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Reducing Medical Admissions into Hospital through Optimising Medicines (REMAIN HOME) Study: protocol for a stepped-wedge, cluster-randomised trial
INTRODUCTION: A model of general practitioner (GP) and pharmacist collaboration in primary care may be an effective strategy to reduce medication-related problems and provide better support to patients after discharge. The aim of this study is to investigate whether a model of structured pharmacist...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Open
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5719661/ https://www.ncbi.nlm.nih.gov/pubmed/28408545 http://dx.doi.org/10.1136/bmjopen-2016-015301 |
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author | Foot, Holly Freeman, Christopher Hemming, Karla Scott, Ian Coombes, Ian D Williams, Ian D Connelly, Luke Whitty, Jennifer A Sturman, Nancy Kirsa, Sue Nicholson, Caroline Russell, Grant Kirkpatrick, Carl Cottrell, Neil |
author_facet | Foot, Holly Freeman, Christopher Hemming, Karla Scott, Ian Coombes, Ian D Williams, Ian D Connelly, Luke Whitty, Jennifer A Sturman, Nancy Kirsa, Sue Nicholson, Caroline Russell, Grant Kirkpatrick, Carl Cottrell, Neil |
author_sort | Foot, Holly |
collection | PubMed |
description | INTRODUCTION: A model of general practitioner (GP) and pharmacist collaboration in primary care may be an effective strategy to reduce medication-related problems and provide better support to patients after discharge. The aim of this study is to investigate whether a model of structured pharmacist and GP care reduces hospital readmissions in high-risk patients. METHODS AND ANALYSIS: This protocol details a stepped-wedge, cluster-randomised trial that will recruit participants over 9 months with a 12-month follow-up. There will be 14 clusters each representing a different general practice medical centre. A total of 2240 participants will be recruited from hospital who attend an enrolled medical centre, take five or more long-term medicines or whose reason for admission was related to heart failure or chronic obstructive pulmonary disease. The intervention is a multifaceted service, involving a pharmacist integrated into a medical centre to assist patients after hospitalisation. Participants will meet with the practice pharmacist and their GP after discharge to review and reconcile their medicines and discuss changes made in hospital. The pharmacist will follow-up with the participant and liaise with other health professionals involved in the participant’s care. The control will be usual care, which usually involves a patient self-organising a visit to their GP after hospital discharge. The primary outcome is the rate of unplanned, all-cause hospital readmissions over 12 months, which will be analysed using a mixed effects Poisson regression model with a random effect for cluster and a fixed effect to account for any temporal trend. A cost analysis will be undertaken to compare the healthcare costs associated with the intervention to those of usual care. ETHICS AND DISSEMINATION: The study has received ethical approval (HREC/16/QRBW/410). The study findings will be disseminated through peer-reviewed publications, conferences and reports to key stakeholders. TRIAL REGISTRATION NUMBER: ACTRN12616001627448 |
format | Online Article Text |
id | pubmed-5719661 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BMJ Open |
record_format | MEDLINE/PubMed |
spelling | pubmed-57196612017-12-08 Reducing Medical Admissions into Hospital through Optimising Medicines (REMAIN HOME) Study: protocol for a stepped-wedge, cluster-randomised trial Foot, Holly Freeman, Christopher Hemming, Karla Scott, Ian Coombes, Ian D Williams, Ian D Connelly, Luke Whitty, Jennifer A Sturman, Nancy Kirsa, Sue Nicholson, Caroline Russell, Grant Kirkpatrick, Carl Cottrell, Neil BMJ Open Health Services Research INTRODUCTION: A model of general practitioner (GP) and pharmacist collaboration in primary care may be an effective strategy to reduce medication-related problems and provide better support to patients after discharge. The aim of this study is to investigate whether a model of structured pharmacist and GP care reduces hospital readmissions in high-risk patients. METHODS AND ANALYSIS: This protocol details a stepped-wedge, cluster-randomised trial that will recruit participants over 9 months with a 12-month follow-up. There will be 14 clusters each representing a different general practice medical centre. A total of 2240 participants will be recruited from hospital who attend an enrolled medical centre, take five or more long-term medicines or whose reason for admission was related to heart failure or chronic obstructive pulmonary disease. The intervention is a multifaceted service, involving a pharmacist integrated into a medical centre to assist patients after hospitalisation. Participants will meet with the practice pharmacist and their GP after discharge to review and reconcile their medicines and discuss changes made in hospital. The pharmacist will follow-up with the participant and liaise with other health professionals involved in the participant’s care. The control will be usual care, which usually involves a patient self-organising a visit to their GP after hospital discharge. The primary outcome is the rate of unplanned, all-cause hospital readmissions over 12 months, which will be analysed using a mixed effects Poisson regression model with a random effect for cluster and a fixed effect to account for any temporal trend. A cost analysis will be undertaken to compare the healthcare costs associated with the intervention to those of usual care. ETHICS AND DISSEMINATION: The study has received ethical approval (HREC/16/QRBW/410). The study findings will be disseminated through peer-reviewed publications, conferences and reports to key stakeholders. TRIAL REGISTRATION NUMBER: ACTRN12616001627448 BMJ Open 2017-04-13 /pmc/articles/PMC5719661/ /pubmed/28408545 http://dx.doi.org/10.1136/bmjopen-2016-015301 Text en © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted. This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ |
spellingShingle | Health Services Research Foot, Holly Freeman, Christopher Hemming, Karla Scott, Ian Coombes, Ian D Williams, Ian D Connelly, Luke Whitty, Jennifer A Sturman, Nancy Kirsa, Sue Nicholson, Caroline Russell, Grant Kirkpatrick, Carl Cottrell, Neil Reducing Medical Admissions into Hospital through Optimising Medicines (REMAIN HOME) Study: protocol for a stepped-wedge, cluster-randomised trial |
title | Reducing Medical Admissions into Hospital through Optimising Medicines (REMAIN HOME) Study: protocol for a stepped-wedge, cluster-randomised trial |
title_full | Reducing Medical Admissions into Hospital through Optimising Medicines (REMAIN HOME) Study: protocol for a stepped-wedge, cluster-randomised trial |
title_fullStr | Reducing Medical Admissions into Hospital through Optimising Medicines (REMAIN HOME) Study: protocol for a stepped-wedge, cluster-randomised trial |
title_full_unstemmed | Reducing Medical Admissions into Hospital through Optimising Medicines (REMAIN HOME) Study: protocol for a stepped-wedge, cluster-randomised trial |
title_short | Reducing Medical Admissions into Hospital through Optimising Medicines (REMAIN HOME) Study: protocol for a stepped-wedge, cluster-randomised trial |
title_sort | reducing medical admissions into hospital through optimising medicines (remain home) study: protocol for a stepped-wedge, cluster-randomised trial |
topic | Health Services Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5719661/ https://www.ncbi.nlm.nih.gov/pubmed/28408545 http://dx.doi.org/10.1136/bmjopen-2016-015301 |
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