Alpha NSW: What would it take to create a state-wide paediatric population-level learning health system?

child health data systems health information management learning health system systems integration

Journal

Health information management : journal of the Health Information Management Association of Australia
ISSN: 1833-3575
Titre abrégé: Health Inf Manag
Pays: Australia
ID NLM: 9438200

Informations de publication

Date de publication:
07 Jul 2023
Historique:
medline: 7 7 2023
pubmed: 7 7 2023
entrez: 7 7 2023
Statut: aheadofprint

Résumé

The health and well-being of children in the first 2000 days has a lasting effect on educational achievement and long-term chronic disease in later life. However, the lack of integration between high-quality data, analytic capacity and timely health improvement initiatives means practitioners, service leaders and policymakers cannot use data effectively to plan and evaluate early intervention services and monitor high-level health outcomes. Our exploratory study aimed to develop an in-depth understanding of the system and clinical requirements of a state-wide paediatric learning health system (LHS) that uses routinely collected data to not only identify where the inequities and variation in care are, but also to also inform service development and delivery where it is needed most. Our approach included reviewing exemplars of how administrative data are used in Australia; consulting with clinical, policy and data stakeholders to determine their needs for a child health LHS; mapping the existing data points collected across the first 2000 days of a child's life and geospatially locating patterns of key indicators for child health needs. Our study identified the indicators that are available and accessible to inform service delivery and demonstrated the potential of using routinely collected administrative data to identify the gap between health needs and service availability. We recommend improving data collection, accessibility and integration to establish a state-wide LHS, whereby there is a streamlined process for data cleaning, analysis and visualisation to help identify populations in need in a timely manner.

Sections du résumé

BACKGROUND UNASSIGNED
The health and well-being of children in the first 2000 days has a lasting effect on educational achievement and long-term chronic disease in later life. However, the lack of integration between high-quality data, analytic capacity and timely health improvement initiatives means practitioners, service leaders and policymakers cannot use data effectively to plan and evaluate early intervention services and monitor high-level health outcomes.
OBJECTIVE UNASSIGNED
Our exploratory study aimed to develop an in-depth understanding of the system and clinical requirements of a state-wide paediatric learning health system (LHS) that uses routinely collected data to not only identify where the inequities and variation in care are, but also to also inform service development and delivery where it is needed most.
METHOD UNASSIGNED
Our approach included reviewing exemplars of how administrative data are used in Australia; consulting with clinical, policy and data stakeholders to determine their needs for a child health LHS; mapping the existing data points collected across the first 2000 days of a child's life and geospatially locating patterns of key indicators for child health needs.
RESULTS UNASSIGNED
Our study identified the indicators that are available and accessible to inform service delivery and demonstrated the potential of using routinely collected administrative data to identify the gap between health needs and service availability.
CONCLUSION UNASSIGNED
We recommend improving data collection, accessibility and integration to establish a state-wide LHS, whereby there is a streamlined process for data cleaning, analysis and visualisation to help identify populations in need in a timely manner.

Identifiants

pubmed: 37417664
doi: 10.1177/18333583231176597
doi:

Types de publication

Journal Article

Langues

eng

Pagination

18333583231176597

Auteurs

Michael Hodgins (M)

University of New South Wales, Australia.

Nora Samir (N)

University of New South Wales, Australia.

Susan Woolfenden (S)

University of New South Wales, Australia.
Sydney Institute for Women, Children and their Families, Sydney Local Health District, Australia.

Nan Hu (N)

University of New South Wales, Australia.

Francisco Schneuer (F)

Child Population and Translational Health Research, The University of Sydney, Australia.

Natasha Nassar (N)

Child Population and Translational Health Research, The University of Sydney, Australia.
Community Child Health, Randwick, The Sydney Children's Hospitals Network, Australia.

Raghu Lingam (R)

University of New South Wales, Australia.

Classifications MeSH