The Australian Genetic Heart Disease Registry: Protocol for a Data Linkage Study.

arrhythmia big data cardiology cardiomyopathies data linkage genetic heart diseases genetics harmonization health care use heart mortality national probabilistic matching registries registry risk

Journal

JMIR research protocols
ISSN: 1929-0748
Titre abrégé: JMIR Res Protoc
Pays: Canada
ID NLM: 101599504

Informations de publication

Date de publication:
20 Sep 2023
Historique:
received: 01 05 2023
accepted: 26 07 2023
revised: 25 07 2023
medline: 20 9 2023
pubmed: 20 9 2023
entrez: 20 9 2023
Statut: epublish

Résumé

Genetic heart diseases such as hypertrophic cardiomyopathy can cause significant morbidity and mortality, ranging from syncope, chest pain, and palpitations to heart failure and sudden cardiac death. These diseases are inherited in an autosomal dominant fashion, meaning family members of affected individuals have a 1 in 2 chance of also inheriting the disease ("at-risk relatives"). The health care use patterns of individuals with a genetic heart disease, including emergency department presentations and hospital admissions, are poorly understood. By linking genetic heart disease registry data to routinely collected health data, we aim to provide a more comprehensive clinical data set to examine the burden of disease on individuals, families, and health care systems. The objective of this study is to link the Australian Genetic Heart Disease (AGHD) Registry with routinely collected whole-population health data sets to investigate the health care use of individuals with a genetic heart disease and their at-risk relatives. This linked data set will allow for the investigation of differences in outcomes and health care use due to disease, sex, socioeconomic status, and other factors. The AGHD Registry is a nationwide data set that began in 2007 and aims to recruit individuals with a genetic heart disease and their family members. In this study, demographic, clinical, and genetic data (available from 2007 to 2019) for AGHD Registry participants and at-risk relatives residing in New South Wales (NSW), Australia, were linked to routinely collected health data. These data included NSW-based data sets covering hospitalizations (2001-2019), emergency department presentations (2005-2019), and both state-wide and national mortality registries (2007-2019). The linkage was performed by the Centre for Health Record Linkage. Investigations stratifying by diagnosis, age, sex, socioeconomic status, and gene status will be undertaken and reported using descriptive statistics. NSW AGHD Registry participants were linked to routinely collected health data sets using probabilistic matching (November 2019). Of 1720 AGHD Registry participants, 1384 had linkages with 11,610 hospital records, 7032 emergency department records, and 60 death records. Data assessment and harmonization were performed, and descriptive data analysis is underway. We intend to provide insights into the health care use patterns of individuals with a genetic heart disease and their at-risk relatives, including frequency of hospital admissions and differences due to factors such as disease, sex, and socioeconomic status. Identifying disparities and potential barriers to care may highlight specific health care needs (eg, between sexes) and factors impacting health care access and use. DERR1-10.2196/48636.

Sections du résumé

BACKGROUND BACKGROUND
Genetic heart diseases such as hypertrophic cardiomyopathy can cause significant morbidity and mortality, ranging from syncope, chest pain, and palpitations to heart failure and sudden cardiac death. These diseases are inherited in an autosomal dominant fashion, meaning family members of affected individuals have a 1 in 2 chance of also inheriting the disease ("at-risk relatives"). The health care use patterns of individuals with a genetic heart disease, including emergency department presentations and hospital admissions, are poorly understood. By linking genetic heart disease registry data to routinely collected health data, we aim to provide a more comprehensive clinical data set to examine the burden of disease on individuals, families, and health care systems.
OBJECTIVE OBJECTIVE
The objective of this study is to link the Australian Genetic Heart Disease (AGHD) Registry with routinely collected whole-population health data sets to investigate the health care use of individuals with a genetic heart disease and their at-risk relatives. This linked data set will allow for the investigation of differences in outcomes and health care use due to disease, sex, socioeconomic status, and other factors.
METHODS METHODS
The AGHD Registry is a nationwide data set that began in 2007 and aims to recruit individuals with a genetic heart disease and their family members. In this study, demographic, clinical, and genetic data (available from 2007 to 2019) for AGHD Registry participants and at-risk relatives residing in New South Wales (NSW), Australia, were linked to routinely collected health data. These data included NSW-based data sets covering hospitalizations (2001-2019), emergency department presentations (2005-2019), and both state-wide and national mortality registries (2007-2019). The linkage was performed by the Centre for Health Record Linkage. Investigations stratifying by diagnosis, age, sex, socioeconomic status, and gene status will be undertaken and reported using descriptive statistics.
RESULTS RESULTS
NSW AGHD Registry participants were linked to routinely collected health data sets using probabilistic matching (November 2019). Of 1720 AGHD Registry participants, 1384 had linkages with 11,610 hospital records, 7032 emergency department records, and 60 death records. Data assessment and harmonization were performed, and descriptive data analysis is underway.
CONCLUSIONS CONCLUSIONS
We intend to provide insights into the health care use patterns of individuals with a genetic heart disease and their at-risk relatives, including frequency of hospital admissions and differences due to factors such as disease, sex, and socioeconomic status. Identifying disparities and potential barriers to care may highlight specific health care needs (eg, between sexes) and factors impacting health care access and use.
INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID) UNASSIGNED
DERR1-10.2196/48636.

