More than 15% of the population will experience depression during their lifetime, making quality of services for these patients of critical importance.

We know there is a strong and enduring relationship between a person’s economic circumstances and their health and social status. We might therefore expect the recent growth of unemployment, poverty and inequality to translate into increased demand for health services.

However, the causal relationships between social disadvantage and health can be complex and it may take many years to see the full health consequences of economic blight.

One area where change may be more visible in the short term is through the rise in mental health problems, particularly depression associated with unemployment. Such problems are most likely to be seen in the first instance through management in primary care.

That acceleration in the use of these drugs raises some difficult questions

In our latest study we look at indicators linked to the prescription of antidepressants in primary care. Using national datasets, we analyse how changes in prescribing patterns are linked to key factors including patient characteristics, economic indicators and GP prescribing behaviour.

The study shows that between 1998 and 2012, the amount of antidepressants dispensed in the community each year rose by 25 million – from 15 million items in 1998, to 40 million in 2012. Almost half of that increase occurred in the four years between the 2008 financial crisis and 2012, the last year for which data are available.

Antidepressant medication is an intervention of proven value in treating depression (NICE, 2009). However, over-prescribing of antidepressants can have a negative impact on patient health and represents an inefficient use of health care resources. Therefore, it is important that health services seek to minimise instances of over, or under, prescribing of these important drugs.

Antidepressant prescribing model – interactive spreadsheet

The below interactive spreadsheet is aimed specifically at analysts in clinical commissioning groups, commissioning support units and GP practices for calculating predicted rates of antidepressant prescribing based on GP practice and local area characteristics.

The model is limited and you will need to know your GP practice code. It is not a tool designed to compare between GP practices. If you have any further queries regarding this model, please contact our research team.