Solebo, Ameenat Lola;
Hysi, Pirro;
Horvat-Gitsels, Lisanne Andra;
Rahi, Jugnoo Sangeeta;
(2023)
Data saves lives: optimising routinely collected clinical data for rare disease research.
Orphanet Journal of Rare Diseases
, 18
, Article 285. 10.1186/s13023-023-02912-1.
Preview |
Text
s13023-023-02912-1.pdf - Published Version Download (920kB) | Preview |
Abstract
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.
| Type: | Article |
|---|---|
| Title: | Data saves lives: optimising routinely collected clinical data for rare disease research |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1186/s13023-023-02912-1 |
| Publisher version: | https://doi.org/10.1186/s13023-023-02912-1 |
| Language: | English |
| Additional information: | Copyright © The Author(s) 2023. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecom‑ mons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
| Keywords: | Electronic health records; Information management; Rare disease; Translational research; Biomedical; Epidemiology |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL GOS Institute of Child Health UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL GOS Institute of Child Health > Population, Policy and Practice Dept |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10176546 |
Archive Staff Only
 |
View Item |
