribute to medication uptake and mortality. We hope to create insight in the burden of HF based on real-world evidence. Other important impacts of the study include the establishment of an international co-operation on HF research, development of the BigData@Heart network and fostering a collaboration between academia and industry in heart failure and myocardial infarction research.
Collaborator Contribution The partners have contributed to the collaboration in the following aspects: 1. Assemble a unique cross-European dataset of electronic health records. 2. Create systems to develop and test the methodology for high-power identification, harmonisation, access and analysis of the assembled data. 3. Provide clinical input for disease definitions and health system characterisation. 4. Leverage the access to other unique databases. 5. Provide technical input to establish a scalable method to maximise impact and speed at which the results will be broadly implemented in other EU and non-EU countries.
Impact The project is multi-disciplinary, including the training of information science, data science, cardiology, and clinical epidemiology. Since February 2018, it has been granted a € 135.000 grant from the IMI BigData@Heart, UMCU.
Start Year 2017
 
Description Collaboration in the European BigData@Heart Consortium, a research consortium of the Innovative Medicines Initiative (IMI), a public-private initiative between the European Union and the pharmaceutical industry association, the European Federation of Pharmaceutical Industries and Associations (EFPIA). 
Organisation Galencia
Department Vifor Pharma UK
Country United Kingdom 
Sector Private 
PI Contribution Collaborated with researchers from the University Medical Center Utrecht, we aim to contribute to the research consortium with the investigation on the differences in the heart failure treatment and survival: a comparison between Sweden, United Kingdom, Netherlands and Spain using Linked Electronic Health Care Records. Heart failure (HF) remains a major public health issue, resulting in substantial morbidity, mortality and considerable health care costs, and myocardial infarction (MI) is one of the leading causes of heart failure (HF). MI and HF together impose a major burden on health care systems worldwide. Attributes of health care systems, such as incidence, length of stay, outcomes of hospital admissions, medication or guideline adherence could be associated with disease outcome. Though, studies that examine both health care and disease outcomes are lacking. Consequently, recognition is growing for comparative effectiveness research to improve quality and outcomes of health care. International comparisons of whole healthcare systems might yield important knowledge of distinct differences in HF care. The objective of our investigation is thus to 1) compare HF care between UK, Sweden, Spain and the Netherlands using comparable cohorts of HF patients during similar time periods, and, 2) to study how MI and HF interplay in the modern era of coronary care units, PCI technology and effective therapy in different health care systems to further harness learning opportunities. Method Population data In the UK, information about HF care would be obtained from CALIBER (CArdiovascular research using LInked Bespoke studies and Electronic Health Records). This registry links three sources of electronic health records in England: primary care records in practices contributing to the Clinical Practice Research Datalink (CPRD), secondary care hospital discharges in Hospital Episodes Statistics (HES) and the national death registration in the Office for National Statistics (ONS) registry. In Sweden, the Swedish Heart Failure Registry (SwedeHF) for long-term follow-up of HF management would be used. In the Netherlands, a nationwide HF registry is available through linkage of the Population Register, Hospital Discharge Register, and cause of death register. Additional linkage with Vektis (insurance company data) provides information about prescriptions of medication and use of care. Lastly, in Spain ABUCASIS, an electronic centralized clinical record system for primary and secondary ambulatory care in the Valencia Community would be used for the international comparison of HF care. The common denominator of all four registries is patients hospitalised for HF. Our study focuses on the follow-up of these patients, with a common follow-time between the registries from 2008 - 2014. Patients are followed until death, as defined in the national mortality registrations of the participant countries. In collaboration with the Hyve, a company that specialises in data management, our team harmonises the data from all registries to create a common model which can be applied to all, Definition of heart failure and myocardial infarction Patients included in the study are 30 years and older and have been diagnosed with HF through an ICD-10/ICD-9 code for HF (ICD-10: I11.0, I13.0, I13.2, I26.0, I50/ ICD-9: 402.01, 402.11, 402.91, 428, 398.91). For the post-MI HF studies, early-onset (in-hospital HF identified by a set of clinical parameters that define it) and late-onset HF post-MI HF (from ICD-10/ICD 9 codes for HF) are studied. Clinical outcomes The primary endpoint is the short and long-term all-cause mortality patterns as well as differences in temporal trends. Short-term mortality is defined as 30-day and 1-year mortality, whereas long-term mortality is defined as 5-year mortality. Statistical analyses Baseline patient characteristics are summarised as mean (SD) or median [IQR] for continuous variables and percentages for categorical variables. A Chi-square test is used to compare data for categorical variables, a t-test to compare means, and the Kruskal-Wallis for medians. To compare the crude and case-mix adjusted mortality across countries, we compare the 30-day, 1-year and 5-year mortality outcomes with Kaplan-Meier analysis. Cox proportional hazard model is used to estimate the case-mix adjusted mortality. Variables for case-mix adjustment are age, sex, year of admission, length of hospital admission, obesity, smoking, history of diabetes, hypertension. The mortality and association between HF/MI care on mortality are compared across the health care systems of the four countries. Results and impact With this project we aim to give an overview of the status of heart failure care and myocardial infarction care as well as potential differences in patient characteristics in European countries and highlight differences could attribute to medication uptake and mortality. We hope to create insight in the burden of HF based on real-world evidence. Other important impacts of the study include the establishment of an international co-operation on HF research, development of the BigData@Heart network and fostering a collaboration between academia and industry in heart failure and myocardial infarction research.
Collaborator Contribution The partners have contributed to the collaboration in the following aspects: 1. Assemble a unique cross-European dataset of electronic health records. 2. Create systems to develop and test the methodology for high-power identification, harmonisation, access and analysis of the assembled data. 3. Provide clinical input for disease definitions and health system characterisation. 4. Leverage the access to other unique databases. 5. Provide technical input to establish a scalable method to maximise impact and speed at which the results will be broadly implemented in other EU and non-EU countries.
Impact The project is multi-disciplinary, including the training of information science, data science, cardiology, and clinical epidemiology. Since February 2018, it has been granted a € 135.000 grant from the IMI BigData@Heart, UMCU.
Start Year 2017
 
Description Collaboration in the European BigData@Heart Consortium, a research consortium of the Innovative Medicines Initiative (IMI), a public-private initiative between the European Union and the pharmaceutical industry association, the European Federation of Pharmaceutical Industries and Associations (EFPIA). 
Organisation HYVE AG
PI Contribution Collaborated with researchers from the University Medical Center Utrecht, we aim to contribute to the research consortium with the investigation on the differences in the heart failure treatment and survival: a comparison between Sweden, United Kingdom, Netherlands and Spain using Linked Electronic Health Care Records. Heart failure (HF) remains a major public health issue, resulting in substantial morbidity, mortality and considerable health care costs, and myocardial infarction (MI) is one of the leading causes of heart failure (HF). MI and HF together impose a major burden on health care systems worldwide. Attributes of health care systems, such as incidence, length of stay, outcomes of hospital admissions, medication or guideline adherence could be associated with disease outcome. Though, studies that examine both health care and disease outcomes are lacking. Consequently, recognition is growing for comparative effectiveness research to improve quality and outcomes of health care. International comparisons of whole healthcare systems might yield important knowledge of distinct differences in HF care. The objective of our investigation is thus to 1) compare HF care between UK, Sweden, Spain and the Netherlands using comparable cohorts of HF patients during similar time periods, and, 2) to study how MI and HF interplay in the modern era of coronary care units, PCI technology and effective therapy in different health care systems to further harness learning opportunities. Method Population data In the UK, information about HF care would be obtained from CALIBER (CArdiovascular research using LInked Bespoke studies and Electronic Health Records). This registry links three sources of electronic health records in England: primary care records in practices contributing to the Clinical Practice Research Datalink (CPRD), secondary care hospital discharges in Hospital Episodes Statistics (HES) and the national death registration in the Office for National Statistics (ONS) registry. In Sweden, the Swedish Heart Failure Registry (SwedeHF) for long-term follow-up of HF management would be used. In the Netherlands, a nationwide HF registry is available through linkage of the Population Register, Hospital Discharge Register, and cause of death register. Additional linkage with Vektis (insurance company data) provides information about prescriptions of medication and use of care. Lastly, in Spain ABUCASIS, an electronic centralized clinical record system for primary and secondary ambulatory care in the Valencia Community would be used for the international comparison of HF care. The common denominator of all four registries is patients hospitalised for HF. Our study focuses on the follow-up of these patients, with a common follow-time between the registries from 2008 - 2014. Patients are followed until death, as defined in the national mortality registrations of the participant countries. In collaboration with the Hyve, a company that specialises in data management, our team harmonises the data from all registries to create a common model which can be applied to all, Definition of heart failure and myocardial infarction Patients included in the study are 30 years and older and have been diagnosed with HF through an ICD-10/ICD-9 code for HF (ICD-10: I11.0, I13.0, I13.2, I26.0, I50/ ICD-9: 402.01, 402.11, 402.91, 428, 398.91). For the post-MI HF studies, early-onset (in-hospital HF identified by a set of clinical parameters that define it) and late-onset HF post-MI HF (from ICD-10/ICD 9 codes for HF) are studied. Clinical outcomes The primary endpoint is the short and long-term all-cause mortality patterns as well as differences in temporal trends. Short-term mortality is defined as 30-day and 1-year mortality, whereas long-term mortality is defined as 5-year mortality. Statistical analyses Baseline patient characteristics are summarised as mean (SD) or median [IQR] for continuous variables and percentages for categorical variables. A Chi-square test is used to compare data for categorical variables, a t-test to compare means, and the Kruskal-Wallis for medians. To compare the crude and case-mix adjusted mortality across countries, we compare the 30-day, 1-year and 5-year mortality outcomes with Kaplan-Meier analysis. Cox proportional hazard model is used to estimate the case-mix adjusted mortality. Variables for case-mix adjustment are age, sex, year of admission, length of hospital admission, obesity, smoking, history of diabetes, hypertension. The mortality and association between HF/MI care on mortality are compared across the health care systems of the four countries. Results and impact With this project we aim to give an overview of the status of heart failure care and myocardial infarction care as well as potential differences in patient characteristics in European countries and highlight differences could attribute to medication uptake and mortality. We hope to create insight in the burden of HF based on real-world evidence. Other important impacts of the study include the establishment of an international co-operation on HF research, development of the BigData@Heart network and fostering a collaboration between academia and industry in heart failure and myocardial infarction research.
Collaborator Contribution The partners have contributed to the collaboration in the following aspects: 1. Assemble a unique cross-European dataset of electronic health records. 2. Create systems to develop and test the methodology for high-power identification, harmonisation, access and analysis of the assembled data. 3. Provide clinical input for disease definitions and health system characterisation. 4. Leverage the access to other unique databases. 5. Provide technical input to establish a scalable method to maximise impact and speed at which the results will be broadly implemented in other EU and non-EU countries.
Impact The project is multi-disciplinary, including the training of information science, data science, cardiology, and clinical epidemiology. Since February 2018, it has been granted a € 135.000 grant from the IMI BigData@Heart, UMCU.
Start Year 2017
 
