TY - JOUR
T1 - Validation of UK Biobank data for mental health outcomes
T2 - a pilot study using secondary care electronic health records
AU - Li, Zhenpeng
AU - Kormilitzin, Andrey
AU - Fernandes, Marco
AU - Vaci, Nemanja
AU - Liu, Qiang
AU - Newby, Danielle
AU - Goodday, Sarah
AU - Smith, Tanya
AU - Nevado-Holgado, Alejo J.
AU - Winchester, Laura
N1 - The study was funded by the MRC Pathfinder Grant (MC_PC_17215); the National Institute for Health Research’s (NIHR) Oxford Health Biomedical Research Centre (BRC-1215-20005) and the Virtual Brain Cloud from European Commission (grant no. H2020SC1-DTH-2018-1). This work was supported by the UK Clinical Record Interactive Search (UK-CRIS) system funded by the National Institute for Health Research (NIHR) and the Medical Research Council, with the University of Oxford, using data and systems of the NIHR Oxford Health Biomedical Research Centre (BRC-1215-20005).
PY - 2022/4
Y1 - 2022/4
N2 - UK Biobank (UKB) is widely employed to investigate mental health disorders and related exposures; however, its applicability and relevance in a clinical setting and the assumptions required have not been sufficiently and systematically investigated. Here, we present the first validation study using secondary care mental health data with linkage to UKB from Oxford - Clinical Record Interactive Search (CRIS) focusing on comparison of demographic information, diagnostic outcome, medication record and cognitive test results, with missing data and the implied bias from both resources depicted. We applied a natural language processing model to extract information embedded in unstructured text from clinical notes and attachments. Using a contingency table we compared the demographic information recorded in UKB and CRIS. We calculated the positive predictive value (PPV, proportion of true positives cases detected) for mental health diagnosis and relevant medication. Amongst the cohort of 854 subjects, PPVs for any mental health diagnosis for dementia, depression, bipolar disorder and schizophrenia were 41.6%, and were 59.5%, 12.5%, 50.0% and 52.6%, respectively. Self-reported medication records in UKB had general PPV of 47.0%, with the prevalence of frequently prescribed medicines to each typical mental health disorder considerably different from the information provided by CRIS. UKB is highly multimodal, but with limited follow-up records, whereas CRIS offers a longitudinal high-resolution clinical picture with more than ten years of observations. The linkage of both datasets will reduce the self-report bias and synergistically augment diverse modalities into a unified resource to facilitate more robust research in mental health.
AB - UK Biobank (UKB) is widely employed to investigate mental health disorders and related exposures; however, its applicability and relevance in a clinical setting and the assumptions required have not been sufficiently and systematically investigated. Here, we present the first validation study using secondary care mental health data with linkage to UKB from Oxford - Clinical Record Interactive Search (CRIS) focusing on comparison of demographic information, diagnostic outcome, medication record and cognitive test results, with missing data and the implied bias from both resources depicted. We applied a natural language processing model to extract information embedded in unstructured text from clinical notes and attachments. Using a contingency table we compared the demographic information recorded in UKB and CRIS. We calculated the positive predictive value (PPV, proportion of true positives cases detected) for mental health diagnosis and relevant medication. Amongst the cohort of 854 subjects, PPVs for any mental health diagnosis for dementia, depression, bipolar disorder and schizophrenia were 41.6%, and were 59.5%, 12.5%, 50.0% and 52.6%, respectively. Self-reported medication records in UKB had general PPV of 47.0%, with the prevalence of frequently prescribed medicines to each typical mental health disorder considerably different from the information provided by CRIS. UKB is highly multimodal, but with limited follow-up records, whereas CRIS offers a longitudinal high-resolution clinical picture with more than ten years of observations. The linkage of both datasets will reduce the self-report bias and synergistically augment diverse modalities into a unified resource to facilitate more robust research in mental health.
KW - Data resource
KW - Linkage studies
KW - Mental health
KW - Neuro-epidemiology
KW - UK Biobank
KW - Validation study
U2 - 10.1016/j.ijmedinf.2022.104704
DO - 10.1016/j.ijmedinf.2022.104704
M3 - Article
C2 - 35168089
AN - SCOPUS:85124408917
SN - 1386-5056
VL - 160
JO - International Journal of Medical Informatics
JF - International Journal of Medical Informatics
M1 - 104704
ER -