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 may...
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| Format: | Article |
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BMJ Publishing Group
2017-02-01
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| Series: | BMJ Open |
| Online Access: | https://bmjopen.bmj.com/content/7/2/e014120.full |
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| author | Alex McConnachie Philip Wilson Ross McQueenie David A Ellis Andrea E Williamson |
| author_facet | Alex McConnachie Philip Wilson Ross McQueenie David A Ellis Andrea E Williamson |
| author_sort | Alex McConnachie |
| collection | DOAJ |
| 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 | Article |
| id | doaj-art-92afae877bb24134ab8e1cb98104b4d5 |
| institution | Kabale University |
| issn | 2044-6055 |
| language | English |
| publishDate | 2017-02-01 |
| publisher | BMJ Publishing Group |
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| series | BMJ Open |
| spelling | doaj-art-92afae877bb24134ab8e1cb98104b4d52025-02-08T14:30:09ZengBMJ Publishing GroupBMJ Open2044-60552017-02-017210.1136/bmjopen-2016-014120Understanding repeated non-attendance in health services: a pilot analysis of administrative data and full study protocol for a national retrospective cohortAlex McConnachie0Philip Wilson1Ross McQueenie2David A Ellis3Andrea E Williamson46 Robertson Centre for Biostatistics, University of Glasgow, Glasgow, UK3Centre for Rural Health, Institute of Applied Health Sciences University of Aberdeen, Aberdeen, UKPlace and Wellbeing Directorate, Public Health Scotland, Edinburgh, UKSchool of Management, University of Bath, Bath, UKGeneral Practice and Primary Care, School of Medicine, College of MVLS, University of Glasgow, Glasgow, UKIntroduction 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.https://bmjopen.bmj.com/content/7/2/e014120.full |
| spellingShingle | Alex McConnachie Philip Wilson Ross McQueenie David A Ellis Andrea E Williamson Understanding repeated non-attendance in health services: a pilot analysis of administrative data and full study protocol for a national retrospective cohort BMJ Open |
| 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 |
| url | https://bmjopen.bmj.com/content/7/2/e014120.full |
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