Evidence map›Paper›PMID 36419040›Full record

ArticleBMC health services research2022

Establishment of a medical device adverse event management system for hospitals.

Jing Sun, Jin Pan, Yile Jin, Qian Zhang, Yingying Lv, Jingyi Feng

Open access · goldAbstract read
In one paragraph

Article in BMC health services research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
4.3field-weighted citation impact, top 6% of its field
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

5 citing papers in PubMed, 12 citations in OpenAlex.

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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 at 2 institutions in 1 country.

Jing SunKey Laboratory of Clinical Evaluation Technology for Medical Device of Zhejiang Province, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, People's Republic of China.
Jin PanDepartment of Clinical Engineering, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, People's Republic of China.
Yile JinKey Laboratory of Clinical Evaluation Technology for Medical Device of Zhejiang Province, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, People's Republic of China.
Qian ZhangDepartment of Clinical Engineering, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, People's Republic of China.
Yingying LvDepartment of Clinical Engineering, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, People's Republic of China.
Jingyi FengKey Laboratory of Clinical Evaluation Technology for Medical Device of Zhejiang Province, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, People's Republic of China. feng.jingyi@zju.edu.cn.
First Affiliated Hospital Zhejiang University · CNZhejiang University · CN

Funding

the Department of Education of Zhejiang Province General Scientific Research Project (No. Y201839759)
6 · The paper itself

Abstract

backgroundThe management of medical device adverse event (MDAE) is one of the most important aspects of improving medical quality and safety management. Nonetheless, hospitals still lack standardized and unified initiatives to improve MDAE management.

methodsThis study, thus, established a MDAE monitoring system on May 1 in 2011 for suspected adverse events and designed a hospital-based dynamic warning system, aiming to standardize the process of MDAE handling and provide real-time monitoring for MDAEs in a hospital. This system was used in the First Affiliated Hospital of Zhejiang University School of Medicine. Numbers and the compound growth rate of MDAE reports from 2010 to 2020 were compared to test the effectiveness of the MDAE monitoring system. Numbers of MDAE reported to the National Adverse Event Monitoring System were also compared over 2013 to 2020, due to the loss of data before 2013 after shutdown of the old system. Efficacy and usability of the hospital-based dynamic warning system was then verified by analyzing risk and warning levels of MDAEs in 2020. Descriptive statistics was used for data analysis in this study.

resultsResults showed that the compound annual growth rates of MDAE reports and those submitted to the National Adverse Event Monitoring System from 2013 to 2020 were 35.0% and 31.5%, respectively. A standardized management of MDAE with full participant, timely response and effective feedback was formed in the hospital by establishment of the MDAE system.

conclusionsThis system effectively improved the monitoring level of MDAEs, helping to improve early detection, early warning, and early intervention of risk of medical device. This study may provide suggestions for medical institutions to establish a MDAE monitoring system, and may promote development of medical quality and safety management for hospitals to some extent.

Indexed as

HospitalsMedicineData AnalysisEarly Intervention, EducationalHumansSafety ManagementContinuous quality improvementHealth policyManagementMedical device adverse eventRisk management

Identifiers

PMID36419040
PMCPMC9685867
OpenAlexW4309889987

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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 OpenQuestion graph.