AIM: To describe the cardiovascular disease (CVD) risk factor status of approximately 18,000 patients profiled in routine primary care practice by PREDICT-CVD, a web-based clinical decision support program for assessing and managing CVD risk. METHODS: Between 2002 and 2005, 31,241 CVD risk assessments of 18,260 patients were undertaken in ProCare, a large primary care organisation in Auckland. RESULTS: Baseline risk assessments were completed for 10,374 (57%) men and 7886 (43%) women. The mean age was 56 years (range 17 to 94 years), Of those assessed, 11% were of Pacific and 7% of Maori ethnicity. Risk assessment was more likely in men under the age of 65 years. In the over 65 year age group, women were more likely to be risk assessed. The overall prevalence of diabetes and smoking in this cohort was 14% and 13% respectively. A history of a previous CVD event increased with age in both men and women. Above the age of 75 years, 36% reported a previous cardiovascular event, most commonly ischaemic heart disease. The patients assessed represented 6% of men and 4% of women in the enrolled ProCare population over 35 years of age. CONCLUSIONS: General practitioners and practice nurses using PREDICT-CVD targeted patients according to national guideline age and gender recommendations. PREDICT-CVD is a practical and effective tool for systematically generating standardised patient CVD risk factor profiles during routine primary care practice. When implemented widely, PREDICT will enable primary care organisations to monitor the CVD risk burden and management in their practice populations using a nationally standardised evidence-based approach.
AIM: To describe the cardiovascular disease (CVD) risk factor status of approximately 18,000 patients profiled in routine primary care practice by PREDICT-CVD, a web-based clinical decision support program for assessing and managing CVD risk. METHODS: Between 2002 and 2005, 31,241 CVD risk assessments of 18,260 patients were undertaken in ProCare, a large primary care organisation in Auckland. RESULTS: Baseline risk assessments were completed for 10,374 (57%) men and 7886 (43%) women. The mean age was 56 years (range 17 to 94 years), Of those assessed, 11% were of Pacific and 7% of Maori ethnicity. Risk assessment was more likely in men under the age of 65 years. In the over 65 year age group, women were more likely to be risk assessed. The overall prevalence of diabetes and smoking in this cohort was 14% and 13% respectively. A history of a previous CVD event increased with age in both men and women. Above the age of 75 years, 36% reported a previous cardiovascular event, most commonly ischaemic heart disease. The patients assessed represented 6% of men and 4% of women in the enrolled ProCare population over 35 years of age. CONCLUSIONS: General practitioners and practice nurses using PREDICT-CVD targeted patients according to national guideline age and gender recommendations. PREDICT-CVD is a practical and effective tool for systematically generating standardised patient CVD risk factor profiles during routine primary care practice. When implemented widely, PREDICT will enable primary care organisations to monitor the CVD risk burden and management in their practice populations using a nationally standardised evidence-based approach.
Authors: Miles C Benton; Rod A Lea; Donia Macartney-Coxson; Melanie A Carless; Harald H Göring; Claire Bellis; Michelle Hanna; David Eccles; Geoffrey K Chambers; Joanne E Curran; Jacquie L Harper; John Blangero; Lyn R Griffiths Journal: Am J Hum Genet Date: 2013-12-05 Impact factor: 11.025
Authors: Sheng-Chia Chung; Johan Sundström; Chris P Gale; Stefan James; John Deanfield; Lars Wallentin; Adam Timmis; Tomas Jernberg; Harry Hemingway Journal: BMJ Date: 2015-08-07
Authors: Sue Crengle; Janet Smylie; Margaret Kelaher; Michelle Lambert; Susan Reid; Joanne Luke; Ian Anderson; Jennie Harré Hindmarsh; Matire Harwood Journal: BMC Public Health Date: 2014-07-12 Impact factor: 3.295
Authors: Kjersti S Rabanal; Haakon E Meyer; Grethe S Tell; Jannicke Igland; Romana Pylypchuk; Suneela Mehta; Bernadette Kumar; Anne Karen Jenum; Randi M Selmer; Rod Jackson Journal: BMJ Open Date: 2017-12-06 Impact factor: 2.692