Introduction

Secondary prevention of cardiovascular disease (CVD) requires strict adherence to evidence‑based medication regimens to reduce recurrent events. Prescription errors or irrational drug use can compromise outcomes, highlighting the need for effective pre-prescription review strategies.

Aim

This study aimed to assess the application of pre-prescription review of suspicious data via an intelligent supervision platform based on evidence-based medicine (EBM) for secondary prevention of CVD.

Material and methods

One hundred and forty CVD patients requiring secondary prevention were randomized to a control group (traditional prescription review) and an observation group (EBM-based intelligent platform pre-review). We compared between-group differences in medication appropriateness, rational drug use rates, prescription modification rates, adverse cardiovascular events, and patient satisfaction before and after review.

Results

Post-review assessments revealed significant improvements in both groups across all measured outcomes, including medication appropriateness, rational drug use rates, and patient satisfaction, alongside reductions in Medication Appropriateness Index inappropriateness rates, prescription modifications, and cardiovascular adverse events. However, the observation group demonstrated markedly superior outcomes compared to traditional review: higher medication appropriateness and rationality scores, greater adherence to rational drug use standards, and significantly lower rates of prescription modifications and adverse events. Patient satisfaction scores were also higher in the observation group, confirming the platform’s clinical and operational advantages.

Conclusions

EBM‑based intelligent supervision platform pre‑review markedly enhances medication appropriateness and rational drug use in CVD secondary prevention, reduces prescription modifications and adverse cardiovascular events, and improves patient satisfaction, offering clear clinical and operational benefits over traditional review methods.