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

被引:0
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作者
Ameenat Lola Solebo
Pirro Hysi
Lisanne Andra Horvat-Gitsels
Jugnoo Sangeeta Rahi
机构
[1] University College London,Population, Policy and Practice Research and Teaching Department, Great Ormond Street Institute of Child Health
[2] University College London,Ulverscroft Vision Research Group, Great Ormond Street Institute of Child Health
[3] NHS Foundation Trust,Great Ormond Street Hospital for Children
[4] King’s College London,Section of Ophthalmology, School of Life Course Sciences
[5] King’s College London,Department of Twin Research and Genetic Epidemiology, School of Life Course Sciences
[6] University College London and NIHR Moorfields Biomedical Research Centre London,Institute of Ophthalmology
关键词
Electronic health records; Information management; Rare disease; Translational research; Biomedical; Epidemiology;
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摘要
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.
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