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

Williamson, Andrea and Ellis, David Alexander and Wilson, Philip and McQueenie, Ross and McConnachie, Alex (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). ISSN 2044-6055

[thumbnail of s1-ln25332732-377715733-1939656818Hwf1935514148IdV-113300264225332732PDF_HI0001]
Preview
PDF (s1-ln25332732-377715733-1939656818Hwf1935514148IdV-113300264225332732PDF_HI0001)
s1_ln25332732_377715733_1939656818Hwf1935514148IdV_113300264225332732PDF_HI0001.pdf - Accepted Version
Available under License Creative Commons Attribution-NonCommercial.

Download (4MB)
[thumbnail of e014120.full]
Preview
PDF (e014120.full)
e014120.full.pdf - Published Version

Download (1MB)

Abstract

Introduction Understanding 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 analysis A 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 dissemination The 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.

Item Type:
Journal Article
Journal or Publication Title:
BMJ Open
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/2700
Subjects:
?? MEDICINE(ALL) ??
ID Code:
84156
Deposited By:
Deposited On:
23 Jan 2017 09:30
Refereed?:
Yes
Published?:
Published
Last Modified:
15 Sep 2023 00:32