Using topic modelling for unsupervised annotation of electronic health records to identify an outbreak of disease in UK dogs.

ABSTRACT: A key goal of disease surveillance is to identify outbreaks of known or novel diseases in a timely manner. Such an outbreak occurred in the UK associated with acute vomiting in dogs between December 2019 and March 2020. We tracked this outbreak using the clinical free text component of anonymised electronic health records (EHRs) collected from a sentinel network of participating veterinary practices. We sourced the free text (narrative) component of each EHR supplemented with one of 10 practitioner-derived main presenting complaints (MPCs), with the 'gastroenteric' MPC identifying cases involved in the disease outbreak. Such clinician-derived annotation systems can suffer from poor compliance requiring retrospective, often manual, coding, thereby limiting real-time usability, especially wh

SUBMITTER: Noble PM 

PROVIDER: S-EPMC8659617 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature