OBJECTIVE

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To optimize the prescription pre-review system in our hospital and evaluate its application effects.

METHODS

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Aiming at the problems of imperfect rule base and high false positive rate in the early operation of the system， optimization measures were taken， including improving the content of the rule base， adjusting the interception level and prompt mode， refining the working model of prescription review pharmacists， and strengthening clinical communication. A retrospective cohort study was conducted， with prescription data from June to December 2023 （before optimization） as the control group and June to December 2024 （after optimization） as the observation group. Through inter group comparative analysis， the actual effect of optimizing the prescription pre-approval system was evaluated.

RESULTS

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The prescription qualified rate increased from （82.51±4.04）% before optimization to （90.98±1.55）% after optimization； the false positive rate decreased from （20.87±1.64）% before optimization to （7.41±2.04）% after optimization. The monthly range of prescription qualified rate narrowed from 10.24% to 4.11%， and the coefficient of variation decreased from 4.92% to 1.73%. The monthly range of false positive rate slightly increased from 4.40% to 5.34%， the coefficient of variation rose from 8.32% to 26.18%.

CONCLUSIONS

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Through multi-dimensional optimizations of the prescription pre-review system in our hospital， its prescription review efficiency has been significantly enhanced， the quality of prescriptions has steadily improved， and the accuracy of reviews has notably improved.