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Journal article : Review

Optimizing the use of electronic medical records for large scale research in psychiatry

Abstract:
The explosion and abundance of digital data could facilitate large scale research for psychiatry and mental health. Research using so-called “real world data” – such as electronic medical/health records – can be resource-efficient, facilitate rapid hypothesis generation and testing, complement existing evidence (e.g. from trials and evidence-synthesis) and may enable a route to translate evidence into clinically effective, outcomes-driven care for patient populations that may be under-represented. However, the interpretation and processing of real world data sources is complex because the clinically important ‘signal’ is often contained in both structured and unstructured (narrative or “free-text”) data. Techniques for extracting meaningful information (signal) from unstructured text exist and have advanced the re-use of routinely collected clinical data but these techniques require cautious evaluation. In this paper, we survey the opportunities, risks and progress made in the use of electronic medical record (real world) data for psychiatric research.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1038/s41398-024-02911-1

Authors


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Institution:
University of Oxford
Division:
MSD
Department:
NDORMS
Sub department:
Centre for Statistics in Medicine
Role:
Author
ORCID:
0000-0002-3001-1478
More by this author
Institution:
University of Oxford
Division:
MSD
Department:
Psychiatry
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MSD
Department:
Psychiatry
Role:
Author
ORCID:
0000-0003-3826-7694


Publisher:
Springer Nature
Journal:
Translational Psychiatry More from this journal
Volume:
14
Article number:
232
Publication date:
2024-06-01
Acceptance date:
2024-04-15
DOI:
EISSN:
2158-3188


Language:
English
Subtype:
Review
Pubs id:
1991182
Local pid:
pubs:1991182
Deposit date:
2024-04-18

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