Identifying dementia outcomes in UK Biobank: a validation study of primary care, hospital admissions and mortality data

Journal article

Prospective, population-based studies that recruit participants in mid-life are valuable resources for dementia research. Follow-up in these studies is often through linkage to routinely-collected healthcare datasets. We investigated the accuracy of these datasets for dementia case ascertainment in a validation study using data from UK Biobank—an open access, population-based study of > 500,000 adults aged 40–69 years at recruitment in 2006–2010. From 17,198 UK Biobank participants recruited in Edinburgh, we identified those with ≥ 1 dementia code in their linked primary care, hospital admissions or mortality data and compared their coded diagnoses to clinical expert adjudication of their full-text medical record. We calculated the positive predictive value (PPV, the proportion of cases identified that were true positives) for all-cause dementia, Alzheimer’s disease and vascular dementia for each dataset alone and in combination, and explored algorithmic code combinations to improve PPV. Among 120 participants, PPVs for all-cause dementia were 86.8%, 87.3% and 80.0% for primary care, hospital admissions and mortality data respectively and 82.5% across all datasets. We identified three algorithms that balanced a high PPV with reasonable case ascertainment. For Alzheimer’s disease, PPVs were 74.1% for primary care, 68.2% for hospital admissions, 50.0% for mortality data and 71.4% in combination. PPV for vascular dementia was 43.8% across all sources. UK routinely-collected healthcare data can be used to identify all-cause dementia in prospective studies. PPVs for Alzheimer’s disease and vascular dementia are lower. Further research is required to explore the geographic generalisability of these findings.

Authors: Wilkinson, T; Schnier, C; Bush, K; Rannikmäe, K; Henshall, D

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Springer
• Journal: European Journal of Epidemiology
• Volume: 34
• Issue: 6
• Pages: 557-565
• Publication date: 2019-02-26
• Acceptance date: 2019-02-19
• DOI: 10.1007/s10654-019-00499-1
• EISSN: 1573-7284
• ISSN: 0393-2990
• Language: English
• Keywords: cohort studies; predictive value of tests; dementia; data accuracy; alzheimer disease; validation studies