Cardiovascular preventive pharmacotherapy stratified by predicted cardiovascular risk: a national data linkage study

2021 
AIMS Cardiovascular disease (CVD) risk management guided by predicted CVD risk is widely recommended internationally. This is the first study to examine CVD preventive pharmacotherapy in a whole-of-country primary prevention population, stratified by CVD risk. METHODS AND RESULTS Anonymized individual-level linkage of New Zealand administrative health and non-health data identified 2 250 201 individuals without atherosclerotic CVD, alive, and aged 30-74 years on 31 March 2013. We identified individuals with ≥1 dispensing by community pharmacies of blood pressure lowering (BPL) and/or lipid-lowering (LL) medications at baseline (1 October 2012-31 March 2013) and in 6-month periods between 1 April 2013 and 31 March 2016. Individuals were stratified using 5-year CVD risk equations specifically developed for application in administrative datasets. One-quarter of individuals had ≥5% 5-year risk (the current New Zealand guideline threshold for discussing preventive medications) and 5% met the ≥15% risk threshold for recommended dual therapy. By study end, dual therapy was dispensed to 2%, 18%, 34%, and 49% of individuals with <5%, 5-9%, 10-14%, and ≥15% 5-year risk, respectively. Among those dispensed baseline dual therapy, 83-89% across risk strata were still treated after 3 years. Dual therapy initiation during follow-up occurred among only 13% of high-risk individuals untreated at baseline. People without diabetes and those aged ≥65 years were more likely to remain untreated. CONCLUSION Cardiovascular disease primary preventive pharmacotherapy was strongly associated with predicted CVD risk and, once commenced, was generally continued. However, only half of high-risk individuals received recommended dual therapy and treatment initiation was modest. Individually linked administrative datasets can identify clinically relevant quality improvement opportunities for entire populations.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    17
    References
    2
    Citations
    NaN
    KQI
    []