Evidence map›Paper›PMID 40297139›Full record

ArticleFrontiers in pharmacology2025

Optimization and impact of an evidence-based pre-audit prescription decision system in primary healthcare settings.

Xiao-Hui Yue, Lei Yang, Jing-Jing Zhong, Hong-Mei Liu, Dan Wang, Xue Tao, Gao-Feng Zheng

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 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Observational
  2. Article
  3. Article
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

7 authors.

Xiao-Hui YueDepartment of Pharmacy, The People's Hospital of Jianyang City, Chengdu, China.
Lei YangDepartment of Pharmacy, The People's Hospital of Jianyang City, Chengdu, China.
Jing-Jing ZhongDepartment of Pharmacy, The People's Hospital of Jianyang City, Chengdu, China.
Hong-Mei LiuDepartment of Pharmacy, Sichuan Academy of Medical Sciences and Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.
Dan WangDepartment of Infection, Ziyang Central Hospital, Ziyang, China.
Xue TaoDepartment of Pharmacy, Sichuan Academy of Medical Sciences and Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.
Gao-Feng ZhengDepartment of Pharmacy, The People's Hospital of Jianyang City, Chengdu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Analyze the operation mode of the prescription pre-audit intelligent decision system in a county-level hospital, evaluate its intervention effects on outpatient and emergency operations, thus providing references for similar hospitals to carry out pre-audit intelligent decision system and promote rational drug use. Methods: Utilizing evidence-based approaches, system rule modifications have been refined and synergized with AI-driven decision-making analytics to examine the operational framework of pre-audit prescription decision system. Additionally, retrospectively analyze the types and levels of problems triggered by outpatient and emergency prescriptions from October 2022 to August 2023, as well as the rationality of prescriptions in the system. Results: According to the clinical operation of the hospital, problems triggered by unreasonable prescriptions have been finely classified into different levels according to the severity of prescription problems. From October 2022 to August 2023, the number of prescriptions triggering issues such as indications, dosage, special populations, compatibility, administration, and contraindications showed a decreasing trend compared with October 2022 before the intervention. For example, the number of prescriptions with unreasonable routes of administration decreased from 1,745 to 20, and the number of contraindicated prescriptions decreased from 1,399 to 16. The prescriptions triggering Level 5 alerts decreased from 5.609% to 1.793% and the prescription compliance rate increased from 92.20% to 95.98%. Conclusion: The prescription pre-audit intelligent decision system enhances patient safety and promotes rational drug use. However, the system requires fine-tuning and continuous improvement of the system rule library to effectively validate prescriptions and improve prescription accuracy. In the future, integrating big data, artificial intelligence and other technologies for secondary system development will be a model worthy of consideration. In addition, promoting this system to medical federation to establish a regional prescription review model will further promote the high-quality development of pharmaceutical services.

Indexed as

evidence-based practicemedication errorspre-prescription reviewprescription pre-audit intelligent decision systemrational drug use

Identifiers

PMID40297139
PMCPMC12034548

What Socratic holds

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LicenceCC BY
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Registered trials

None linked

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 Socratic graph.