title: Integrated electronic decision support increases cardiovascular disease risk assessment four fold in routine primary care practice.
abstract: BACKGROUND
  A decade of cardiovascular disease (CVD) risk-based guidelines, education programmes and widespread availability of paper-based risk prediction charts have not significantly influenced targeting of CVD risk management in New Zealand primary care practice. A web-based decision support system (PREDICT-CVD), integrated with primary care electronic medical record software was developed as one strategy to address this problem.
  
  
  METHODS
  A before-after audit of 3564 electronic patient records assessed the impact of electronic decision support on documentation of CVD risk and CVD risk factors. Participants were patients meeting national guideline criteria for CVD risk assessment, registered with 84/107 (78.5%) general practitioners (GPs) in one large primary care organization who used electronic patient medical records, and had PREDICT-CVD installed. The GPs received group education sessions, practice IT support and a small risk assessment payment. Four weeks of practice visit records were audited from 1 month after installation of PREDICT-CVD, and during the same 4-week period 12 months earlier.
  
  
  RESULTS
  Less than 3% of eligible patients had a documented CVD risk before PREDICT-CVD installation. This increased four-fold (RR=4.0; 95% confidence interval 2.4-6.5) after installation and documentation of all relevant CVD risk factors also increased significantly.
  
  
  CONCLUSIONS
  Documentation of CVD risk in primary care patient records in New Zealand is negligible, despite being recommended as a prerequisite for targeted treatment for over 10 years, suggesting that previous strategies were ineffective. We demonstrate that integrated electronic decision support can quadruple CVD risk assessment in just one cycle of patient visits.
authors.affiliation: School of Population Health, University of Auckland, Auckland, New Zealand. s.wells@auckland.ac.nz
authors.forename: Sue
authors.initials: S
authors.lastname: Wells
authors.forename: Sue
authors.initials: S
authors.lastname: Furness
authors.forename: Natasha
authors.initials: N
authors.lastname: Rafter
authors.forename: Elaine
authors.initials: E
authors.lastname: Horn
authors.forename: Robyn
authors.initials: R
authors.lastname: Whittaker
authors.forename: Alistair
authors.initials: A
authors.lastname: Stewart
authors.forename: Kate
authors.initials: K
authors.lastname: Moodabe
authors.forename: Paul
authors.initials: P
authors.lastname: Roseman
authors.forename: Vanessa
authors.initials: V
authors.lastname: Selak
authors.forename: Dale
authors.initials: D
authors.lastname: Bramley
authors.forename: Rod
authors.initials: R
authors.lastname: Jackson
mesh_terms: D002318:Cardiovascular Diseases / Q000453:epidemiology / Q000209:etiology* / Q000517:prevention & control; D020000:Decision Support Systems, Clinical / Q000706:statistics & numerical data; D003661:Decision Support Techniques; D005194:Family Practice; D006801:Humans; D020407:Internet; D008485:Medical Audit; D016347:Medical Records Systems, Computerized / Q000706:statistics & numerical data; D009520:New Zealand; D011320:Primary Health Care / Q000706:statistics & numerical data; D015397:Program Evaluation; D015203:Reproducibility of Results; D012189:Retrospective Studies; D018570:Risk Assessment; D012307:Risk Factors; D012984:Software; D013997:Time Factors