Evidence map›Paper›PMID 41104328›Full record

ArticleFrontiers in pharmacology2025

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

Xiaoli Qin, Shanhong Luo, Heng Xi, Min Xu, Yujie Yang, Qin He

Abstract read
In one paragraph

Article in Frontiers in pharmacology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Xiaoli QinDepartment of Pharmacy, Affiliated Hospital of Southwest Jiaotong University, The Third People's Hospital of Chengdu, Chengdu, Sichuan, China.
Shanhong LuoDepartment of Pharmacy, Affiliated Hospital of Sichuan University, Chengdu Second People's Hospital, Chengdu, Sichuan, China.
Heng XiDepartment of Pharmacy, Affiliated Hospital of Southwest Jiaotong University, The Third People's Hospital of Chengdu, Chengdu, Sichuan, China.
Min XuDepartment of Pharmacy, Affiliated Hospital of Southwest Jiaotong University, The Third People's Hospital of Chengdu, Chengdu, Sichuan, China.
Yujie YangDepartment of Pharmacy, Affiliated Hospital of Southwest Jiaotong University, The Third People's Hospital of Chengdu, Chengdu, Sichuan, China.
Qin HeDepartment of Pharmacy, Affiliated Hospital of Southwest Jiaotong University, The Third People's Hospital of Chengdu, Chengdu, Sichuan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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% ( Conclusion: 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.

Indexed as

adverse drug eventsclinical decision support systemmedication errorsORTCC modelprescription automatic screening system

Identifiers

PMID41104328
PMCPMC12520964

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.