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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

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Title: Understanding repeated non-attendance in health services: a pilot analysis of administrative data and full study protocol for a national retrospective cohort
Authors: Williamson, Andrea, Ellis, David A., Wilson, Philip, McQueenie, Ross, McConnachie, Alex
Contributors: University of Aberdeen.Other Applied Health Sciences, University of Aberdeen.Institute of Applied Health Sciences
Source: BMJ Open
BMJ Open, Vol 7, Iss 2 (2017)
Williamson, A E, Ellis, D A, Wilson, P, McQueenie, R & McConnachie, A 2017, ' Understanding repeated non-attendance in health services : a pilot analysis of administrative data and full study protocol for a national retrospective cohort ', BMJ Open, vol. 7, no. 2, e014120 . https://doi.org/10.1136/bmjopen-2016-014120
Publisher Information: BMJ, 2017.
Publication Year: 2017
Subject Terms: No-Show Patients, General Practice, Pilot Projects, R Medicine, Proof of Concept Study, Vulnerable Populations, Appointments and Schedules, 03 medical and health sciences, 0302 clinical medicine, SDG 3 - Good Health and Well-being, Journal Article, Humans, Retrospective Studies, Health Services/statistics & numerical data, Chief Scientist Office (CSO), Focus Groups, Health Services, CZH/4/1118, 3. Good health, No-Show Patients/psychology, General Practice/statistics & numerical data, Scotland, Research Design, Vulnerable Populations/statistics & numerical data, Medicine, Public Health, Medical Record Linkage
Description: IntroductionUnderstanding 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 analysisA 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 disseminationThe 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.
Document Type: Article
Other literature type
File Description: application/pdf
Language: English
ISSN: 2044-6055
DOI: 10.1136/bmjopen-2016-014120
Access URL: https://bmjopen.bmj.com/content/bmjopen/7/2/e014120.full.pdf
https://pubmed.ncbi.nlm.nih.gov/28196951
https://eprints.gla.ac.uk/135145/1/135145.pdf
https://doaj.org/article/92afae877bb24134ab8e1cb98104b4d5
https://eprints.lancs.ac.uk/id/eprint/84156
http://europepmc.org/articles/PMC5319001
https://aura.abdn.ac.uk/handle/2164/8214
https://core.ac.uk/display/74232407
https://bmjopen.bmj.com/lookup/doi/10.1136/bmjopen-2016-014120
http://eprints.gla.ac.uk/135145/
https://curis.ku.dk/portal/da/publications/understanding-repeated-nonattendance-in-health-services(15078b5f-0f56-49f8-a2a2-ca37ac6e5aef).html
https://eprints.lancs.ac.uk/id/eprint/84156/
Rights: CC BY
CC BY NC
Accession Number: edsair.doi.dedup.....0655c929e1e85c5073c021a6f8961b92
Database: OpenAIRE
Description
Abstract:IntroductionUnderstanding 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 analysisA 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 disseminationThe 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.
ISSN:20446055
DOI:10.1136/bmjopen-2016-014120