Description Collaboration in the European BigData@Heart Consortium, a research consortium of the Innovative Medicines Initiative (IMI), a public-private initiative between the European Union and the pharmaceutical industry association, the European Federation of Pharmaceutical Industries and Associations (EFPIA). 
Organisation International Consortium for Health Outcomes Measurement
Country Unknown 
Sector Charity/Non Profit 
PI Contribution Collaborated with researchers from the University Medical Center Utrecht, we aim to contribute to the research consortium with the investigation on the differences in the heart failure treatment and survival: a comparison between Sweden, United Kingdom, Netherlands and Spain using Linked Electronic Health Care Records. Heart failure (HF) remains a major public health issue, resulting in substantial morbidity, mortality and considerable health care costs, and myocardial infarction (MI) is one of the leading causes of heart failure (HF). MI and HF together impose a major burden on health care systems worldwide. Attributes of health care systems, such as incidence, length of stay, outcomes of hospital admissions, medication or guideline adherence could be associated with disease outcome. Though, studies that examine both health care and disease outcomes are lacking. Consequently, recognition is growing for comparative effectiveness research to improve quality and outcomes of health care. International comparisons of whole healthcare systems might yield important knowledge of distinct differences in HF care. The objective of our investigation is thus to 1) compare HF care between UK, Sweden, Spain and the Netherlands using comparable cohorts of HF patients during similar time periods, and, 2) to study how MI and HF interplay in the modern era of coronary care units, PCI technology and effective therapy in different health care systems to further harness learning opportunities. Method Population data In the UK, information about HF care would be obtained from CALIBER (CArdiovascular research using LInked Bespoke studies and Electronic Health Records). This registry links three sources of electronic health records in England: primary care records in practices contributing to the Clinical Practice Research Datalink (CPRD), secondary care hospital discharges in Hospital Episodes Statistics (HES) and the national death registration in the Office for National Statistics (ONS) registry. In Sweden, the Swedish Heart Failure Registry (SwedeHF) for long-term follow-up of HF management would be used. In the Netherlands, a nationwide HF registry is available through linkage of the Population Register, Hospital Discharge Register, and cause of death register. Additional linkage with Vektis (insurance company data) provides information about prescriptions of medication and use of care. Lastly, in Spain ABUCASIS, an electronic centralized clinical record system for primary and secondary ambulatory care in the Valencia Community would be used for the international comparison of HF care. The common denominator of all four registries is patients hospitalised for HF. Our study focuses on the follow-up of these patients, with a common follow-time between the registries from 2008 - 2014. Patients are followed until death, as defined in the national mortality registrations of the participant countries. In collaboration with the Hyve, a company that specialises in data management, our team harmonises the data from all registries to create a common model which can be applied to all, Definition of heart failure and myocardial infarction Patients included in the study are 30 years and older and have been diagnosed with HF through an ICD-10/ICD-9 code for HF (ICD-10: I11.0, I13.0, I13.2, I26.0, I50/ ICD-9: 402.01, 402.11, 402.91, 428, 398.91). For the post-MI HF studies, early-onset (in-hospital HF identified by a set of clinical parameters that define it) and late-onset HF post-MI HF (from ICD-10/ICD 9 codes for HF) are studied. Clinical outcomes The primary endpoint is the short and long-term all-cause mortality patterns as well as differences in temporal trends. Short-term mortality is defined as 30-day and 1-year mortality, whereas long-term mortality is defined as 5-year mortality. Statistical analyses Baseline patient characteristics are summarised as mean (SD) or median [IQR] for continuous variables and percentages for categorical variables. A Chi-square test is used to compare data for categorical variables, a t-test to compare means, and the Kruskal-Wallis for medians. To compare the crude and case-mix adjusted mortality across countries, we compare the 30-day, 1-year and 5-year mortality outcomes with Kaplan-Meier analysis. Cox proportional hazard model is used to estimate the case-mix adjusted mortality. Variables for case-mix adjustment are age, sex, year of admission, length of hospital admission, obesity, smoking, history of diabetes, hypertension. The mortality and association between HF/MI care on mortality are compared across the health care systems of the four countries. Results and impact With this project we aim to give an overview of the status of heart failure care and myocardial infarction care as well as potential differences in patient characteristics in European countries and highlight differences could attribute to medication uptake and mortality. We hope to create insight in the burden of HF based on real-world evidence. Other important impacts of the study include the establishment of an international co-operation on HF research, development of the BigData@Heart network and fostering a collaboration between academia and industry in heart failure and myocardial infarction research.
Collaborator Contribution The partners have contributed to the collaboration in the following aspects: 1. Assemble a unique cross-European dataset of electronic health records. 2. Create systems to develop and test the methodology for high-power identification, harmonisation, access and analysis of the assembled data. 3. Provide clinical input for disease definitions and health system characterisation. 4. Leverage the access to other unique databases. 5. Provide technical input to establish a scalable method to maximise impact and speed at which the results will be broadly implemented in other EU and non-EU countries.
Impact The project is multi-disciplinary, including the training of information science, data science, cardiology, and clinical epidemiology. Since February 2018, it has been granted a € 135.000 grant from the IMI BigData@Heart, UMCU.
Start Year 2017
 
Description Collaboration in the European BigData@Heart Consortium, a research consortium of the Innovative Medicines Initiative (IMI), a public-private initiative between the European Union and the pharmaceutical industry association, the European Federation of Pharmaceutical Industries and Associations (EFPIA). 
Organisation Karolinska Institute
Country Sweden 
Sector Academic/University 
PI Contribution Collaborated with researchers from the University Medical Center Utrecht, we aim to contribute to the research consortium with the investigation on the differences in the heart failure treatment and survival: a comparison between Sweden, United Kingdom, Netherlands and Spain using Linked Electronic Health Care Records. Heart failure (HF) remains a major public health issue, resulting in substantial morbidity, mortality and considerable health care costs, and myocardial infarction (MI) is one of the leading causes of heart failure (HF). MI and HF together impose a major burden on health care systems worldwide. Attributes of health care systems, such as incidence, length of stay, outcomes of hospital admissions, medication or guideline adherence could be associated with disease outcome. Though, studies that examine both health care and disease outcomes are lacking. Consequently, recognition is growing for comparative effectiveness research to improve quality and outcomes of health care. International comparisons of whole healthcare systems might yield important knowledge of distinct differences in HF care. The objective of our investigation is thus to 1) compare HF care between UK, Sweden, Spain and the Netherlands using comparable cohorts of HF patients during similar time periods, and, 2) to study how MI and HF interplay in the modern era of coronary care units, PCI technology and effective therapy in different health care systems to further harness learning opportunities. Method Population data In the UK, information about HF care would be obtained from CALIBER (CArdiovascular research using LInked Bespoke studies and Electronic Health Records). This registry links three sources of electronic health records in England: primary care records in practices contributing to the Clinical Practice Research Datalink (CPRD), secondary care hospital discharges in Hospital Episodes Statistics (HES) and the national death registration in the Office for National Statistics (ONS) registry. In Sweden, the Swedish Heart Failure Registry (SwedeHF) for long-term follow-up of HF management would be used. In the Netherlands, a nationwide HF registry is available through linkage of the Population Register, Hospital Discharge Register, and cause of death register. Additional linkage with Vektis (insurance company data) provides information about prescriptions of medication and use of care. Lastly, in Spain ABUCASIS, an electronic centralized clinical record system for primary and secondary ambulatory care in the Valencia Community would be used for the international comparison of HF care. The common denominator of all four registries is patients hospitalised for HF. Our study focuses on the follow-up of these patients, with a common follow-time between the registries from 2008 - 2014. Patients are followed until death, as defined in the national mortality registrations of the participant countries. In collaboration with the Hyve, a company that specialises in data management, our team harmonises the data from all registries to create a common model which can be applied to all, Definition of heart failure and myocardial infarction Patients included in the study are 30 years and older and have been diagnosed with HF through an ICD-10/ICD-9 code for HF (ICD-10: I11.0, I13.0, I13.2, I26.0, I50/ ICD-9: 402.01, 402.11, 402.91, 428, 398.91). For the post-MI HF studies, early-onset (in-hospital HF identified by a set of clinical parameters that define it) and late-onset HF post-MI HF (from ICD-10/ICD 9 codes for HF) are studied. Clinical outcomes The primary endpoint is the short and long-term all-cause mortality patterns as well as differences in temporal trends. Short-term mortality is defined as 30-day and 1-year mortality, whereas long-term mortality is defined as 5-year mortality. Statistical analyses Baseline patient characteristics are summarised as mean (SD) or median [IQR] for continuous variables and percentages for categorical variables. A Chi-square test is used to compare data for categorical variables, a t-test to compare means, and the Kruskal-Wallis for medians. To compare the crude and case-mix adjusted mortality across countries, we compare the 30-day, 1-year and 5-year mortality outcomes with Kaplan-Meier analysis. Cox proportional hazard model is used to estimate the case-mix adjusted mortality. Variables for case-mix adjustment are age, sex, year of admission, length of hospital admission, obesity, smoking, history of diabetes, hypertension. The mortality and association between HF/MI care on mortality are compared across the health care systems of the four countries. Results and impact With this project we aim to give an overview of the status of heart failure care and myocardial infarction care as well as potential differences in patient characteristics in European countries and highlight differences could attribute to medication uptake and mortality. We hope to create insight in the burden of HF based on real-world evidence. Other important impacts of the study include the establishment of an international co-operation on HF research, development of the BigData@Heart network and fostering a collaboration between academia and industry in heart failure and myocardial infarction research.
Collaborator Contribution The partners have contributed to the collaboration in the following aspects: 1. Assemble a unique cross-European dataset of electronic health records. 2. Create systems to develop and test the methodology for high-power identification, harmonisation, access and analysis of the assembled data. 3. Provide clinical input for disease definitions and health system characterisation. 4. Leverage the access to other unique databases. 5. Provide technical input to establish a scalable method to maximise impact and speed at which the results will be broadly implemented in other EU and non-EU countries.
Impact The project is multi-disciplinary, including the training of information science, data science, cardiology, and clinical epidemiology. Since February 2018, it has been granted a € 135.000 grant from the IMI BigData@Heart, UMCU.
Start Year 2017
 
