TY - JOUR
T1 - Understanding repeated non-attendance in health services
T2 - a pilot analysis of administrative data and full study protocol for a national retrospective cohort
AU - Williamson, Andrea E
AU - Ellis, David A
AU - Wilson, Philip
AU - McQueenie, Ross
AU - McConnachie, Alex
N1 - 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/.
PY - 2017/2/1
Y1 - 2017/2/1
N2 - 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.
AB - 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.
KW - Appointments and Schedules
KW - Focus Groups
KW - General Practice/statistics & numerical data
KW - Health Services/statistics & numerical data
KW - Humans
KW - Medical Record Linkage
KW - No-Show Patients/psychology
KW - Pilot Projects
KW - Proof of Concept Study
KW - Research Design
KW - Retrospective Studies
KW - Scotland
KW - Vulnerable Populations/statistics & numerical data
U2 - 10.1136/bmjopen-2016-014120
DO - 10.1136/bmjopen-2016-014120
M3 - Journal article
C2 - 28196951
SN - 2044-6055
VL - 7
JO - BMJ Open
JF - BMJ Open
IS - 2
M1 - e014120
ER -
