AbstractBackground: Investigating long-term antipsychotic polypharmacy is key to
unpacking the associations between serious mental illnesses (SMI) and
detrimental outcomes, such as premature death and frequent hospital
readmissions, observed in this population. However, existing research is
sparse and hampered by methodological problems such as examining small
and homogeneous samples and residual confounding.
1) To identify cases on long-term antipsychotic polypharmacy (≥ 6 months)
prescribing in South London and Maudsley electronic health records (EHR);
2) To identify factors that predict long-term antipsychotic polypharmacy
prescribing for SMI patients in secondary mental health care;
3) To investigate whether outcomes such as hospital readmission and
mortality are associated with long-term antipsychotic polypharmacy
prescribing in secondary mental health care.
Methods: Antipsychotic medication information was derived from the Clinical
Record Interactive Search (CRIS), a de-identified electronic patient records
system, for the period between 2007 and 2014. Data on mortality were
extracted using existing linkages between CRIS and death certification (Office
of National Statistics). Information about antipsychotic co-prescribing was
extracted using a bespoke algorithm. Multivariable logistic models were built
to investigate predictors of antipsychotic polypharmacy. To investigate the
impact of antipsychotic polypharmacy on hospital readmission and all-cause
mortality, I constructed multivariable Cox proportion hazard models. To test
the association between long-term antipsychotic polypharmacy and cause-specific mortality I used competing risk regression.
Implications: On a clinical level, this thesis provides an insight into factors
that can predict clinical decision-making regarding antipsychotic
polypharmacy prescribing in real-life clinical settings. On a patient level, the
findings highlight patient burden associated with this antipsychotic regimen. In
the wider treatment, service and policy context, the lack of patient benefit from
antipsychotic polypharmacy highlights the need for programmes that target
prescribers, to reduce antipsychotic polypharmacy.
|Date of Award||2017|
|Supervisor||Richard Hayes (Supervisor), James Maccabe (Supervisor) & Robert Stewart (Supervisor)|