Description Collaboration in the European BigData@Heart Consortium, a research consortium of the Innovative Medicines Initiative (IMI), a public-private initiative between the European Union and the pharmaceutical industry association, the European Federation of Pharmaceutical Industries and Associations (EFPIA). 
Organisation Novartis
Country Global 
Sector Private 
PI Contribution Collaborated with researchers from the University Medical Center Utrecht, we aim to contribute to the research consortium with the investigation on the differences in the heart failure treatment and survival: a comparison between Sweden, United Kingdom, Netherlands and Spain using Linked Electronic Health Care Records. Heart failure (HF) remains a major public health issue, resulting in substantial morbidity, mortality and considerable health care costs, and myocardial infarction (MI) is one of the leading causes of heart failure (HF). MI and HF together impose a major burden on health care systems worldwide. Attributes of health care systems, such as incidence, length of stay, outcomes of hospital admissions, medication or guideline adherence could be associated with disease outcome. Though, studies that examine both health care and disease outcomes are lacking. Consequently, recognition is growing for comparative effectiveness research to improve quality and outcomes of health care. International comparisons of whole healthcare systems might yield important knowledge of distinct differences in HF care. The objective of our investigation is thus to 1) compare HF care between UK, Sweden, Spain and the Netherlands using comparable cohorts of HF patients during similar time periods, and, 2) to study how MI and HF interplay in the modern era of coronary care units, PCI technology and effective therapy in different health care systems to further harness learning opportunities. Method Population data In the UK, information about HF care would be obtained from CALIBER (CArdiovascular research using LInked Bespoke studies and Electronic Health Records). This registry links three sources of electronic health records in England: primary care records in practices contributing to the Clinical Practice Research Datalink (CPRD), secondary care hospital discharges in Hospital Episodes Statistics (HES) and the national death registration in the Office for National Statistics (ONS) registry. In Sweden, the Swedish Heart Failure Registry (SwedeHF) for long-term follow-up of HF management would be used. In the Netherlands, a nationwide HF registry is available through linkage of the Population Register, Hospital Discharge Register, and cause of death register. Additional linkage with Vektis (insurance company data) provides information about prescriptions of medication and use of care. Lastly, in Spain ABUCASIS, an electronic centralized clinical record system for primary and secondary ambulatory care in the Valencia Community would be used for the international comparison of HF care. The common denominator of all four registries is patients hospitalised for HF. Our study focuses on the follow-up of these patients, with a common follow-time between the registries from 2008 - 2014. Patients are followed until death, as defined in the national mortality registrations of the participant countries. In collaboration with the Hyve, a company that specialises in data management, our team harmonises the data from all registries to create a common model which can be applied to all, Definition of heart failure and myocardial infarction Patients included in the study are 30 years and older and have been diagnosed with HF through an ICD-10/ICD-9 code for HF (ICD-10: I11.0, I13.0, I13.2, I26.0, I50/ ICD-9: 402.01, 402.11, 402.91, 428, 398.91). For the post-MI HF studies, early-onset (in-hospital HF identified by a set of clinical parameters that define it) and late-onset HF post-MI HF (from ICD-10/ICD 9 codes for HF) are studied. Clinical outcomes The primary endpoint is the short and long-term all-cause mortality patterns as well as differences in temporal trends. Short-term mortality is defined as 30-day and 1-year mortality, whereas long-term mortality is defined as 5-year mortality. Statistical analyses Baseline patient characteristics are summarised as mean (SD) or median [IQR] for continuous variables and percentages for categorical variables. A Chi-square test is used to compare data for categorical variables, a t-test to compare means, and the Kruskal-Wallis for medians. To compare the crude and case-mix adjusted mortality across countries, we compare the 30-day, 1-year and 5-year mortality outcomes with Kaplan-Meier analysis. Cox proportional hazard model is used to estimate the case-mix adjusted mortality. Variables for case-mix adjustment are age, sex, year of admission, length of hospital admission, obesity, smoking, history of diabetes, hypertension. The mortality and association between HF/MI care on mortality are compared across the health care systems of the four countries. Results and impact With this project we aim to give an overview of the status of heart failure care and myocardial infarction care as well as potential differences in patient characteristics in European countries and highlight differences could attribute to medication uptake and mortality. We hope to create insight in the burden of HF based on real-world evidence. Other important impacts of the study include the establishment of an international co-operation on HF research, development of the BigData@Heart network and fostering a collaboration between academia and industry in heart failure and myocardial infarction research.
Collaborator Contribution The partners have contributed to the collaboration in the following aspects: 1. Assemble a unique cross-European dataset of electronic health records. 2. Create systems to develop and test the methodology for high-power identification, harmonisation, access and analysis of the assembled data. 3. Provide clinical input for disease definitions and health system characterisation. 4. Leverage the access to other unique databases. 5. Provide technical input to establish a scalable method to maximise impact and speed at which the results will be broadly implemented in other EU and non-EU countries.
Impact The project is multi-disciplinary, including the training of information science, data science, cardiology, and clinical epidemiology. Since February 2018, it has been granted a € 135.000 grant from the IMI BigData@Heart, UMCU.
Start Year 2017
 
Description Collaboration in the European BigData@Heart Consortium, a research consortium of the Innovative Medicines Initiative (IMI), a public-private initiative between the European Union and the pharmaceutical industry association, the European Federation of Pharmaceutical Industries and Associations (EFPIA). 
Organisation Servier Laboratories
Country France 
Sector Private 
PI Contribution Collaborated with researchers from the University Medical Center Utrecht, we aim to contribute to the research consortium with the investigation on the differences in the heart failure treatment and survival: a comparison between Sweden, United Kingdom, Netherlands and Spain using Linked Electronic Health Care Records. Heart failure (HF) remains a major public health issue, resulting in substantial morbidity, mortality and considerable health care costs, and myocardial infarction (MI) is one of the leading causes of heart failure (HF). MI and HF together impose a major burden on health care systems worldwide. Attributes of health care systems, such as incidence, length of stay, outcomes of hospital admissions, medication or guideline adherence could be associated with disease outcome. Though, studies that examine both health care and disease outcomes are lacking. Consequently, recognition is growing for comparative effectiveness research to improve quality and outcomes of health care. International comparisons of whole healthcare systems might yield important knowledge of distinct differences in HF care. The objective of our investigation is thus to 1) compare HF care between UK, Sweden, Spain and the Netherlands using comparable cohorts of HF patients during similar time periods, and, 2) to study how MI and HF interplay in the modern era of coronary care units, PCI technology and effective therapy in different health care systems to further harness learning opportunities. Method Population data In the UK, information about HF care would be obtained from CALIBER (CArdiovascular research using LInked Bespoke studies and Electronic Health Records). This registry links three sources of electronic health records in England: primary care records in practices contributing to the Clinical Practice Research Datalink (CPRD), secondary care hospital discharges in Hospital Episodes Statistics (HES) and the national death registration in the Office for National Statistics (ONS) registry. In Sweden, the Swedish Heart Failure Registry (SwedeHF) for long-term follow-up of HF management would be used. In the Netherlands, a nationwide HF registry is available through linkage of the Population Register, Hospital Discharge Register, and cause of death register. Additional linkage with Vektis (insurance company data) provides information about prescriptions of medication and use of care. Lastly, in Spain ABUCASIS, an electronic centralized clinical record system for primary and secondary ambulatory care in the Valencia Community would be used for the international comparison of HF care. The common denominator of all four registries is patients hospitalised for HF. Our study focuses on the follow-up of these patients, with a common follow-time between the registries from 2008 - 2014. Patients are followed until death, as defined in the national mortality registrations of the participant countries. In collaboration with the Hyve, a company that specialises in data management, our team harmonises the data from all registries to create a common model which can be applied to all, Definition of heart failure and myocardial infarction Patients included in the study are 30 years and older and have been diagnosed with HF through an ICD-10/ICD-9 code for HF (ICD-10: I11.0, I13.0, I13.2, I26.0, I50/ ICD-9: 402.01, 402.11, 402.91, 428, 398.91). For the post-MI HF studies, early-onset (in-hospital HF identified by a set of clinical parameters that define it) and late-onset HF post-MI HF (from ICD-10/ICD 9 codes for HF) are studied. Clinical outcomes The primary endpoint is the short and long-term all-cause mortality patterns as well as differences in temporal trends. Short-term mortality is defined as 30-day and 1-year mortality, whereas long-term mortality is defined as 5-year mortality. Statistical analyses Baseline patient characteristics are summarised as mean (SD) or median [IQR] for continuous variables and percentages for categorical variables. A Chi-square test is used to compare data for categorical variables, a t-test to compare means, and the Kruskal-Wallis for medians. To compare the crude and case-mix adjusted mortality across countries, we compare the 30-day, 1-year and 5-year mortality outcomes with Kaplan-Meier analysis. Cox proportional hazard model is used to estimate the case-mix adjusted mortality. Variables for case-mix adjustment are age, sex, year of admission, length of hospital admission, obesity, smoking, history of diabetes, hypertension. The mortality and association between HF/MI care on mortality are compared across the health care systems of the four countries. Results and impact With this project we aim to give an overview of the status of heart failure care and myocardial infarction care as well as potential differences in patient characteristics in European countries and highlight differences could attribute to medication uptake and mortality. We hope to create insight in the burden of HF based on real-world evidence. Other important impacts of the study include the establishment of an international co-operation on HF research, development of the BigData@Heart network and fostering a collaboration between academia and industry in heart failure and myocardial infarction research.
Collaborator Contribution The partners have contributed to the collaboration in the following aspects: 1. Assemble a unique cross-European dataset of electronic health records. 2. Create systems to develop and test the methodology for high-power identification, harmonisation, access and analysis of the assembled data. 3. Provide clinical input for disease definitions and health system characterisation. 4. Leverage the access to other unique databases. 5. Provide technical input to establish a scalable method to maximise impact and speed at which the results will be broadly implemented in other EU and non-EU countries.
Impact The project is multi-disciplinary, including the training of information science, data science, cardiology, and clinical epidemiology. Since February 2018, it has been granted a € 135.000 grant from the IMI BigData@Heart, UMCU.
Start Year 2017
 
Description Collaboration in the European BigData@Heart Consortium, a research consortium of the Innovative Medicines Initiative (IMI), a public-private initiative between the European Union and the pharmaceutical industry association, the European Federation of Pharmaceutical Industries and Associations (EFPIA). 
Organisation SomaLogic
Country United States 
Sector Private 
PI Contribution Collaborated with researchers from the University Medical Center Utrecht, we aim to contribute to the research consortium with the investigation on the differences in the heart failure treatment and survival: a comparison between Sweden, United Kingdom, Netherlands and Spain using Linked Electronic Health Care Records. Heart failure (HF) remains a major public health issue, resulting in substantial morbidity, mortality and considerable health care costs, and myocardial infarction (MI) is one of the leading causes of heart failure (HF). MI and HF together impose a major burden on health care systems worldwide. Attributes of health care systems, such as incidence, length of stay, outcomes of hospital admissions, medication or guideline adherence could be associated with disease outcome. Though, studies that examine both health care and disease outcomes are lacking. Consequently, recognition is growing for comparative effectiveness research to improve quality and outcomes of health care. International comparisons of whole healthcare systems might yield important knowledge of distinct differences in HF care. The objective of our investigation is thus to 1) compare HF care between UK, Sweden, Spain and the Netherlands using comparable cohorts of HF patients during similar time periods, and, 2) to study how MI and HF interplay in the modern era of coronary care units, PCI technology and effective therapy in different health care systems to further harness learning opportunities. Method Population data In the UK, information about HF care would be obtained from CALIBER (CArdiovascular research using LInked Bespoke studies and Electronic Health Records). This registry links three sources of electronic health records in England: primary care records in practices contributing to the Clinical Practice Research Datalink (CPRD), secondary care hospital discharges in Hospital Episodes Statistics (HES) and the national death registration in the Office for National Statistics (ONS) registry. In Sweden, the Swedish Heart Failure Registry (SwedeHF) for long-term follow-up of HF management would be used. In the Netherlands, a nationwide HF registry is available through linkage of the Population Register, Hospital Discharge Register, and cause of death register. Additional linkage with Vektis (insurance company data) provides information about prescriptions of medication and use of care. Lastly, in Spain ABUCASIS, an electronic centralized clinical record system for primary and secondary ambulatory care in the Valencia Community would be used for the international comparison of HF care. The common denominator of all four registries is patients hospitalised for HF. Our study focuses on the follow-up of these patients, with a common follow-time between the registries from 2008 - 2014. Patients are followed until death, as defined in the national mortality registrations of the participant countries. In collaboration with the Hyve, a company that specialises in data management, our team harmonises the data from all registries to create a common model which can be applied to all, Definition of heart failure and myocardial infarction Patients included in the study are 30 years and older and have been diagnosed with HF through an ICD-10/ICD-9 code for HF (ICD-10: I11.0, I13.0, I13.2, I26.0, I50/ ICD-9: 402.01, 402.11, 402.91, 428, 398.91). For the post-MI HF studies, early-onset (in-hospital HF identified by a set of clinical parameters that define it) and late-onset HF post-MI HF (from ICD-10/ICD 9 codes for HF) are studied. Clinical outcomes The primary endpoint is the short and long-term all-cause mortality patterns as well as differences in temporal trends. Short-term mortality is defined as 30-day and 1-year mortality, whereas long-term mortality is defined as 5-year mortality. Statistical analyses Baseline patient characteristics are summarised as mean (SD) or median [IQR] for continuous variables and percentages for categorical variables. A Chi-square test is used to compare data for categorical variables, a t-test to compare means, and the Kruskal-Wallis for medians. To compare the crude and case-mix adjusted mortality across countries, we compare the 30-day, 1-year and 5-year mortality outcomes with Kaplan-Meier analysis. Cox proportional hazard model is used to estimate the case-mix adjusted mortality. Variables for case-mix adjustment are age, sex, year of admission, length of hospital admission, obesity, smoking, history of diabetes, hypertension. The mortality and association between HF/MI care on mortality are compared across the health care systems of the four countries. Results and impact With this project we aim to give an overview of the status of heart failure care and myocardial infarction care as well as potential differences in patient characteristics in European countries and highlight differences could attribute to medication uptake and mortality. We hope to create insight in the burden of HF based on real-world evidence. Other important impacts of the study include the establishment of an international co-operation on HF research, development of the BigData@Heart network and fostering a collaboration between academia and industry in heart failure and myocardial infarction research.
Collaborator Contribution The partners have contributed to the collaboration in the following aspects: 1. Assemble a unique cross-European dataset of electronic health records. 2. Create systems to develop and test the methodology for high-power identification, harmonisation, access and analysis of the assembled data. 3. Provide clinical input for disease definitions and health system characterisation. 4. Leverage the access to other unique databases. 5. Provide technical input to establish a scalable method to maximise impact and speed at which the results will be broadly implemented in other EU and non-EU countries.
Impact The project is multi-disciplinary, including the training of information science, data science, cardiology, and clinical epidemiology. Since February 2018, it has been granted a € 135.000 grant from the IMI BigData@Heart, UMCU.
Start Year 2017
 
