Curating a longitudinal research resource using linked primary care EHR data-a UK Biobank case study.
J Am Med Inform Assoc
; 29(3): 546-552, 2022 01 29.
Article
em En
| MEDLINE
| ID: mdl-34897458
ABSTRACT
Primary care EHR data are often of clinical importance to cohort studies however they require careful handling. Challenges include determining the periods during which EHR data were collected. Participants are typically censored when they deregister from a medical practice, however, cohort studies wish to follow participants longitudinally including those that change practice. Using UK Biobank as an exemplar, we developed methodology to infer continuous periods of data collection and maximize follow-up in longitudinal studies. This resulted in longer follow-up for around 40% of participants with multiple registration records (mean increase of 3.8 years from the first study visit). The approach did not sacrifice phenotyping accuracy when comparing agreement between self-reported and EHR data. A diabetes mellitus case study illustrates how the algorithm supports longitudinal study design and provides further validation. We use UK Biobank data, however, the tools provided can be used for other conditions and studies with minimal alteration.
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Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Bancos de Espécimes Biológicos
/
Registros Eletrônicos de Saúde
Tipo de estudo:
Observational_studies
Limite:
Humans
País/Região como assunto:
Europa
Idioma:
En
Revista:
J Am Med Inform Assoc
Assunto da revista:
INFORMATICA MEDICA
Ano de publicação:
2022
Tipo de documento:
Article
País de afiliação:
Reino Unido