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Predictors of long-term (≥ 6 months) antipsychotic polypharmacy prescribing in secondary mental healthcare
INTRODUCTION: The predictors of long-term antipsychotic polypharmacy (APP) initiation are poorly understood. Existing research has been hampered by residual confounding, failure to exclude cross-titration, and difficulties in separating the timing of predictors and APP administration. MATERIALS AND...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Science Publisher B. V
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4922621/ https://www.ncbi.nlm.nih.gov/pubmed/27091655 http://dx.doi.org/10.1016/j.schres.2016.04.010 |
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author | Kadra, Giouliana Stewart, Robert Shetty, Hitesh Downs, Johnny MacCabe, James H. Taylor, David Hayes, Richard D. |
author_facet | Kadra, Giouliana Stewart, Robert Shetty, Hitesh Downs, Johnny MacCabe, James H. Taylor, David Hayes, Richard D. |
author_sort | Kadra, Giouliana |
collection | PubMed |
description | INTRODUCTION: The predictors of long-term antipsychotic polypharmacy (APP) initiation are poorly understood. Existing research has been hampered by residual confounding, failure to exclude cross-titration, and difficulties in separating the timing of predictors and APP administration. MATERIALS AND METHODS: Using data from the South London and Maudsley (SLaM) case register, we identified all adult patients with serious mental illness (SMI) who were receiving care between 1st July 2011 and 30th June 2012. Exposures measured between 1st July and 31st December 2011 included socio-demographic, socioeconomic, clinical and service use characteristics. We then determined if long-term APP (six or more months) had been initiated between 1st January and 30th June 2012. Multivariable logistic regression models, adjusted for socio-demographic and socioeconomic factors, were built to investigate the associations between the above factors and the initiation of long-term APP. RESULTS: We identified 6857 adults with SMI receiving SLaM care, of whom 115 (1.7%) were newly prescribed long-term APP. In the adjusted models, predictors of long-term APP initiation included: symptoms (severity of hallucinations and/or delusions), previous treatments (clozapine and long-acting injectable antipsychotic agents), service use (more contact with outpatient services, community treatment order receipt), social factors (higher area-level deprivation, homelessness) and socio-demographic status (younger age, not in a relationship). CONCLUSION: Our findings highlight that certain patient groups are at an increased risk for long-term APP initiation. Identifying these groups earlier in their treatment could encourage clinicians to employ a broader range of interventions in addition to pharmacotherapy to reduce the risk of APP prescribing. |
format | Online Article Text |
id | pubmed-4922621 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Elsevier Science Publisher B. V |
record_format | MEDLINE/PubMed |
spelling | pubmed-49226212016-07-12 Predictors of long-term (≥ 6 months) antipsychotic polypharmacy prescribing in secondary mental healthcare Kadra, Giouliana Stewart, Robert Shetty, Hitesh Downs, Johnny MacCabe, James H. Taylor, David Hayes, Richard D. Schizophr Res Article INTRODUCTION: The predictors of long-term antipsychotic polypharmacy (APP) initiation are poorly understood. Existing research has been hampered by residual confounding, failure to exclude cross-titration, and difficulties in separating the timing of predictors and APP administration. MATERIALS AND METHODS: Using data from the South London and Maudsley (SLaM) case register, we identified all adult patients with serious mental illness (SMI) who were receiving care between 1st July 2011 and 30th June 2012. Exposures measured between 1st July and 31st December 2011 included socio-demographic, socioeconomic, clinical and service use characteristics. We then determined if long-term APP (six or more months) had been initiated between 1st January and 30th June 2012. Multivariable logistic regression models, adjusted for socio-demographic and socioeconomic factors, were built to investigate the associations between the above factors and the initiation of long-term APP. RESULTS: We identified 6857 adults with SMI receiving SLaM care, of whom 115 (1.7%) were newly prescribed long-term APP. In the adjusted models, predictors of long-term APP initiation included: symptoms (severity of hallucinations and/or delusions), previous treatments (clozapine and long-acting injectable antipsychotic agents), service use (more contact with outpatient services, community treatment order receipt), social factors (higher area-level deprivation, homelessness) and socio-demographic status (younger age, not in a relationship). CONCLUSION: Our findings highlight that certain patient groups are at an increased risk for long-term APP initiation. Identifying these groups earlier in their treatment could encourage clinicians to employ a broader range of interventions in addition to pharmacotherapy to reduce the risk of APP prescribing. Elsevier Science Publisher B. V 2016-07 /pmc/articles/PMC4922621/ /pubmed/27091655 http://dx.doi.org/10.1016/j.schres.2016.04.010 Text en © 2016 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Kadra, Giouliana Stewart, Robert Shetty, Hitesh Downs, Johnny MacCabe, James H. Taylor, David Hayes, Richard D. Predictors of long-term (≥ 6 months) antipsychotic polypharmacy prescribing in secondary mental healthcare |
title | Predictors of long-term (≥ 6 months) antipsychotic polypharmacy prescribing in secondary mental healthcare |
title_full | Predictors of long-term (≥ 6 months) antipsychotic polypharmacy prescribing in secondary mental healthcare |
title_fullStr | Predictors of long-term (≥ 6 months) antipsychotic polypharmacy prescribing in secondary mental healthcare |
title_full_unstemmed | Predictors of long-term (≥ 6 months) antipsychotic polypharmacy prescribing in secondary mental healthcare |
title_short | Predictors of long-term (≥ 6 months) antipsychotic polypharmacy prescribing in secondary mental healthcare |
title_sort | predictors of long-term (≥ 6 months) antipsychotic polypharmacy prescribing in secondary mental healthcare |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4922621/ https://www.ncbi.nlm.nih.gov/pubmed/27091655 http://dx.doi.org/10.1016/j.schres.2016.04.010 |
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