title: Using run charts for cardiovascular disease risk assessments in general practice.
abstract: INTRODUCTION Run charts are quality improvement tools. AIM To investigate the feasibility and acceptability of run charts displaying weekly cardiovascular disease (CVD) risk assessments in general practice and assess their impact on CVD risk assessments. METHODS A controlled non-randomised observational study in nine practices using run charts and nine control practices. We measured the weekly proportion of eligible patients with completed CVD risk assessments for 19 weeks before and after run charts were introduced into intervention practices. A random coefficients model determined changes in CVD risk assessment rates (slope) from pre- to post- intervention by aggregating and comparing intervention and control practices' mean slopes. We interviewed staff in intervention practices about their use of run charts. RESULTS Seven intervention practices used their run chart; six consistently plotting weekly data for >12 weeks and positioning charts in a highly visible place. Staff reported that charts were easy to use, a visual reminder for ongoing team efforts, and useful for measuring progress. There were no significant differences between study groups: the mean difference in pre- to post-run chart slope in the intervention group was 0.03% more CVD risk assessments per week; for the control group the mean difference was 0.07%. The between group difference was 0.04% per week (95% CI: -0.26 to 0.35, P = 0.77). DISCUSSION Run charts are feasible in everyday general practice and support team processes. There were no differences in CVD risk assessment between the two groups, likely due to national targets driving performance at the time of the study.
authors.affiliation: 1 Section of Epidemiology and Biostatistics, School of Population Health, University of Auckland, New Zealand.
authors.forename: Susan
authors.initials: S
authors.lastname: Wells
authors.affiliation: 2 Senior Lecturer, Royal College of Surgeons in Ireland.
authors.forename: Natasha
authors.initials: N
authors.lastname: Rafter
authors.affiliation: 3 Department of General Practice and Primary Health Care, School of Population Health, University of Auckland, New Zealand.
authors.forename: Kyle
authors.initials: K
authors.lastname: Eggleton
authors.affiliation: 4 Population Health Strategist/Analyst, Northland Primary Health Organisations.
authors.forename: Catherine
authors.initials: C
authors.lastname: Turner
authors.affiliation: 1 Section of Epidemiology and Biostatistics, School of Population Health, University of Auckland, New Zealand.
authors.forename: Ying
authors.initials: Y
authors.lastname: Huang
authors.affiliation: 5 Director, The National Institute for Health Innovation (NIHI), School of Population Health, University of Auckland, New Zealand.
authors.forename: Chris
authors.initials: C
authors.lastname: Bullen
mesh_terms: D001296:Audiovisual Aids; D002318:Cardiovascular Diseases / Q000175:diagnosis*; D058006:General Practice / Q000458:organization & administration*; D006801:Humans; D018570:Risk Assessment / Q000379:methods*