ORIGINAL RESEARCH article
Front. Pharmacol.
Sec. Drugs Outcomes Research and Policies
Volume 16 - 2025 | doi: 10.3389/fphar.2025.1681245
This article is part of the Research TopicPharmacist and patient safety: Focus on drug safetyView all 6 articles
Evaluation of the Implementation Effect of Pre-audit of Inpatient Medical Orders: Based on the ORTCC Model
Provisionally accepted- 1Chengdu Third People's Hospital, Chengdu, China
- 2Chengdu Second People's Hospital, Chengdu, China
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Objective: This study aimed to evaluate the impact of implementing a pre-audit system for inpatient medical orders based on the ORTCC (Objectives, Rules, Training, Check, Culture) management model in a tertiary hospital in Chengdu, China. The primary goals were to enhance the pass rate of medical orders, reduce medication errors (MEs), and improve patient safety regarding medication administration. Methods: A pre-post intervention study was conducted using data from 2022 (pre-implementation) and 2024 (post-implementation). The Prescription Automatic Screening System (PASS) was employed to analyze medical orders, incorporating a "three review and three interception" model involving system alerts, pharmacist reviews, and dispensing checks. Key metrics included the qualification rate of medical orders, physician modification rates, and types of unreasonable orders. Statistical analysis was performed using SPSS (version 27), with chi-square tests for categorical data. Results: Following implementation, unreasonable medical orders significantly decreased from 540,000 in 2022 to 79,514 in 2024. The physician modification rate increased from 8.59% to 31.86% (P < 0.001), while the final qualification rate improved by 21.31% (P < 0.001). Modules with frequent issues (e.g., dosage, administration routes, drug compatibility) showed reduced error proportions (P < 0.05). Targeted interventions in high-risk departments (e.g., cardiovascular, ICU) further reduced errors (P < 0.05). Conclusions: The ORTCC-based pre-audit system significantly enhanced the rationality of medical orders, reduced MEs, and promoted safer medication practices. Continuous pharmacist training, dynamic rule updates, and advanced technologies are recommended to sustain improvements and address system limitations, such as false alerts.
Keywords: Adverse drug events, Medication Errors, Prescription automatic screening system, ORTCC model, Clinical decision support system
Received: 07 Aug 2025; Accepted: 22 Sep 2025.
Copyright: © 2025 Qin, Luo, Xi, Xu, Yang and He. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Xiaoli Qin, 549279916@qq.com
Qin He, yjkhq@sina.com
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