Many international guidelines and national health policies for the prevention of cardiovascular disease (CVD) advocate using estimates of patients’ absolute CVD risk, generated from multifactor risk prediction equations, to inform…
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Ninety percent of New Zealanders who are in the NZ Guidelines target group have had a CVD risk assessment. There is little information on how this information is used by doctors and their patients. The decision to start cholesterol lowering medications (statins) might be driven mainly by cholesterol levels, or (as NZ Guidelines suggest) by a comprehensive assessment of the person’s overall risk. This paper suggests that the latter approach is more likely, but that the decision process is complex and takes into account other factors.
Cardiovascular disease (CVD) risk assessment is commonly recommended in guidelines, but there is uncertainty about how clinicians use this information. Our objective was to understand how New Zealand primary care clinicians use CVD risk assessment estimates to inform new statin prescribing.
We used a cohort of patients seen in primary care who have had a CVD risk estimated on the basis of a New Zealand modified Framingham risk equation. These patients were linked to national pharmaceutical dispensing records to determine new statin use in the following six months. Regression discontinuity and logistic regression analysis, and graphical approaches, were used to explore associations between estimated CVD risk and primary clinicians’ decisions to initiate statin treatment.
There were 76,571 patients aged 35 to 75 who were not on a statin, had a first recorded CVD risk assessment between July 2007 and June 2011, and for whom national guidelines recommended management on the basis of estimated CVD risk. Statin dispensing increased with increasing CVD risk. There was no evidence of sudden jumps in the proportions of patients dispensed statins at guideline recommended treatment threshold values of 15% and 20% CVD risk (P=0.314 and 0.731). A logistic regression model using the CVD risk score predicted statin initiation better than models using lipid measures (Area Under the Curve 0.725 versus 0.682). However, further modelling and graphical analysis suggested clinicians were using a range of other information to inform the initiation of statins.
New Zealand primary care clinicians’ statin prescribing decisions appear to be influenced by patients’ predicted CVD risk. However, other factors are associated with increased statin dispensing independent of CVD risk score.