Description Collaboration in the European BigData@Heart Consortium, a research consortium of the Innovative Medicines Initiative (IMI), a public-private initiative between the European Union and the pharmaceutical industry association, the European Federation of Pharmaceutical Industries and Associations (EFPIA). 
Organisation University College London
Country United Kingdom 
Sector Academic/University 
PI Contribution Collaborated with researchers from the University Medical Center Utrecht, we aim to contribute to the research consortium with the investigation on the differences in the heart failure treatment and survival: a comparison between Sweden, United Kingdom, Netherlands and Spain using Linked Electronic Health Care Records. Heart failure (HF) remains a major public health issue, resulting in substantial morbidity, mortality and considerable health care costs, and myocardial infarction (MI) is one of the leading causes of heart failure (HF). MI and HF together impose a major burden on health care systems worldwide. Attributes of health care systems, such as incidence, length of stay, outcomes of hospital admissions, medication or guideline adherence could be associated with disease outcome. Though, studies that examine both health care and disease outcomes are lacking. Consequently, recognition is growing for comparative effectiveness research to improve quality and outcomes of health care. International comparisons of whole healthcare systems might yield important knowledge of distinct differences in HF care. The objective of our investigation is thus to 1) compare HF care between UK, Sweden, Spain and the Netherlands using comparable cohorts of HF patients during similar time periods, and, 2) to study how MI and HF interplay in the modern era of coronary care units, PCI technology and effective therapy in different health care systems to further harness learning opportunities. Method Population data In the UK, information about HF care would be obtained from CALIBER (CArdiovascular research using LInked Bespoke studies and Electronic Health Records). This registry links three sources of electronic health records in England: primary care records in practices contributing to the Clinical Practice Research Datalink (CPRD), secondary care hospital discharges in Hospital Episodes Statistics (HES) and the national death registration in the Office for National Statistics (ONS) registry. In Sweden, the Swedish Heart Failure Registry (SwedeHF) for long-term follow-up of HF management would be used. In the Netherlands, a nationwide HF registry is available through linkage of the Population Register, Hospital Discharge Register, and cause of death register. Additional linkage with Vektis (insurance company data) provides information about prescriptions of medication and use of care. Lastly, in Spain ABUCASIS, an electronic centralized clinical record system for primary and secondary ambulatory care in the Valencia Community would be used for the international comparison of HF care. The common denominator of all four registries is patients hospitalised for HF. Our study focuses on the follow-up of these patients, with a common follow-time between the registries from 2008 - 2014. Patients are followed until death, as defined in the national mortality registrations of the participant countries. In collaboration with the Hyve, a company that specialises in data management, our team harmonises the data from all registries to create a common model which can be applied to all, Definition of heart failure and myocardial infarction Patients included in the study are 30 years and older and have been diagnosed with HF through an ICD-10/ICD-9 code for HF (ICD-10: I11.0, I13.0, I13.2, I26.0, I50/ ICD-9: 402.01, 402.11, 402.91, 428, 398.91). For the post-MI HF studies, early-onset (in-hospital HF identified by a set of clinical parameters that define it) and late-onset HF post-MI HF (from ICD-10/ICD 9 codes for HF) are studied. Clinical outcomes The primary endpoint is the short and long-term all-cause mortality patterns as well as differences in temporal trends. Short-term mortality is defined as 30-day and 1-year mortality, whereas long-term mortality is defined as 5-year mortality. Statistical analyses Baseline patient characteristics are summarised as mean (SD) or median [IQR] for continuous variables and percentages for categorical variables. A Chi-square test is used to compare data for categorical variables, a t-test to compare means, and the Kruskal-Wallis for medians. To compare the crude and case-mix adjusted mortality across countries, we compare the 30-day, 1-year and 5-year mortality outcomes with Kaplan-Meier analysis. Cox proportional hazard model is used to estimate the case-mix adjusted mortality. Variables for case-mix adjustment are age, sex, year of admission, length of hospital admission, obesity, smoking, history of diabetes, hypertension. The mortality and association between HF/MI care on mortality are compared across the health care systems of the four countries. Results and impact With this project we aim to give an overview of the status of heart failure care and myocardial infarction care as well as potential differences in patient characteristics in European countries and highlight differences could attribute to medication uptake and mortality. We hope to create insight in the burden of HF based on real-world evidence. Other important impacts of the study include the establishment of an international co-operation on HF research, development of the BigData@Heart network and fostering a collaboration between academia and industry in heart failure and myocardial infarction research.
Collaborator Contribution The partners have contributed to the collaboration in the following aspects: 1. Assemble a unique cross-European dataset of electronic health records. 2. Create systems to develop and test the methodology for high-power identification, harmonisation, access and analysis of the assembled data. 3. Provide clinical input for disease definitions and health system characterisation. 4. Leverage the access to other unique databases. 5. Provide technical input to establish a scalable method to maximise impact and speed at which the results will be broadly implemented in other EU and non-EU countries.
Impact The project is multi-disciplinary, including the training of information science, data science, cardiology, and clinical epidemiology. Since February 2018, it has been granted a € 135.000 grant from the IMI BigData@Heart, UMCU.
Start Year 2017
 
Description Collaboration in the European BigData@Heart Consortium, a research consortium of the Innovative Medicines Initiative (IMI), a public-private initiative between the European Union and the pharmaceutical industry association, the European Federation of Pharmaceutical Industries and Associations (EFPIA). 
Organisation University Medical Center Hamburg-Eppendorf
Country Germany 
Sector Hospitals 
PI Contribution Collaborated with researchers from the University Medical Center Utrecht, we aim to contribute to the research consortium with the investigation on the differences in the heart failure treatment and survival: a comparison between Sweden, United Kingdom, Netherlands and Spain using Linked Electronic Health Care Records. Heart failure (HF) remains a major public health issue, resulting in substantial morbidity, mortality and considerable health care costs, and myocardial infarction (MI) is one of the leading causes of heart failure (HF). MI and HF together impose a major burden on health care systems worldwide. Attributes of health care systems, such as incidence, length of stay, outcomes of hospital admissions, medication or guideline adherence could be associated with disease outcome. Though, studies that examine both health care and disease outcomes are lacking. Consequently, recognition is growing for comparative effectiveness research to improve quality and outcomes of health care. International comparisons of whole healthcare systems might yield important knowledge of distinct differences in HF care. The objective of our investigation is thus to 1) compare HF care between UK, Sweden, Spain and the Netherlands using comparable cohorts of HF patients during similar time periods, and, 2) to study how MI and HF interplay in the modern era of coronary care units, PCI technology and effective therapy in different health care systems to further harness learning opportunities. Method Population data In the UK, information about HF care would be obtained from CALIBER (CArdiovascular research using LInked Bespoke studies and Electronic Health Records). This registry links three sources of electronic health records in England: primary care records in practices contributing to the Clinical Practice Research Datalink (CPRD), secondary care hospital discharges in Hospital Episodes Statistics (HES) and the national death registration in the Office for National Statistics (ONS) registry. In Sweden, the Swedish Heart Failure Registry (SwedeHF) for long-term follow-up of HF management would be used. In the Netherlands, a nationwide HF registry is available through linkage of the Population Register, Hospital Discharge Register, and cause of death register. Additional linkage with Vektis (insurance company data) provides information about prescriptions of medication and use of care. Lastly, in Spain ABUCASIS, an electronic centralized clinical record system for primary and secondary ambulatory care in the Valencia Community would be used for the international comparison of HF care. The common denominator of all four registries is patients hospitalised for HF. Our study focuses on the follow-up of these patients, with a common follow-time between the registries from 2008 - 2014. Patients are followed until death, as defined in the national mortality registrations of the participant countries. In collaboration with the Hyve, a company that specialises in data management, our team harmonises the data from all registries to create a common model which can be applied to all, Definition of heart failure and myocardial infarction Patients included in the study are 30 years and older and have been diagnosed with HF through an ICD-10/ICD-9 code for HF (ICD-10: I11.0, I13.0, I13.2, I26.0, I50/ ICD-9: 402.01, 402.11, 402.91, 428, 398.91). For the post-MI HF studies, early-onset (in-hospital HF identified by a set of clinical parameters that define it) and late-onset HF post-MI HF (from ICD-10/ICD 9 codes for HF) are studied. Clinical outcomes The primary endpoint is the short and long-term all-cause mortality patterns as well as differences in temporal trends. Short-term mortality is defined as 30-day and 1-year mortality, whereas long-term mortality is defined as 5-year mortality. Statistical analyses Baseline patient characteristics are summarised as mean (SD) or median [IQR] for continuous variables and percentages for categorical variables. A Chi-square test is used to compare data for categorical variables, a t-test to compare means, and the Kruskal-Wallis for medians. To compare the crude and case-mix adjusted mortality across countries, we compare the 30-day, 1-year and 5-year mortality outcomes with Kaplan-Meier analysis. Cox proportional hazard model is used to estimate the case-mix adjusted mortality. Variables for case-mix adjustment are age, sex, year of admission, length of hospital admission, obesity, smoking, history of diabetes, hypertension. The mortality and association between HF/MI care on mortality are compared across the health care systems of the four countries. Results and impact With this project we aim to give an overview of the status of heart failure care and myocardial infarction care as well as potential differences in patient characteristics in European countries and highlight differences could attribute to medication uptake and mortality. We hope to create insight in the burden of HF based on real-world evidence. Other important impacts of the study include the establishment of an international co-operation on HF research, development of the BigData@Heart network and fostering a collaboration between academia and industry in heart failure and myocardial infarction research.
Collaborator Contribution The partners have contributed to the collaboration in the following aspects: 1. Assemble a unique cross-European dataset of electronic health records. 2. Create systems to develop and test the methodology for high-power identification, harmonisation, access and analysis of the assembled data. 3. Provide clinical input for disease definitions and health system characterisation. 4. Leverage the access to other unique databases. 5. Provide technical input to establish a scalable method to maximise impact and speed at which the results will be broadly implemented in other EU and non-EU countries.
Impact The project is multi-disciplinary, including the training of information science, data science, cardiology, and clinical epidemiology. Since February 2018, it has been granted a € 135.000 grant from the IMI BigData@Heart, UMCU.
Start Year 2017
 
