Defining Mental Health Conditions Within Primary Care Data: A Validation Study With a Mixed Qualitative and Quantitative Approach

Overview

Journal J Eval Clin Pract

Specialties General Medicine
Health Services

Date 2024 Dec 11

PMID 39660636

Authors

Juan Carlos Bazo-Alvarez

Christina Avgerinou

Danielle Nimmons

Joseph F Hayes

David Osborn

Claudia Cooper

Kate Walters

Irene Petersen

Affiliations

Soon will be listed here.

Abstract

Objectives: To 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.

Methods: We 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.

Results: From 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.

Conclusions: We 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.

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