Citation

Lyons RA. Inj. Prev. 2020; 26(4): 397-399.

Copyright

(Copyright © 2020, BMJ Publishing Group)

DOI

10.1136/injuryprev-2019-043369

PMID

32694194

Abstract

In a world of competing priorities, accurate production of information on the scale of the injury burden and the effectiveness of prevention-orientated interventions and policies is important; hence, data quality matters. This article surveys the literature about what is known about data quality in the injury field and developments to improve the quality and usability of information, particularly through triangulation of data sources, data linkage and unlocking the potential for more deeply phenotyped data through natural language processing.

Language: en

Keywords

epidemiology; advocacy; coding systems