PDCA Cycle-Driven Whole-Chain Optimization of the Pre-Prescription Audit System: A Multidimensional Approach from Pharmacist Competency Development to Dynamic Rule Database Management

Background This study aimed to enhance the operational efficacy of the pre-prescription review system by applying the PDCA (Plan-Do-Check-Act) cycle management model, with the goal of improving prescription review accuracy, strengthening rational drug use management, and bolstering patient medication safety. Methods Based on the PDCA cycle framework, the fishbone diagram was used to systematically identify potential factors affecting pre-prescription review accuracy across seven dimensions: physicians, pharmacists, competent authorities, systems, drugs, regulations, and interdepartmental collaboration. The 80/20 rule was applied to prioritize key factors, and targeted improvement strategies were formulated using the 5W1H method. Outcomes were quantitatively evaluated. Results Six critical factors influencing review accuracy were pinpointed: delays in registering off-label drug use, insufficient pharmacist competency, untimely analysis of irrational prescriptions, inadequate rule adjustment procedures, unclear rule revision/approval processes, and limited system intelligence. Key interventions included centralized rule database management, core competency development for prescription review pharmacists, accurate documentation of irrational prescriptions at dispensing windows, and optimization of pharmacist workflows. Post-implementation, the proportion of irrational prescriptions identified by window pharmacists dropped from 0.11% to 0.008% (χ² = 249.019, P < 0.005). The system's post-review irrational task rate decreased from 19.30% to 10.61% (χ² = 5668.134, P < 0.005). Physician prescription modification rates rose from 60.36% to 70.52% (χ² = 616.086, P < 0.005), and overall prescription compliance improved from 93.28% to 97.94% (χ² = 5653.660, P < 0.005). Physician satisfaction with the system increased significantly from 9.6% to 40.4% (Z = -2.180, P < 0.05). Conclusion The PDCA cycle management model effectively optimizes the pre-prescription review system. Its core value lies in enhancing alert accuracy and system adaptability through multidimensional analysis and targeted interventions, while promoting system intelligence and informatization. This model offers a practical, replicable framework for improving pharmaceutical service quality and for the continuous, refined optimization of pre-prescription review processes.