Description Collaboration in the European BigData@Heart Consortium, a research consortium of the Innovative Medicines Initiative (IMI), a public-private initiative between the European Union and the pharmaceutical industry association, the European Federation of Pharmaceutical Industries and Associations (EFPIA). 
Organisation University Medical Center Utrecht (UMC)
Country Netherlands 
Sector Academic/University 
PI Contribution Collaborated with researchers from the University Medical Center Utrecht, we aim to contribute to the research consortium with the investigation on the differences in the heart failure treatment and survival: a comparison between Sweden, United Kingdom, Netherlands and Spain using Linked Electronic Health Care Records. Heart failure (HF) remains a major public health issue, resulting in substantial morbidity, mortality and considerable health care costs, and myocardial infarction (MI) is one of the leading causes of heart failure (HF). MI and HF together impose a major burden on health care systems worldwide. Attributes of health care systems, such as incidence, length of stay, outcomes of hospital admissions, medication or guideline adherence could be associated with disease outcome. Though, studies that examine both health care and disease outcomes are lacking. Consequently, recognition is growing for comparative effectiveness research to improve quality and outcomes of health care. International comparisons of whole healthcare systems might yield important knowledge of distinct differences in HF care. The objective of our investigation is thus to 1) compare HF care between UK, Sweden, Spain and the Netherlands using comparable cohorts of HF patients during similar time periods, and, 2) to study how MI and HF interplay in the modern era of coronary care units, PCI technology and effective therapy in different health care systems to further harness learning opportunities. Method Population data In the UK, information about HF care would be obtained from CALIBER (CArdiovascular research using LInked Bespoke studies and Electronic Health Records). This registry links three sources of electronic health records in England: primary care records in practices contributing to the Clinical Practice Research Datalink (CPRD), secondary care hospital discharges in Hospital Episodes Statistics (HES) and the national death registration in the Office for National Statistics (ONS) registry. In Sweden, the Swedish Heart Failure Registry (SwedeHF) for long-term follow-up of HF management would be used. In the Netherlands, a nationwide HF registry is available through linkage of the Population Register, Hospital Discharge Register, and cause of death register. Additional linkage with Vektis (insurance company data) provides information about prescriptions of medication and use of care. Lastly, in Spain ABUCASIS, an electronic centralized clinical record system for primary and secondary ambulatory care in the Valencia Community would be used for the international comparison of HF care. The common denominator of all four registries is patients hospitalised for HF. Our study focuses on the follow-up of these patients, with a common follow-time between the registries from 2008 - 2014. Patients are followed until death, as defined in the national mortality registrations of the participant countries. In collaboration with the Hyve, a company that specialises in data management, our team harmonises the data from all registries to create a common model which can be applied to all, Definition of heart failure and myocardial infarction Patients included in the study are 30 years and older and have been diagnosed with HF through an ICD-10/ICD-9 code for HF (ICD-10: I11.0, I13.0, I13.2, I26.0, I50/ ICD-9: 402.01, 402.11, 402.91, 428, 398.91). For the post-MI HF studies, early-onset (in-hospital HF identified by a set of clinical parameters that define it) and late-onset HF post-MI HF (from ICD-10/ICD 9 codes for HF) are studied. Clinical outcomes The primary endpoint is the short and long-term all-cause mortality patterns as well as differences in temporal trends. Short-term mortality is defined as 30-day and 1-year mortality, whereas long-term mortality is defined as 5-year mortality. Statistical analyses Baseline patient characteristics are summarised as mean (SD) or median [IQR] for continuous variables and percentages for categorical variables. A Chi-square test is used to compare data for categorical variables, a t-test to compare means, and the Kruskal-Wallis for medians. To compare the crude and case-mix adjusted mortality across countries, we compare the 30-day, 1-year and 5-year mortality outcomes with Kaplan-Meier analysis. Cox proportional hazard model is used to estimate the case-mix adjusted mortality. Variables for case-mix adjustment are age, sex, year of admission, length of hospital admission, obesity, smoking, history of diabetes, hypertension. The mortality and association between HF/MI care on mortality are compared across the health care systems of the four countries. Results and impact With this project we aim to give an overview of the status of heart failure care and myocardial infarction care as well as potential differences in patient characteristics in European countries and highlight differences could attribute to medication uptake and mortality. We hope to create insight in the burden of HF based on real-world evidence. Other important impacts of the study include the establishment of an international co-operation on HF research, development of the BigData@Heart network and fostering a collaboration between academia and industry in heart failure and myocardial infarction research.
Collaborator Contribution The partners have contributed to the collaboration in the following aspects: 1. Assemble a unique cross-European dataset of electronic health records. 2. Create systems to develop and test the methodology for high-power identification, harmonisation, access and analysis of the assembled data. 3. Provide clinical input for disease definitions and health system characterisation. 4. Leverage the access to other unique databases. 5. Provide technical input to establish a scalable method to maximise impact and speed at which the results will be broadly implemented in other EU and non-EU countries.
Impact The project is multi-disciplinary, including the training of information science, data science, cardiology, and clinical epidemiology. Since February 2018, it has been granted a € 135.000 grant from the IMI BigData@Heart, UMCU.
Start Year 2017
 
Description Collaboration in the European BigData@Heart Consortium, a research consortium of the Innovative Medicines Initiative (IMI), a public-private initiative between the European Union and the pharmaceutical industry association, the European Federation of Pharmaceutical Industries and Associations (EFPIA). 
Organisation University of Birmingham
Country United Kingdom 
Sector Academic/University 
PI Contribution Collaborated with researchers from the University Medical Center Utrecht, we aim to contribute to the research consortium with the investigation on the differences in the heart failure treatment and survival: a comparison between Sweden, United Kingdom, Netherlands and Spain using Linked Electronic Health Care Records. Heart failure (HF) remains a major public health issue, resulting in substantial morbidity, mortality and considerable health care costs, and myocardial infarction (MI) is one of the leading causes of heart failure (HF). MI and HF together impose a major burden on health care systems worldwide. Attributes of health care systems, such as incidence, length of stay, outcomes of hospital admissions, medication or guideline adherence could be associated with disease outcome. Though, studies that examine both health care and disease outcomes are lacking. Consequently, recognition is growing for comparative effectiveness research to improve quality and outcomes of health care. International comparisons of whole healthcare systems might yield important knowledge of distinct differences in HF care. The objective of our investigation is thus to 1) compare HF care between UK, Sweden, Spain and the Netherlands using comparable cohorts of HF patients during similar time periods, and, 2) to study how MI and HF interplay in the modern era of coronary care units, PCI technology and effective therapy in different health care systems to further harness learning opportunities. Method Population data In the UK, information about HF care would be obtained from CALIBER (CArdiovascular research using LInked Bespoke studies and Electronic Health Records). This registry links three sources of electronic health records in England: primary care records in practices contributing to the Clinical Practice Research Datalink (CPRD), secondary care hospital discharges in Hospital Episodes Statistics (HES) and the national death registration in the Office for National Statistics (ONS) registry. In Sweden, the Swedish Heart Failure Registry (SwedeHF) for long-term follow-up of HF management would be used. In the Netherlands, a nationwide HF registry is available through linkage of the Population Register, Hospital Discharge Register, and cause of death register. Additional linkage with Vektis (insurance company data) provides information about prescriptions of medication and use of care. Lastly, in Spain ABUCASIS, an electronic centralized clinical record system for primary and secondary ambulatory care in the Valencia Community would be used for the international comparison of HF care. The common denominator of all four registries is patients hospitalised for HF. Our study focuses on the follow-up of these patients, with a common follow-time between the registries from 2008 - 2014. Patients are followed until death, as defined in the national mortality registrations of the participant countries. In collaboration with the Hyve, a company that specialises in data management, our team harmonises the data from all registries to create a common model which can be applied to all, Definition of heart failure and myocardial infarction Patients included in the study are 30 years and older and have been diagnosed with HF through an ICD-10/ICD-9 code for HF (ICD-10: I11.0, I13.0, I13.2, I26.0, I50/ ICD-9: 402.01, 402.11, 402.91, 428, 398.91). For the post-MI HF studies, early-onset (in-hospital HF identified by a set of clinical parameters that define it) and late-onset HF post-MI HF (from ICD-10/ICD 9 codes for HF) are studied. Clinical outcomes The primary endpoint is the short and long-term all-cause mortality patterns as well as differences in temporal trends. Short-term mortality is defined as 30-day and 1-year mortality, whereas long-term mortality is defined as 5-year mortality. Statistical analyses Baseline patient characteristics are summarised as mean (SD) or median [IQR] for continuous variables and percentages for categorical variables. A Chi-square test is used to compare data for categorical variables, a t-test to compare means, and the Kruskal-Wallis for medians. To compare the crude and case-mix adjusted mortality across countries, we compare the 30-day, 1-year and 5-year mortality outcomes with Kaplan-Meier analysis. Cox proportional hazard model is used to estimate the case-mix adjusted mortality. Variables for case-mix adjustment are age, sex, year of admission, length of hospital admission, obesity, smoking, history of diabetes, hypertension. The mortality and association between HF/MI care on mortality are compared across the health care systems of the four countries. Results and impact With this project we aim to give an overview of the status of heart failure care and myocardial infarction care as well as potential differences in patient characteristics in European countries and highlight differences could attribute to medication uptake and mortality. We hope to create insight in the burden of HF based on real-world evidence. Other important impacts of the study include the establishment of an international co-operation on HF research, development of the BigData@Heart network and fostering a collaboration between academia and industry in heart failure and myocardial infarction research.
Collaborator Contribution The partners have contributed to the collaboration in the following aspects: 1. Assemble a unique cross-European dataset of electronic health records. 2. Create systems to develop and test the methodology for high-power identification, harmonisation, access and analysis of the assembled data. 3. Provide clinical input for disease definitions and health system characterisation. 4. Leverage the access to other unique databases. 5. Provide technical input to establish a scalable method to maximise impact and speed at which the results will be broadly implemented in other EU and non-EU countries.
Impact The project is multi-disciplinary, including the training of information science, data science, cardiology, and clinical epidemiology. Since February 2018, it has been granted a € 135.000 grant from the IMI BigData@Heart, UMCU.
Start Year 2017
 
