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Understanding repeated non-attendance in health services: a pilot analysis of administrative data and full study protocol for a national retrospective cohort

INTRODUCTION: Understanding the causes of low engagement in healthcare is a pre-requisite for improving health services’ contribution to tackling health inequalities. Low engagement includes missing healthcare appointments. Serially (having a pattern of) missing general practice (GP) appointments ma...

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Autores principales: Williamson, Andrea E, Ellis, David A, Wilson, Philip, McQueenie, Ross, McConnachie, Alex
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5319001/
https://www.ncbi.nlm.nih.gov/pubmed/28196951
http://dx.doi.org/10.1136/bmjopen-2016-014120
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author Williamson, Andrea E
Ellis, David A
Wilson, Philip
McQueenie, Ross
McConnachie, Alex
author_facet Williamson, Andrea E
Ellis, David A
Wilson, Philip
McQueenie, Ross
McConnachie, Alex
author_sort Williamson, Andrea E
collection PubMed
description INTRODUCTION: Understanding the causes of low engagement in healthcare is a pre-requisite for improving health services’ contribution to tackling health inequalities. Low engagement includes missing healthcare appointments. Serially (having a pattern of) missing general practice (GP) appointments may provide a risk marker for vulnerability and poorer health outcomes. METHODS AND ANALYSIS: A proof of concept pilot using GP appointment data and a focus group with GPs informed the development of missed appointment categories: patients can be classified based on the number of appointments missed each year. The full study, using a retrospective cohort design, will link routine health service and education data to determine the relationship between GP appointment attendance, health outcomes, healthcare usage, preventive health activity and social circumstances taking a life course approach and using data from the whole journey in the National Health Service (NHS) healthcare. 172 practices will be recruited (∼900 000 patients) across Scotland. The statistical analysis will focus on 2 key areas: factors that predict patients who serially miss appointments, and serial missed appointments as a predictor of future patient outcomes. Regression models will help understand how missed appointment patterns are associated with patient and practice characteristics. We shall identify key factors associated with serial missed appointments and potential interactions that might predict them. ETHICS AND DISSEMINATION: The results of the project will inform debates concerning how best to reduce non-attendance and increase patient engagement within healthcare systems. Significant non-academic beneficiaries include governments, policymakers and medical practitioners. Results will be disseminated via a combination of academic outputs (papers, conferences), social media and through collaborative public health/policy fora.
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spelling pubmed-53190012017-02-27 Understanding repeated non-attendance in health services: a pilot analysis of administrative data and full study protocol for a national retrospective cohort Williamson, Andrea E Ellis, David A Wilson, Philip McQueenie, Ross McConnachie, Alex BMJ Open Public Health INTRODUCTION: Understanding the causes of low engagement in healthcare is a pre-requisite for improving health services’ contribution to tackling health inequalities. Low engagement includes missing healthcare appointments. Serially (having a pattern of) missing general practice (GP) appointments may provide a risk marker for vulnerability and poorer health outcomes. METHODS AND ANALYSIS: A proof of concept pilot using GP appointment data and a focus group with GPs informed the development of missed appointment categories: patients can be classified based on the number of appointments missed each year. The full study, using a retrospective cohort design, will link routine health service and education data to determine the relationship between GP appointment attendance, health outcomes, healthcare usage, preventive health activity and social circumstances taking a life course approach and using data from the whole journey in the National Health Service (NHS) healthcare. 172 practices will be recruited (∼900 000 patients) across Scotland. The statistical analysis will focus on 2 key areas: factors that predict patients who serially miss appointments, and serial missed appointments as a predictor of future patient outcomes. Regression models will help understand how missed appointment patterns are associated with patient and practice characteristics. We shall identify key factors associated with serial missed appointments and potential interactions that might predict them. ETHICS AND DISSEMINATION: The results of the project will inform debates concerning how best to reduce non-attendance and increase patient engagement within healthcare systems. Significant non-academic beneficiaries include governments, policymakers and medical practitioners. Results will be disseminated via a combination of academic outputs (papers, conferences), social media and through collaborative public health/policy fora. BMJ Publishing Group 2017-02-14 /pmc/articles/PMC5319001/ /pubmed/28196951 http://dx.doi.org/10.1136/bmjopen-2016-014120 Text en Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/ This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: http://creativecommons.org/licenses/by/4.0/
spellingShingle Public Health
Williamson, Andrea E
Ellis, David A
Wilson, Philip
McQueenie, Ross
McConnachie, Alex
Understanding repeated non-attendance in health services: a pilot analysis of administrative data and full study protocol for a national retrospective cohort
title Understanding repeated non-attendance in health services: a pilot analysis of administrative data and full study protocol for a national retrospective cohort
title_full Understanding repeated non-attendance in health services: a pilot analysis of administrative data and full study protocol for a national retrospective cohort
title_fullStr Understanding repeated non-attendance in health services: a pilot analysis of administrative data and full study protocol for a national retrospective cohort
title_full_unstemmed Understanding repeated non-attendance in health services: a pilot analysis of administrative data and full study protocol for a national retrospective cohort
title_short Understanding repeated non-attendance in health services: a pilot analysis of administrative data and full study protocol for a national retrospective cohort
title_sort understanding repeated non-attendance in health services: a pilot analysis of administrative data and full study protocol for a national retrospective cohort
topic Public Health
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5319001/
https://www.ncbi.nlm.nih.gov/pubmed/28196951
http://dx.doi.org/10.1136/bmjopen-2016-014120
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