• Juan Carlos Bazo-Alvarez, Christina Avgerinou, Danielle Nimmons, Joseph F Hayes, David Osborn, Claudia Cooper, Kate Walters, and Irene Petersen.
• Research Department of Primary Care and Population Health, University College London (UCL), London, UK.
• J Eval Clin Pract. 2025 Feb 1; 31 (1): e14256e14256.

ObjectivesTo validate codelists for defining a range of mental health (MH) conditions with primary care data, using a mixed qualitative and quantitative approach and without requiring external data.MethodsWe validated Read codelists, selecting and classifying them in three steps. The qualitative step included an in-depth revision of the codes by six doctors. Simultaneously, the quantitative step performed on UK primary care data included an exploratory factor analysis to cluster Read codes in MH conditions to obtain an independent classification. The statistical results informed the qualitative conclusions, generating a final selection and classification.ResultsFrom a preselected list of 2007 Read codes, a total of 1638 were selected by all doctors. Later, they agreed on classifying these codes into 12 categories of MH disorders. From the same preselected list, a total of 1364 were quantitatively selected. Using data from 497,649 persons who used these Read codes at least once, we performed the exploratory factor analysis, retaining five factors (five categories). Both classifications showed good correspondence, while discrepancies informed decisions on reclassification.ConclusionsWe produced a comprehensive set of medical codes lists for 12 MH conditions validated by a combination of clinical consensus panel and quantitative cluster analysis with cross-validation.© 2024 The Author(s). Journal of Evaluation in Clinical Practice published by John Wiley & Sons Ltd.

20 keywords...

hide…