Description Collaboration in the European BigData@Heart Consortium, a research consortium of the Innovative Medicines Initiative (IMI), a public-private initiative between the European Union and the pharmaceutical industry association, the European Federation of Pharmaceutical Industries and Associations (EFPIA). 
Organisation University of Cambridge
Country United Kingdom 
Sector Academic/University 
PI Contribution Collaborated with researchers from the University Medical Center Utrecht, we aim to contribute to the research consortium with the investigation on the differences in the heart failure treatment and survival: a comparison between Sweden, United Kingdom, Netherlands and Spain using Linked Electronic Health Care Records. Heart failure (HF) remains a major public health issue, resulting in substantial morbidity, mortality and considerable health care costs, and myocardial infarction (MI) is one of the leading causes of heart failure (HF). MI and HF together impose a major burden on health care systems worldwide. Attributes of health care systems, such as incidence, length of stay, outcomes of hospital admissions, medication or guideline adherence could be associated with disease outcome. Though, studies that examine both health care and disease outcomes are lacking. Consequently, recognition is growing for comparative effectiveness research to improve quality and outcomes of health care. International comparisons of whole healthcare systems might yield important knowledge of distinct differences in HF care. The objective of our investigation is thus to 1) compare HF care between UK, Sweden, Spain and the Netherlands using comparable cohorts of HF patients during similar time periods, and, 2) to study how MI and HF interplay in the modern era of coronary care units, PCI technology and effective therapy in different health care systems to further harness learning opportunities. Method Population data In the UK, information about HF care would be obtained from CALIBER (CArdiovascular research using LInked Bespoke studies and Electronic Health Records). This registry links three sources of electronic health records in England: primary care records in practices contributing to the Clinical Practice Research Datalink (CPRD), secondary care hospital discharges in Hospital Episodes Statistics (HES) and the national death registration in the Office for National Statistics (ONS) registry. In Sweden, the Swedish Heart Failure Registry (SwedeHF) for long-term follow-up of HF management would be used. In the Netherlands, a nationwide HF registry is available through linkage of the Population Register, Hospital Discharge Register, and cause of death register. Additional linkage with Vektis (insurance company data) provides information about prescriptions of medication and use of care. Lastly, in Spain ABUCASIS, an electronic centralized clinical record system for primary and secondary ambulatory care in the Valencia Community would be used for the international comparison of HF care. The common denominator of all four registries is patients hospitalised for HF. Our study focuses on the follow-up of these patients, with a common follow-time between the registries from 2008 - 2014. Patients are followed until death, as defined in the national mortality registrations of the participant countries. In collaboration with the Hyve, a company that specialises in data management, our team harmonises the data from all registries to create a common model which can be applied to all, Definition of heart failure and myocardial infarction Patients included in the study are 30 years and older and have been diagnosed with HF through an ICD-10/ICD-9 code for HF (ICD-10: I11.0, I13.0, I13.2, I26.0, I50/ ICD-9: 402.01, 402.11, 402.91, 428, 398.91). For the post-MI HF studies, early-onset (in-hospital HF identified by a set of clinical parameters that define it) and late-onset HF post-MI HF (from ICD-10/ICD 9 codes for HF) are studied. Clinical outcomes The primary endpoint is the short and long-term all-cause mortality patterns as well as differences in temporal trends. Short-term mortality is defined as 30-day and 1-year mortality, whereas long-term mortality is defined as 5-year mortality. Statistical analyses Baseline patient characteristics are summarised as mean (SD) or median [IQR] for continuous variables and percentages for categorical variables. A Chi-square test is used to compare data for categorical variables, a t-test to compare means, and the Kruskal-Wallis for medians. To compare the crude and case-mix adjusted mortality across countries, we compare the 30-day, 1-year and 5-year mortality outcomes with Kaplan-Meier analysis. Cox proportional hazard model is used to estimate the case-mix adjusted mortality. Variables for case-mix adjustment are age, sex, year of admission, length of hospital admission, obesity, smoking, history of diabetes, hypertension. The mortality and association between HF/MI care on mortality are compared across the health care systems of the four countries. Results and impact With this project we aim to give an overview of the status of heart failure care and myocardial infarction care as well as potential differences in patient characteristics in European countries and highlight differences could attribute to medication uptake and mortality. We hope to create insight in the burden of HF based on real-world evidence. Other important impacts of the study include the establishment of an international co-operation on HF research, development of the BigData@Heart network and fostering a collaboration between academia and industry in heart failure and myocardial infarction research.
Collaborator Contribution The partners have contributed to the collaboration in the following aspects: 1. Assemble a unique cross-European dataset of electronic health records. 2. Create systems to develop and test the methodology for high-power identification, harmonisation, access and analysis of the assembled data. 3. Provide clinical input for disease definitions and health system characterisation. 4. Leverage the access to other unique databases. 5. Provide technical input to establish a scalable method to maximise impact and speed at which the results will be broadly implemented in other EU and non-EU countries.
Impact The project is multi-disciplinary, including the training of information science, data science, cardiology, and clinical epidemiology. Since February 2018, it has been granted a € 135.000 grant from the IMI BigData@Heart, UMCU.
Start Year 2017
 
Description Collaboration in the European BigData@Heart Consortium, a research consortium of the Innovative Medicines Initiative (IMI), a public-private initiative between the European Union and the pharmaceutical industry association, the European Federation of Pharmaceutical Industries and Associations (EFPIA). 
Organisation University of Göttingen
Country Germany 
Sector Academic/University 
PI Contribution Collaborated with researchers from the University Medical Center Utrecht, we aim to contribute to the research consortium with the investigation on the differences in the heart failure treatment and survival: a comparison between Sweden, United Kingdom, Netherlands and Spain using Linked Electronic Health Care Records. Heart failure (HF) remains a major public health issue, resulting in substantial morbidity, mortality and considerable health care costs, and myocardial infarction (MI) is one of the leading causes of heart failure (HF). MI and HF together impose a major burden on health care systems worldwide. Attributes of health care systems, such as incidence, length of stay, outcomes of hospital admissions, medication or guideline adherence could be associated with disease outcome. Though, studies that examine both health care and disease outcomes are lacking. Consequently, recognition is growing for comparative effectiveness research to improve quality and outcomes of health care. International comparisons of whole healthcare systems might yield important knowledge of distinct differences in HF care. The objective of our investigation is thus to 1) compare HF care between UK, Sweden, Spain and the Netherlands using comparable cohorts of HF patients during similar time periods, and, 2) to study how MI and HF interplay in the modern era of coronary care units, PCI technology and effective therapy in different health care systems to further harness learning opportunities. Method Population data In the UK, information about HF care would be obtained from CALIBER (CArdiovascular research using LInked Bespoke studies and Electronic Health Records). This registry links three sources of electronic health records in England: primary care records in practices contributing to the Clinical Practice Research Datalink (CPRD), secondary care hospital discharges in Hospital Episodes Statistics (HES) and the national death registration in the Office for National Statistics (ONS) registry. In Sweden, the Swedish Heart Failure Registry (SwedeHF) for long-term follow-up of HF management would be used. In the Netherlands, a nationwide HF registry is available through linkage of the Population Register, Hospital Discharge Register, and cause of death register. Additional linkage with Vektis (insurance company data) provides information about prescriptions of medication and use of care. Lastly, in Spain ABUCASIS, an electronic centralized clinical record system for primary and secondary ambulatory care in the Valencia Community would be used for the international comparison of HF care. The common denominator of all four registries is patients hospitalised for HF. Our study focuses on the follow-up of these patients, with a common follow-time between the registries from 2008 - 2014. Patients are followed until death, as defined in the national mortality registrations of the participant countries. In collaboration with the Hyve, a company that specialises in data management, our team harmonises the data from all registries to create a common model which can be applied to all, Definition of heart failure and myocardial infarction Patients included in the study are 30 years and older and have been diagnosed with HF through an ICD-10/ICD-9 code for HF (ICD-10: I11.0, I13.0, I13.2, I26.0, I50/ ICD-9: 402.01, 402.11, 402.91, 428, 398.91). For the post-MI HF studies, early-onset (in-hospital HF identified by a set of clinical parameters that define it) and late-onset HF post-MI HF (from ICD-10/ICD 9 codes for HF) are studied. Clinical outcomes The primary endpoint is the short and long-term all-cause mortality patterns as well as differences in temporal trends. Short-term mortality is defined as 30-day and 1-year mortality, whereas long-term mortality is defined as 5-year mortality. Statistical analyses Baseline patient characteristics are summarised as mean (SD) or median [IQR] for continuous variables and percentages for categorical variables. A Chi-square test is used to compare data for categorical variables, a t-test to compare means, and the Kruskal-Wallis for medians. To compare the crude and case-mix adjusted mortality across countries, we compare the 30-day, 1-year and 5-year mortality outcomes with Kaplan-Meier analysis. Cox proportional hazard model is used to estimate the case-mix adjusted mortality. Variables for case-mix adjustment are age, sex, year of admission, length of hospital admission, obesity, smoking, history of diabetes, hypertension. The mortality and association between HF/MI care on mortality are compared across the health care systems of the four countries. Results and impact With this project we aim to give an overview of the status of heart failure care and myocardial infarction care as well as potential differences in patient characteristics in European countries and highlight differences could attribute to medication uptake and mortality. We hope to create insight in the burden of HF based on real-world evidence. Other important impacts of the study include the establishment of an international co-operation on HF research, development of the BigData@Heart network and fostering a collaboration between academia and industry in heart failure and myocardial infarction research.
Collaborator Contribution The partners have contributed to the collaboration in the following aspects: 1. Assemble a unique cross-European dataset of electronic health records. 2. Create systems to develop and test the methodology for high-power identification, harmonisation, access and analysis of the assembled data. 3. Provide clinical input for disease definitions and health system characterisation. 4. Leverage the access to other unique databases. 5. Provide technical input to establish a scalable method to maximise impact and speed at which the results will be broadly implemented in other EU and non-EU countries.
Impact The project is multi-disciplinary, including the training of information science, data science, cardiology, and clinical epidemiology. Since February 2018, it has been granted a € 135.000 grant from the IMI BigData@Heart, UMCU.
Start Year 2017
 
