Antidepressant exposure, response and resistance in Severe Mental Illness – patterns and consequences
Project reference: RAS-24-2
Approval date: 29 May 2024
Lead organisation |
Principal Investigator |
---|---|
University of Edinburgh | Matthew Iveson |
Lay summary
This project aims to examine the pattern of antidepressant use within patients living with Severe Mental Illness, identifying changes in treatment that are indicative of response, non-response and resistance (e.g., frequent switching to different antidepressants). It also aims to examine the consequences of these changes in terms of the healthcare utilisation and mortality risk of individuals living with Severe Mental Illness. This will result in academic papers and lay reports, tools that add value to national prescribing data for other researchers, and a stakeholder workshop to co-design meaningful changes to prescribing policy.
Public benefit statement
Understanding the patterns and consequences of antidepressant use can improve the lives of those living with Severe Mental Illness (SMI) by helping them to find effective treatments quickly. Findings will help inform clinical decision making in these complex cases and minimize treatment burden on those living with SMI. Furthermore, we will produce tools that add value to national prescribing data, making it easier to examine treatment response and to track medication use in future research. We will run a stakeholder workshop, bringing together patients living with mental illness, medical professionals and healthcare policy makers to highlight medication-related challenges faced by patients and to co-design meaningful changes to policy.
Datasets used
- Scottish Morbidity Records (SMR) 00 - Outpatient Appointments and Attendances
- Scottish Morbidity Records (SMR) 01 - General Acute Inpatient and Day Case
- Scottish Morbidity Records (SMR) 04 - Mental Health Inpatient and Day Case
- Prescribing Information System (PIS)
- Scotland Accident and Emergency (A&E)
- National Records of Scotland (NRS) - Deaths Data