Abstract
BackgroundOver the past decade, antidepressant prescriptions have increased in European countries and the United States, partly due to an increase in the number of new cases of mental illness. This paper demonstrates an innovative approach to the classification of population level change in mental health status, using administrative data for a large sample of the Scottish population. We aimed to identify groups of individuals with similar patterns of change in pattern of prescribing, validate these groups by comparison with other indicators of mental illness, and characterise the population most at risk of increasing mental ill health.MethodsNational Health Service (NHS) prescription data were linked to the Scottish Longitudinal Study (SLS), a 5.3% sample of the Scottish population (N = 151,418). Antidepressant prescription status over the previous 6 months was recorded for every month for which data were available (January 2009–December 2014), and sequence dissimilarity was computed by optimal matching. Hierarchical clustering was used to create groups of participants who had similar patterns of change, with multi-level logistic regression used to understand group membership.ResultsFive distinct prescription pattern groups were observed, indicating: no prescriptions (76%), occasional prescriptions (10%), continuation of prior use of prescriptions (8%), a new course of prescriptions started (4%) or ceased taking prescriptions (3%). Young, white, female participants, of low social grade, residing in socially deprived neighbourhoods, living alone, being separated/divorced or out of the labour force, were more likely to be in the group that started a new course of antidepressant prescriptions.ConclusionsThe use of sequence analysis for classifying individual antidepressant trajectories offers a novel approach for capturing population-level changes in mental health risk. By classifying individuals into groups based on their anti-depressant medication use we can better identify how over time, mental health is associated with individual risk factors and contextual factors at the local level and the macro political and economic scale.
Highlights
Over the past decade, antidepressant prescriptions have increased in European countries and the United States, partly due to an increase in the number of new cases of mental illness
To add data on National Health Service (NHS) service use and prescriptions for mental health conditions for 2009–2014 to the Scottish Longitudinal Study (SLS) sample, SLS staff used the SLS/CHI (Community Health Index – population index used for healthcare purposes) number. (This is based on the Community Health Index; an administrative index used for healthcare purposes)
We classified the individual sequences into five antidepressant prescription groups; these groups are visualised as the proportion of participants prescribed antidepressants for each month in the time period (Fig. 1)
Summary
Antidepressant prescriptions have increased in European countries and the United States, partly due to an increase in the number of new cases of mental illness. In Scotland, over a 12 month period during 2012/2013, the number of antidepressant items recorded was 5.2 million, dispensed to 747,158 patients in Scotland, costing £29.5 million; a 52% increase from 10 years previously [6] At this time, 9% of the Scottish population reported at least two depressive symptoms [7] and 12% took an antidepressant every day. Population-level administrative data linked with health services information on prescriptions for mental illness offer potential to understand predictors of mental illness over time Ecological studies have captured change in mental health using fixed effects models of suicide rates, self-report and antidepressant use [8,9,10]. Repeated cross-sectional analysis of self-reported mental illness (e.g. General Health Questionnaire) are common, measures were analysed dichotomously [11, 12] These methods make it difficult to distinguish trajectories of mental illness among groups in the population. Studies using individual-level data on antidepressant use usually concentrate on ‘any antidepressant use’ [13] or ‘chronic’ use [14], but not on occasional, increasing or decreasing use, which are harder to define, but may be more indicative of change in population mental health
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