ArticleFrontiers in pharmacology2026
Descriptive analysis of prescription interception patterns: characterizing medication safety risks in an outpatient setting.
Article in Frontiers in pharmacology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Introduction: Prescription errors remain a significant challenge to medication safety in hospital settings. Forced Interception (FI) systems, which automatically flag and block potentially problematic prescriptions, serve as critical safeguards against adverse drug events. However, the specific characteristics and underlying causes of intercepted prescriptions, particularly in Chinese hospital contexts, require further investigation to inform targeted quality improvement strategies. This study aimed to analyze the characteristics and interception reasons of FI prescriptions in a hospital setting, with the goal of identifying patterns that could guide system upgrades, clinical training, and policy interventions. Methods: This study conducted a retrospective analysis of FI prescriptions intercepted by the hospital's electronic prescribing system. Prescriptions were analyzed for interception reasons, drug categories, specific medications, and prescribing department patterns. Data were collected and categorized to identify the most frequent issues and drug types involved in forced interceptions. Results: A total of FI prescriptions were analyzed. The most common interception reasons were "Treatment duration exceeded" (54.89%) and "Exceeding Dosage" (28.11%), together accounting for the majority of interceptions. Traditional Chinese medicine and central nervous system drugs were the most frequently intercepted drug categories. The top three intercepted medications were Duloxetine Hydrochloride Enteric Capsules (3.63%), Atorvastatin Calcium Tablets (3.11%), and Tandospirone Citrate Capsules (2.81%). Departmental analysis revealed distinct prescribing patterns: the cardiology department showed high interceptions for hyperlipidemia-related drugs, while the mental health department had numerous interceptions for long-term antidepressant and anxiolytic prescriptions. Discussion: The study suggests that targeted interventions, including upgrading electronic prescribing systems, department-specific training, and forming special review panels, are necessary to reduce prescription errors and improve medication safety. Future work should focus on multicenter studies and, as a longer-term direction, explore the potential of artificial intelligence for dynamic risk prediction to enhance the continuous optimization of medical quality.
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