Identifiants

DOI: 10.2196/48636 PMID: 37728963 PMC: PMC10551791
pubmed: 37728963
pii: v12i1e48636
doi: 10.2196/48636
pmc: PMC10551791
doi:

Types de publication

Journal Article

Langues

eng

Pagination

e48636

Informations de copyright

©Alexandra Butters, Bianca Blanch, Anna Kemp-Casey, Judy Do, Laura Yeates, Felicity Leslie, Christopher Semsarian, Lee Nedkoff, Tom Briffa, Jodie Ingles, Joanna Sweeting. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 20.09.2023.

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Auteurs

Alexandra Butters (A)

Clinical Genomics Laboratory, Centre for Population Genomics, Garvan Institute of Medical Research, Darlinghurst, Australia.
Clinical Genomics Laboratory, Centre for Population Genomics, Murdoch Children's Research Institute, Melbourne, Australia.
Faculty of Medicine and Health, The University of Sydney, Sydney, Australia.
ORCID: 0000-0003-1626-4302

Bianca Blanch (B)

Agnes Ginges Centre for Molecular Cardiology, Centenary Institute, The University of Sydney, Sydney, Australia.
ORCID: 0000-0002-0853-9401

Anna Kemp-Casey (A)

Clinical and Health Sciences, University of South Australia, Adelaide, Australia.
ORCID: 0000-0002-0018-962X

Judy Do (J)

Clinical Genomics Laboratory, Centre for Population Genomics, Garvan Institute of Medical Research, Darlinghurst, Australia.
Clinical Genomics Laboratory, Centre for Population Genomics, Murdoch Children's Research Institute, Melbourne, Australia.
ORCID: 0009-0007-5181-808X

Laura Yeates (L)

Clinical Genomics Laboratory, Centre for Population Genomics, Garvan Institute of Medical Research, Darlinghurst, Australia.
Clinical Genomics Laboratory, Centre for Population Genomics, Murdoch Children's Research Institute, Melbourne, Australia.
Faculty of Medicine and Health, The University of Sydney, Sydney, Australia.
Agnes Ginges Centre for Molecular Cardiology, Centenary Institute, The University of Sydney, Sydney, Australia.
Department of Cardiology, Royal Prince Alfred Hospital, Sydney, Australia.
ORCID: 0000-0001-8348-815X

Felicity Leslie (F)

Clinical Genomics Laboratory, Centre for Population Genomics, Garvan Institute of Medical Research, Darlinghurst, Australia.
Clinical Genomics Laboratory, Centre for Population Genomics, Murdoch Children's Research Institute, Melbourne, Australia.
ORCID: 0009-0001-5402-9568

Christopher Semsarian (C)

Faculty of Medicine and Health, The University of Sydney, Sydney, Australia.
Agnes Ginges Centre for Molecular Cardiology, Centenary Institute, The University of Sydney, Sydney, Australia.
Department of Cardiology, Royal Prince Alfred Hospital, Sydney, Australia.
ORCID: 0000-0001-6441-274X

Lee Nedkoff (L)

School of Population and Global Health, The University of Western Australia, Perth, Australia.
Victor Change Cardiac Research Institute, Sydney, Australia.
ORCID: 0000-0002-3970-625X

Tom Briffa (T)

School of Population and Global Health, The University of Western Australia, Perth, Australia.
ORCID: 0009-0000-0012-6461

Jodie Ingles (J)

Clinical Genomics Laboratory, Centre for Population Genomics, Garvan Institute of Medical Research, Darlinghurst, Australia.
Clinical Genomics Laboratory, Centre for Population Genomics, Murdoch Children's Research Institute, Melbourne, Australia.
Department of Cardiology, Royal Prince Alfred Hospital, Sydney, Australia.
ORCID: 0000-0002-4846-7676

Joanna Sweeting (J)

Clinical Genomics Laboratory, Centre for Population Genomics, Garvan Institute of Medical Research, Darlinghurst, Australia.
Clinical Genomics Laboratory, Centre for Population Genomics, Murdoch Children's Research Institute, Melbourne, Australia.
ORCID: 0000-0001-9497-601X

Classifications MeSH