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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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2017
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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. |
format | Online Article Text |
id | pubmed-5319001 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
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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