Evaluation of the implementation effect of pre-audit of inpatient medical orders: based on the ORTCC model

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.

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.

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).

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.