Publication details for Professor Felicity CallardWoodhead, C., Ashworth, M., Broadbent, B., Callard, F., Hotopf, M., Schofield, P., Soncul, M., Stewart, R.J. & Henderson, M.J. (2016). Cardiovascular disease treatment among patients with severe mental illness: a data linkage study between primary and secondary care. British Journal of General Practice 66(647): e374-e381.
- Publication type: Journal Article
- ISSN/ISBN: 0960-1643, 1478-5242
- DOI: 10.3399/bjgp16X685189
- Further publication details on publisher web site
- Durham Research Online (DRO) - may include full text
Author(s) from Durham
Background Suboptimal treatment of cardiovascular diseases (CVD) among patients with severe mental illness (SMI) may contribute to physical health disparities.
Aim To identify SMI characteristics associated with meeting CVD treatment and prevention guidelines.
Design and setting Population-based electronic health record database linkage between primary care and the sole provider of secondary mental health care services in south east London, UK.
Method Cardiovascular disease prevalence, risk factor recording, and Quality and Outcomes Framework (QOF) clinical target achievement were compared among 4056 primary care patients with SMI whose records were linked to secondary healthcare records and 270 669 patients without SMI who were not known to secondary care psychiatric services, using multivariate logistic regression modelling. Data available from secondary care records were then used to identify SMI characteristics associated with QOF clinical target achievement.
Results Patients with SMI and with coronary heart disease and heart failure experienced reduced prescribing of beta blockers and angiotensin-converting enzyme inhibitor/angiotensin receptor blockers (ACEI/ARB). A diagnosis of schizophrenia, being identified with any indicator of risk or illness severity, and being prescribed with depot injectable antipsychotic medication was associated with the lowest likelihood of prescribing.
Conclusion Linking primary and secondary care data allows the identification of patients with SMI most at risk of undertreatment for physical health problems.