Defining adolescent common mental disorders using electronic primary care data: a comparison with outcomes measured using the CIS-R

OBJECTIVE To compare the prevalence of common mental disorders (CMDs) derived from data held in primary care records with that measured using the revised Clinical Interview Schedule (CIS-R) in order to assess the potential robustness of findings based only on routinely collected data. DESIGN AND SETTING Comparison study using linkage between the Avon Longitudinal Study of Parents and Children (ALSPAC) and electronic primary care records. PARTICIPANTS We studied 1562 adolescents who had completed the CIS-R in ALSPAC at age 17-18 years and had linkage established to their primary care records. OUTCOME MEASURES Outcome measures from ALSPAC were whether or not an individual met International Classification of Diseases-10 criteria for a diagnosis of (1) a CMD or, specifically, (2) depression. Lists of Read codes corresponding to diagnoses, symptoms and treatments were used to create 12 definitions of CMD and depression alone using the primary care data. We calculated sensitivities and specificities of these, using CIS-R definitions as the reference standard. RESULTS Sensitivities ranged from 5.2% to 24.3% for depression and from 3.8% to 19.2% for CMD. The specificities of all definitions were above 98% for depression and above 96% for CMD.For both outcomes, the definition that included current diagnosis, treatment or symptoms identified the highest proportion of CIS-R cases. CONCLUSIONS Most individuals meeting case definitions for CMD based on primary care data also met CIS-R case definitions. Conversely many individuals identified as cases using the CIS-R had no evidence of CMD in their clinical records. This suggests that clinical databases are likely to yield underestimates of the burden of CMD in the population. However, clinical records appear to yield valid diagnoses which may be useful for studying risk factors and consequences of CMD. The greatest epidemiological value may be obtained when information is available from survey and clinical records.