Description Collaboration in the European BigData@Heart Consortium, a research consortium of the Innovative Medicines Initiative (IMI), a public-private initiative between the European Union and the pharmaceutical industry association, the European Federation of Pharmaceutical Industries and Associations (EFPIA). 
Organisation Uppsala University
Department Uppsala Clinical Research Center
Country Sweden 
Sector Hospitals 
PI Contribution Collaborated with researchers from the University Medical Center Utrecht, we aim to contribute to the research consortium with the investigation on the differences in the heart failure treatment and survival: a comparison between Sweden, United Kingdom, Netherlands and Spain using Linked Electronic Health Care Records. Heart failure (HF) remains a major public health issue, resulting in substantial morbidity, mortality and considerable health care costs, and myocardial infarction (MI) is one of the leading causes of heart failure (HF). MI and HF together impose a major burden on health care systems worldwide. Attributes of health care systems, such as incidence, length of stay, outcomes of hospital admissions, medication or guideline adherence could be associated with disease outcome. Though, studies that examine both health care and disease outcomes are lacking. Consequently, recognition is growing for comparative effectiveness research to improve quality and outcomes of health care. International comparisons of whole healthcare systems might yield important knowledge of distinct differences in HF care. The objective of our investigation is thus to 1) compare HF care between UK, Sweden, Spain and the Netherlands using comparable cohorts of HF patients during similar time periods, and, 2) to study how MI and HF interplay in the modern era of coronary care units, PCI technology and effective therapy in different health care systems to further harness learning opportunities. Method Population data In the UK, information about HF care would be obtained from CALIBER (CArdiovascular research using LInked Bespoke studies and Electronic Health Records). This registry links three sources of electronic health records in England: primary care records in practices contributing to the Clinical Practice Research Datalink (CPRD), secondary care hospital discharges in Hospital Episodes Statistics (HES) and the national death registration in the Office for National Statistics (ONS) registry. In Sweden, the Swedish Heart Failure Registry (SwedeHF) for long-term follow-up of HF management would be used. In the Netherlands, a nationwide HF registry is available through linkage of the Population Register, Hospital Discharge Register, and cause of death register. Additional linkage with Vektis (insurance company data) provides information about prescriptions of medication and use of care. Lastly, in Spain ABUCASIS, an electronic centralized clinical record system for primary and secondary ambulatory care in the Valencia Community would be used for the international comparison of HF care. The common denominator of all four registries is patients hospitalised for HF. Our study focuses on the follow-up of these patients, with a common follow-time between the registries from 2008 - 2014. Patients are followed until death, as defined in the national mortality registrations of the participant countries. In collaboration with the Hyve, a company that specialises in data management, our team harmonises the data from all registries to create a common model which can be applied to all, Definition of heart failure and myocardial infarction Patients included in the study are 30 years and older and have been diagnosed with HF through an ICD-10/ICD-9 code for HF (ICD-10: I11.0, I13.0, I13.2, I26.0, I50/ ICD-9: 402.01, 402.11, 402.91, 428, 398.91). For the post-MI HF studies, early-onset (in-hospital HF identified by a set of clinical parameters that define it) and late-onset HF post-MI HF (from ICD-10/ICD 9 codes for HF) are studied. Clinical outcomes The primary endpoint is the short and long-term all-cause mortality patterns as well as differences in temporal trends. Short-term mortality is defined as 30-day and 1-year mortality, whereas long-term mortality is defined as 5-year mortality. Statistical analyses Baseline patient characteristics are summarised as mean (SD) or median [IQR] for continuous variables and percentages for categorical variables. A Chi-square test is used to compare data for categorical variables, a t-test to compare means, and the Kruskal-Wallis for medians. To compare the crude and case-mix adjusted mortality across countries, we compare the 30-day, 1-year and 5-year mortality outcomes with Kaplan-Meier analysis. Cox proportional hazard model is used to estimate the case-mix adjusted mortality. Variables for case-mix adjustment are age, sex, year of admission, length of hospital admission, obesity, smoking, history of diabetes, hypertension. The mortality and association between HF/MI care on mortality are compared across the health care systems of the four countries. Results and impact With this project we aim to give an overview of the status of heart failure care and myocardial infarction care as well as potential differences in patient characteristics in European countries and highlight differences could attribute to medication uptake and mortality. We hope to create insight in the burden of HF based on real-world evidence. Other important impacts of the study include the establishment of an international co-operation on HF research, development of the BigData@Heart network and fostering a collaboration between academia and industry in heart failure and myocardial infarction research.
Collaborator Contribution The partners have contributed to the collaboration in the following aspects: 1. Assemble a unique cross-European dataset of electronic health records. 2. Create systems to develop and test the methodology for high-power identification, harmonisation, access and analysis of the assembled data. 3. Provide clinical input for disease definitions and health system characterisation. 4. Leverage the access to other unique databases. 5. Provide technical input to establish a scalable method to maximise impact and speed at which the results will be broadly implemented in other EU and non-EU countries.
Impact The project is multi-disciplinary, including the training of information science, data science, cardiology, and clinical epidemiology. Since February 2018, it has been granted a € 135.000 grant from the IMI BigData@Heart, UMCU.
Start Year 2017
 
Description Collaboration in the UK BioBank 
Organisation UK Biobank
Country United Kingdom 
Sector Charity/Non Profit 
PI Contribution Serum uric acid (SUA) level has been observed to be associated with the risk of developing cardiovascular diseases (CVDs) in some studies, while other studies showed controversial results. A further causal relationship between SUA and CVDs has been discussed but not yet established. My colleague and I thus initiated a study to investigate the causal relationship between SUA and CVDs. It is composed of an observational study with population linked electronic health records and a Mendelian randomisation study based on the UK Biobank data. The study is in collaboration with the approved research project in the UK BioBank, focused on drug repurposing, Mendelian randomisation and genome-scan.
Collaborator Contribution Our collaborator contributes to the partnership by providing access to the full UKBioBank data (genotype and cardiovascular disease outcomes).
Impact The expected output of the collaboration is the publication of serum uric acid level and the cardiovascular risk, with findings from populational linked electronic health records and Mendelian randomisation results. Simultaneously, the feasibility of international comparison based on the UK BioBank and Taiwan BioBank data is evaluated for genotype and CVD outcomes are under evaluation, for the next step in the collaboration.
Start Year 2018
 
Description Collaboration in the UK BioBank 
Organisation University College London
Country United Kingdom 
Sector Academic/University 
PI Contribution Serum uric acid (SUA) level has been observed to be associated with the risk of developing cardiovascular diseases (CVDs) in some studies, while other studies showed controversial results. A further causal relationship between SUA and CVDs has been discussed but not yet established. My colleague and I thus initiated a study to investigate the causal relationship between SUA and CVDs. It is composed of an observational study with population linked electronic health records and a Mendelian randomisation study based on the UK Biobank data. The study is in collaboration with the approved research project in the UK BioBank, focused on drug repurposing, Mendelian randomisation and genome-scan.
Collaborator Contribution Our collaborator contributes to the partnership by providing access to the full UKBioBank data (genotype and cardiovascular disease outcomes).
Impact The expected output of the collaboration is the publication of serum uric acid level and the cardiovascular risk, with findings from populational linked electronic health records and Mendelian randomisation results. Simultaneously, the feasibility of international comparison based on the UK BioBank and Taiwan BioBank data is evaluated for genotype and CVD outcomes are under evaluation, for the next step in the collaboration.
Start Year 2018
 
Description Collaboration in the UK BioBank 
Organisation University of Groningen
Country Netherlands 
Sector Academic/University 
PI Contribution Serum uric acid (SUA) level has been observed to be associated with the risk of developing cardiovascular diseases (CVDs) in some studies, while other studies showed controversial results. A further causal relationship between SUA and CVDs has been discussed but not yet established. My colleague and I thus initiated a study to investigate the causal relationship between SUA and CVDs. It is composed of an observational study with population linked electronic health records and a Mendelian randomisation study based on the UK Biobank data. The study is in collaboration with the approved research project in the UK BioBank, focused on drug repurposing, Mendelian randomisation and genome-scan.
Collaborator Contribution Our collaborator contributes to the partnership by providing access to the full UKBioBank data (genotype and cardiovascular disease outcomes).
Impact The expected output of the collaboration is the publication of serum uric acid level and the cardiovascular risk, with findings from populational linked electronic health records and Mendelian randomisation results. Simultaneously, the feasibility of international comparison based on the UK BioBank and Taiwan BioBank data is evaluated for genotype and CVD outcomes are under evaluation, for the next step in the collaboration.
Start Year 2018
 
Description Collaboration with the Global Burden of Disease Study (GBD) 
Organisation Global Burden of Disease Study
Country Global 
Sector Academic/University 
PI Contribution 1) As a collaborator for the Global Burden of Disease, I provided feedback on the disease burden estimate methodology and output for the following areas: cause of death data process, hospital data process, hemorrhage, intracerebral hemorrhage, and stroke envelope, hypertensive heart disease, non-rheumatic valvular heart disease, atrial fibrillation and flutter, bullying, high LDL cholesterol, high systolic blood pressure. 2) As a collaborator for the Global Burden of Disease, I input on the following manuscripts of the Global Burden of Disease: GBD Capstone Paper: Measuring performance on the Healthcare Access and Quality Index for 195 countries and territories and selected subnational locations: a systematic analysis from the Global Burden of Disease Study 2016 Alcohol use and attributable disease burden in 195 countries and territories, 1990-2016: a systematic analysis of the Global Burden of Disease Study 2016. Global, Regional, and National Cancer Incidence, Mortality, Years of Life Lost, Years Lived With Disability, and Disability-Adjusted Life-years for 29 Cancer Groups, 2006 to 2016: A Systematic Analysis for the Global Burden of Disease Study. 3) I provide access to the Taiwanese population data to the GBD study. 4) Involving GBD colleague in the between-country comparison on cardiovascular diseases led by me.
Collaborator Contribution The Global Burden of Disease contribute to the collaboration from the following aspects: 1) provided latest updated international estimates on the cause of death and risk factors worldwide. 2) provide training on the methodology of the GBD estimates. 3) provide research opportunities based on GBD data.
Impact I input on the following manuscripts as the collaborator of the Global Burden of Disease. The research is multi-disciplinary (clinical science, data science and epidemiology). GBD Capstone Paper: Measuring performance on the Healthcare Access and Quality Index for 195 countries and territories and selected subnational locations: a systematic analysis from the Global Burden of Disease Study 2016 Alcohol use and attributable disease burden in 195 countries and territories, 1990-2016: a systematic analysis of the Global Burden of Disease Study 2016. Global, Regional, and National Cancer Incidence, Mortality, Years of Life Lost, Years Lived With Disability, and Disability-Adjusted Life-years for 29 Cancer Groups, 2006 to 2016: A Systematic Analysis for the Global Burden of Disease Study.
Start Year 2017
 
Description Collaboration with the Global Burden of Disease Study (GBD) 
Organisation Institute for Health Metrics and Evaluation (IHME)
Country United States 
Sector Charity/Non Profit 
PI Contribution 1) As a collaborator for the Global Burden of Disease, I provided feedback on the disease burden estimate methodology and output for the following areas: cause of death data process, hospital data process, hemorrhage, intracerebral hemorrhage, and stroke envelope, hypertensive heart disease, non-rheumatic valvular heart disease, atrial fibrillation and flutter, bullying, high LDL cholesterol, high systolic blood pressure. 2) As a collaborator for the Global Burden of Disease, I input on the following manuscripts of the Global Burden of Disease: GBD Capstone Paper: Measuring performance on the Healthcare Access and Quality Index for 195 countries and territories and selected subnational locations: a systematic analysis from the Global Burden of Disease Study 2016 Alcohol use and attributable disease burden in 195 countries and territories, 1990-2016: a systematic analysis of the Global Burden of Disease Study 2016. Global, Regional, and National Cancer Incidence, Mortality, Years of Life Lost, Years Lived With Disability, and Disability-Adjusted Life-years for 29 Cancer Groups, 2006 to 2016: A Systematic Analysis for the Global Burden of Disease Study. 3) I provide access to the Taiwanese population data to the GBD study. 4) Involving GBD colleague in the between-country comparison on cardiovascular diseases led by me.
Collaborator Contribution The Global Burden of Disease contribute to the collaboration from the following aspects: 1) provided latest updated international estimates on the cause of death and risk factors worldwide. 2) provide training on the methodology of the GBD estimates. 3) provide research opportunities based on GBD data.
Impact I input on the following manuscripts as the collaborator of the Global Burden of Disease. The research is multi-disciplinary (clinical science, data science and epidemiology). GBD Capstone Paper: Measuring performance on the Healthcare Access and Quality Index for 195 countries and territories and selected subnational locations: a systematic analysis from the Global Burden of Disease Study 2016 Alcohol use and attributable disease burden in 195 countries and territories, 1990-2016: a systematic analysis of the Global Burden of Disease Study 2016. Global, Regional, and National Cancer Incidence, Mortality, Years of Life Lost, Years Lived With Disability, and Disability-Adjusted Life-years for 29 Cancer Groups, 2006 to 2016: A Systematic Analysis for the Global Burden of Disease Study.
Start Year 2017
 
