Abstract
PurposeThe purpose of the study is to assess the validity of codes or algorithms used to identify dementia in UK electronic health record (EHR) primary care and hospitalisation databases.MethodsRelevant studies were identified by searching the MEDLINE/EMBASE databases from inception to June 2018, hand‐searching reference lists, and consulting experts. The search strategy included synonyms for “Dementia”, “Europe”, and “EHR”. Studies were included if they validated dementia diagnoses in UK primary care or hospitalisation databases, irrespective of validation method used. The Quality Assessment for Diagnostic Accuracy Studies‐2 (QUADAS‐2) tool was used to assess risk of bias.ResultsFrom 1469 unique records, 14 relevant studies were included. Thirteen validated individual diagnoses against a reference standard, reporting high estimates of validity. Most reported only the positive predictive value (PPV), with estimates ranging between 0.09 and 1.0 and 0.62 and 0.85 in primary care and hospitalisation databases, respectively. One study performed a rate comparison, indicating good generalisability of dementia diagnoses in The Health Improvement Network (THIN) database to the UK population. Studies were of low methodological quality. As studies were not comparable, no summary validity estimates were produced.ConclusionWhile heterogenous across studies, reported validity estimates were generally high. However, the credibility of these estimates is limited by the methodological quality of studies, primarily resulting from insufficient blinding of researchers interpreting the reference test. Inadequate reporting, particularly of the specific codes validated, hindered comparison of estimates across studies. Future validation studies should make use of more robust reference tests, follow established reporting guidelines, and calculate all measures of validity.
Highlights
The burden of dementia and its associated health and societal costs are projected to have major global impact as populations continue to age over the few decades, despite the recent decline in age‐ specific dementia incidence.[1]
With only one‐third of cases being due to potentially modifiable risk factors and in the absence of effective treatments,[2] there is an urgent need for adequately powered studies seeking to identify dementia determinants
We found an absence of high‐quality published literature examining the validity of different codes/algorithms for each dementia type in UK primary care and hospitalisation electronic health records (EHR) databases
Summary
The burden of dementia and its associated health and societal costs are projected to have major global impact as populations continue to age over the few decades, despite the recent decline in age‐ specific dementia incidence.[1]. The advantages associated with the use of EHR data rely on the codes/algorithms used to identify dementia cases in these databases being valid. Several large UK‐based EHR databases exist and are regularly used for research purposes, including the Clinical Practice Research Datalink (CPRD, formerly known as the GPRD), which as of 2013 covered ~7% of the UK population,[3] and the Hospital Episode Statistics Admitted Patient Care (HES‐APC) database, which contains details on admissions to all National Health Service Trusts in England.[4] Previous reviews have established the generally high validity of codes and algorithms for multiple conditions in a single database, such as the CPRD.[5] no published systematic review has examined the validity of codes/algorithms used to identify dementia cases across all UK EHR databases
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