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Data saves lives: optimising routinely collected clinical data for rare disease research

Necessity driven organisational change in the post-pandemic landscape has seen health care providers adopting innovations to manage and process health data. These include the use of ‘real-world’ datasets of routinely collected clinical information, enabling data-driven delivery. Rare disease risks b...

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Detalles Bibliográficos
Autores principales: Solebo, Ameenat Lola, Hysi, Pirro, Horvat-Gitsels, Lisanne Andra, Rahi, Jugnoo Sangeeta
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10496203/
https://www.ncbi.nlm.nih.gov/pubmed/37697298
http://dx.doi.org/10.1186/s13023-023-02912-1
Descripción
Sumario:Necessity driven organisational change in the post-pandemic landscape has seen health care providers adopting innovations to manage and process health data. These include the use of ‘real-world’ datasets of routinely collected clinical information, enabling data-driven delivery. Rare disease risks being ‘left-behind’ unless our clinical and research communities engage with the challenges and opportunities afforded by the burgeoning field of health data informatics. We address the challenges to the meaningful use and reuse of rare disease data, and, through a series of recommendations around workforce education, harmonisation of taxonomy, and ensuring an inclusive health data environment, we highlight the role that those who manage rare disease must play in addressing them.