Description New Zealand and the UK collaboration for international comparison research using nationwide linked electronic health records 
Organisation University of Auckland
Department Department of Physiology
Country New Zealand 
Sector Academic/University 
PI Contribution Currently, ongoing population-wide primary care data, with the capacity to link to other data sources, are available only in New Zealand and the UK. The collaboration is to facilitate international comparison studies based on the unique datasets in the two countries. In New Zealand, the PREDICT project is a well-established cardiovascular (CV) risk prediction and management support programme that aims to substantially improve risk estimation and risk management. PREDICT is a web-based clinical decision support tool for estimating CV risk and recommending personalised management advice, that is integrated into general practitioners electronic records. It simultaneously generates research cohorts that can be linked to routine databases enabling anonymised long-term tracking of drug dispensing, laboratory testing, hospitalisations and deaths. The project is ongoing, with over 400,000 New Zealanders in primary care having contributed at the time of their CV risk assessment. In the UK, the CALIBER program include primary care records of individual patients from the 225 primary care practices, representative to the UK population, consented to contribute data. CALIBER links patient records from four different data sources: primary care (Clinical Practice Research Datalink (CPRD), disease registry (Myocardial Ischaemia National Audit Project registry (MINAP)), hospital care (Hospital Episodes Statistics (HES)), and death registry (the Office of National Statistics (ONS)). The contributions made by me and the UK research team is to liaise with researchers from New Zealand (University of Aukland) to create harmonised approaches for the responsible, voluntary, and secure sharing of health data in the two countries for research; meanwhile, to develop and implement international research projects based on PREDICT and CALIBER.
Collaborator Contribution The New Zealand research team contributes to the collaboration through shared leadership with the UK investigators in both institutional collaboration and research projects. The New Zealand and UK team jointly design and implement the research projects, where each country is responsible for its data management and analysis, based on harmonised approach agreed by both countries, and form the synthesis of findings together.
Impact Two publications have been generated from the international comparison studies based on the collaboration: 1) Shah AD, Thorney S. Chung SC et al. White cell count in the normal range and short and long term mortality: international comparisons of electronic health record cohorts in England and New Zealand. BMJ Open. 2017 Feb 17;7(2):e013100. 2) Poppe KK, Doughty RN, Wells S, Gentles D, Hemingway H, Jackson R, Kerr AJ. Developing and validating a cardiovascular risk score for patients in the community with prior cardiovascular disease. Heart. 2017 Feb 23.
Start Year 2014
 
Description Sweden and the UK collaboration for international comparison research using nationwide linked electronic health records 
Organisation Karolinska Institute
Country Sweden 
Sector Academic/University 
PI Contribution Sweden and the UK are the only two countries worldwide that have continuous national clinical registries for acute coronary syndrome with mandated participation for all hospitals. Comparison of these two countries is facilitated by the similarity of their health systems (universal, funded from taxation, and free at the point of use), proportion of gross domestic product spent on health, and national policy guidance provided for the evidence-based management of acute myocardial infarction. In the collaboration, experts from the field of nationwide linked electronic health records for cardiovascular diseases in Sweden and the UK have worked together in international comparison studies. Our collaborators include established colleagues (e.g. Lars Wallentin, Uppsala, Sweden) and via new collaborations (e.g. Johan Sundström, Uppsala, Sweden). Members of the collaboration work together to create harmonised approaches for the responsible, voluntary, and secure sharing of health data in the two countries for research (SWEDEHEART, Swedish Web-System for Enhancement and Development of Evidence-Based Care in Heart Disease Evaluated According to Recommended Therapies, NICOR/MINAP (National Institute for Cardiovascular Outcomes Research/Myocardial Ischaemia National Audit Project), and CALIBER (CAardiovascular disease research using linked bespoke studies and electronic health records in the UK). The contributions made by me is to firstly coordinate and bond the collaboration through regular communication, either in person or through teleconference. Secondly, I am responsible for the two research projects of the collaboration, and assume the roles to establish and implement the strategy, timeline, data and output of the collaborative projects. Thirdly, I am trusted by both countries to conduct data analysis based on national data, either on site or remotely through secured computing system . The UK Research team initiated and continue to provide guidance in the collective leadership for the collaboration among institutes from both countries.
Collaborator Contribution The Swedish research team provides shared leadership with the UK investigators in both institutional collaboration and research projects. Swedish team has engaged in all coordination and communication of the collaboration, provided support in dedicated computing and IT resources, and granted named researcher voluntary secured access to national data for research projects.
Impact Three publications have been generated from the international comparison studies based on the collaboration. Chung SC, Gedeborg R, Nicholas O et al. Acute myocardial infarction: a comparison of short-term survival in national outcome registries in Sweden and the UK. Lancet. 2014 Apr 12;383(9925):1305-12. McNamara RL, Chung SC, Jernberg T, Holmes D, Roe M, Timmis A, James S, Deanfield J, Fonarow GC, Peterson ED, Jeppsson A, Hemingway H. International comparisons of the management of patients with non-ST segment elevation acute myocardial infarction in the United Kingdom, Sweden, and the United States: The MINAP/NICOR, SWEDEHEART/RIKS-HIA, and ACTION Registry-GWTG/NCDR registries. Int J Cardiol. 2014 Aug 1;175(2):240-7. Chung SC, Sundström J, Gale CP et al. Comparison of hospital variation in acute myocardial infarction care and outcome between Sweden and United Kingdom: population based cohort study using nationwide clinical registries. BMJ. 2015 Aug 7;351:h3913. Rapsomaniki E, Thuresson M, Yang E, Blin P, Hunt P, Chung SC et al. Using big data from health records from four countries to evaluate chronic disease outcomes: a study in 114 364 survivors of myocardial infarction. Eur Heart J Qual Care Clin Outcomes. 2016 Feb 20;2(2):125-140.
Start Year 2011
 
Description Sweden and the UK collaboration for international comparison research using nationwide linked electronic health records 
Organisation Uppsala University
Department Uppsala Biomedical Centre
Country Sweden 
Sector Academic/University 
PI Contribution Sweden and the UK are the only two countries worldwide that have continuous national clinical registries for acute coronary syndrome with mandated participation for all hospitals. Comparison of these two countries is facilitated by the similarity of their health systems (universal, funded from taxation, and free at the point of use), proportion of gross domestic product spent on health, and national policy guidance provided for the evidence-based management of acute myocardial infarction. In the collaboration, experts from the field of nationwide linked electronic health records for cardiovascular diseases in Sweden and the UK have worked together in international comparison studies. Our collaborators include established colleagues (e.g. Lars Wallentin, Uppsala, Sweden) and via new collaborations (e.g. Johan Sundström, Uppsala, Sweden). Members of the collaboration work together to create harmonised approaches for the responsible, voluntary, and secure sharing of health data in the two countries for research (SWEDEHEART, Swedish Web-System for Enhancement and Development of Evidence-Based Care in Heart Disease Evaluated According to Recommended Therapies, NICOR/MINAP (National Institute for Cardiovascular Outcomes Research/Myocardial Ischaemia National Audit Project), and CALIBER (CAardiovascular disease research using linked bespoke studies and electronic health records in the UK). The contributions made by me is to firstly coordinate and bond the collaboration through regular communication, either in person or through teleconference. Secondly, I am responsible for the two research projects of the collaboration, and assume the roles to establish and implement the strategy, timeline, data and output of the collaborative projects. Thirdly, I am trusted by both countries to conduct data analysis based on national data, either on site or remotely through secured computing system . The UK Research team initiated and continue to provide guidance in the collective leadership for the collaboration among institutes from both countries.
Collaborator Contribution The Swedish research team provides shared leadership with the UK investigators in both institutional collaboration and research projects. Swedish team has engaged in all coordination and communication of the collaboration, provided support in dedicated computing and IT resources, and granted named researcher voluntary secured access to national data for research projects.
Impact Three publications have been generated from the international comparison studies based on the collaboration. Chung SC, Gedeborg R, Nicholas O et al. Acute myocardial infarction: a comparison of short-term survival in national outcome registries in Sweden and the UK. Lancet. 2014 Apr 12;383(9925):1305-12. McNamara RL, Chung SC, Jernberg T, Holmes D, Roe M, Timmis A, James S, Deanfield J, Fonarow GC, Peterson ED, Jeppsson A, Hemingway H. International comparisons of the management of patients with non-ST segment elevation acute myocardial infarction in the United Kingdom, Sweden, and the United States: The MINAP/NICOR, SWEDEHEART/RIKS-HIA, and ACTION Registry-GWTG/NCDR registries. Int J Cardiol. 2014 Aug 1;175(2):240-7. Chung SC, Sundström J, Gale CP et al. Comparison of hospital variation in acute myocardial infarction care and outcome between Sweden and United Kingdom: population based cohort study using nationwide clinical registries. BMJ. 2015 Aug 7;351:h3913. Rapsomaniki E, Thuresson M, Yang E, Blin P, Hunt P, Chung SC et al. Using big data from health records from four countries to evaluate chronic disease outcomes: a study in 114 364 survivors of myocardial infarction. Eur Heart J Qual Care Clin Outcomes. 2016 Feb 20;2(2):125-140.
Start Year 2011
 
Description Taiwan and the UK collaboration for international comparison research using nationwide linked electronic health records 
Organisation Fu Jen Catholic University
Country Taiwan, Province of China 
Sector Academic/University 
PI Contribution The collaboration is formed to first facilitate the international comparison research based on nationwide linked electronic health records in Taiwan and the UK. Secondly, to facilitate understanding of the health informatics science infrastructure between the two countries. In Taiwan, the National Health Insurance Research Database (NHIRD) is a population-based database derived from the claims data of the National Health Insurance (NHI) program, which has been established since 1995 that covers almost all (> 99%) of the 23 million population in Taiwan. In the UK, the ClinicAl research using LInked Bespoke studies and Electronic health Records (CALIBER) provides a continuing longitudinal record of health status from healthy to initial diagnosis in primary care, through hospital admissions, to death as recorded in the national death registry. The contributions made by me is to firstly initiate and facilitate the collaboration through regular communication through in person meeting and teleconference. Secondly, I am responsible for form initial research projects of the collaboration, and assume the roles to establish and implement the strategy, timeline, and output of the collaborative projects.
Collaborator Contribution The Taiwanese research team contributes to the collaboration through shared leadership in collaborative research projects. The Taiwanese team has engaged in the coordination and communication of the collaboration, and provide support in dedicated staff, as well as granting named researcher voluntary secured access to national data in Taiwan for research projects.
Impact The collaboration is in its initial stage, and research outputs to be expected in the coming year.
Start Year 2016