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Data saves lives: optimising routinely collected clinical data for rare disease research
Ameenat Lola Solebo1,2,3, Pirro Hysi4,5,6, Lisanne Andra Horvat-Gitsels4,7
1Population, Policy and Practice Research and Teaching Department, Great Ormond Street Institute of Child Health, University College London, 30 Guilford Street, London, WC1N 1EH, UK. a.solebo@ucl.ac.uk.
Orphanet Journal of Rare Diseases
|September 11, 2023
Summary
Healthcare providers are using innovations to manage health data post-pandemic. Engaging with health data informatics is crucial for rare disease research to avoid being left behind.
Area of Science:
- Health Informatics
- Data Science in Healthcare
- Clinical Data Management
Background:
- Post-pandemic organizational changes necessitate innovations in health data management.
- Real-world datasets of routinely collected clinical information are increasingly used for data-driven healthcare delivery.
Discussion:
- Rare diseases risk being overlooked without engagement in health data informatics.
- Challenges exist in the meaningful use and reuse of rare disease data.
- Addressing these challenges requires a concerted effort from clinical and research communities.
Key Insights:
- Recommendations include workforce education in health data informatics.
- Harmonization of taxonomy is essential for consistent data interpretation.
- Ensuring an inclusive health data environment is critical for all patient groups.
Outlook:
- Proactive engagement with health data informatics is vital for the rare disease community.
- Implementing proposed recommendations can facilitate better data utilization.
- This approach supports equitable advancement in rare disease research and care.
Keywords:
BiomedicalElectronic health recordsEpidemiologyInformation managementRare diseaseTranslational researchMore Related Videos
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