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

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Understanding repeated non-attendance in health services: pilot analysis of administrative data and full study protocol for a national retrospective cohort. / Williamson , Andrea; Ellis, David Alexander; Wilson, Philip et al.
In: BMJ Open, Vol. 7, No. 2, e014120, 14.02.2017.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Williamson , A, Ellis, DA, Wilson, P, McQueenie, R & McConnachie, A 2017, 'Understanding repeated non-attendance in health services: 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

APA

Williamson , A., Ellis, D. A., Wilson, P., McQueenie, R., & McConnachie, A. (2017). Understanding repeated non-attendance in health services: pilot analysis of administrative data and full study protocol for a national retrospective cohort. BMJ Open, 7(2), Article e014120. https://doi.org/10.1136/bmjopen-2016-014120

Vancouver

Williamson A, Ellis DA, Wilson P, McQueenie R, McConnachie A. Understanding repeated non-attendance in health services: pilot analysis of administrative data and full study protocol for a national retrospective cohort. BMJ Open. 2017 Feb 14;7(2):e014120. doi: 10.1136/bmjopen-2016-014120

Author

Williamson , Andrea ; Ellis, David Alexander ; Wilson, Philip et al. / Understanding repeated non-attendance in health services : pilot analysis of administrative data and full study protocol for a national retrospective cohort. In: BMJ Open. 2017 ; Vol. 7, No. 2.

Bibtex

@article{f673ed96bc3d4304af3d3139797bfa74,
title = "Understanding repeated non-attendance in health services: pilot analysis of administrative data and full study protocol for a national retrospective cohort",
abstract = "IntroductionUnderstanding the causes of low engagement in health care is a prerequisite for improving health services{\textquoteright} contribution to tackling health inequalities. Low engagement includes missing health care appointments. Serially (having a pattern of) missing general practice appointments may provide a risk marker for vulnerability and poorer health outcomes. Methods and analysisA proof of concept pilot utilising general practice (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 general practice appointment attendance, health outcomes, health care utilization, preventive health activity, and social circumstances taking a life course approach and using data from the whole journey in NHS health care. 172 practices will be recruited (approximately 900,000 patients) across Scotland. The statistical analysis will focus on two 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 health caresystems. Significant non-academic beneficiaries include governments, policy-makers and medical practitioners. Results will be disseminated via a combination of academic outputs (papers, conferences), social media, and through collaborative public health/policy fora. ",
author = "Andrea Williamson and Ellis, {David Alexander} and Philip Wilson and Ross McQueenie and Alex McConnachie",
year = "2017",
month = feb,
day = "14",
doi = "10.1136/bmjopen-2016-014120",
language = "English",
volume = "7",
journal = "BMJ Open",
issn = "2044-6055",
publisher = "BMJ Publishing Group Ltd",
number = "2",

}

RIS

TY - JOUR

T1 - Understanding repeated non-attendance in health services

T2 - pilot analysis of administrative data and full study protocol for a national retrospective cohort

AU - Williamson , Andrea

AU - Ellis, David Alexander

AU - Wilson, Philip

AU - McQueenie, Ross

AU - McConnachie, Alex

PY - 2017/2/14

Y1 - 2017/2/14

N2 - IntroductionUnderstanding the causes of low engagement in health care is a prerequisite for improving health services’ contribution to tackling health inequalities. Low engagement includes missing health care appointments. Serially (having a pattern of) missing general practice appointments may provide a risk marker for vulnerability and poorer health outcomes. Methods and analysisA proof of concept pilot utilising general practice (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 general practice appointment attendance, health outcomes, health care utilization, preventive health activity, and social circumstances taking a life course approach and using data from the whole journey in NHS health care. 172 practices will be recruited (approximately 900,000 patients) across Scotland. The statistical analysis will focus on two 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 health caresystems. Significant non-academic beneficiaries include governments, policy-makers and medical practitioners. Results will be disseminated via a combination of academic outputs (papers, conferences), social media, and through collaborative public health/policy fora.

AB - IntroductionUnderstanding the causes of low engagement in health care is a prerequisite for improving health services’ contribution to tackling health inequalities. Low engagement includes missing health care appointments. Serially (having a pattern of) missing general practice appointments may provide a risk marker for vulnerability and poorer health outcomes. Methods and analysisA proof of concept pilot utilising general practice (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 general practice appointment attendance, health outcomes, health care utilization, preventive health activity, and social circumstances taking a life course approach and using data from the whole journey in NHS health care. 172 practices will be recruited (approximately 900,000 patients) across Scotland. The statistical analysis will focus on two 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 health caresystems. Significant non-academic beneficiaries include governments, policy-makers and medical practitioners. Results will be disseminated via a combination of academic outputs (papers, conferences), social media, and through collaborative public health/policy fora.

U2 - 10.1136/bmjopen-2016-014120

DO - 10.1136/bmjopen-2016-014120

M3 - Journal article

VL - 7

JO - BMJ Open

JF - BMJ Open

SN - 2044-6055

IS - 2

M1 - e014120

ER -