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

被引:2
|
作者
Solebo, Ameenat Lola [1 ,2 ,3 ]
Hysi, Pirro [1 ,4 ,5 ]
Horvat-Gitsels, Lisanne Andra [1 ,2 ]
Rahi, Jugnoo Sangeeta [1 ,2 ,3 ,6 ,7 ]
机构
[1] UCL, Populat Policy & Practice Res & Teaching Dept, Great Ormond St Inst Child Hlth, 30 Guilford St, London WC1N 1EH, England
[2] UCL, Great Ormond St Inst Child Hlth, Ulverscroft Vis Res Grp, London, England
[3] Great Ormond St Hosp Sick Children, NHS Fdn Trust, London, England
[4] Kings Coll London, Sch Life Course Sci, Sect Ophthalmol, London, England
[5] Kings Coll London, Sch Life Course Sci, Dept Twin Res & Genet Epidemiol, London, England
[6] UCL, Inst Ophthalmol, London, England
[7] NIHR Moorfields Biomed Res Ctr London, London, England
关键词
Electronic health records; Information management; Rare disease; Translational research; Biomedical; Epidemiology; ELECTRONIC HEALTH RECORDS; REGISTRY;
D O I
10.1186/s13023-023-02912-1
中图分类号
Q3 [遗传学];
学科分类号
071007 ; 090102 ;
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.
引用
收藏
页数:7
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