Evidence map›Paper›PMID 39183270›Full record

ArticleBMC nursing2024

Knowledge, attitude, and practice toward value-based care among Chinese nurse: a cross-sectional study.

Yuhang Li, Yaxin Liu, Jin Wen

Erratum issuedAbstract read
In one paragraph

Article in BMC nursing, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Yuhang Li *Institute of Hospital Management, West China Hospital, Sichuan University, Chengdu, 610041, China.
Yaxin Liu *Institute of Hospital Management, West China Hospital, Sichuan University, Chengdu, 610041, China.
Jin WenWest China School of Public Health, Sichuan University / West China Fourth Hospital, Sichuan University, Chengdu, 610041, China. huaxiwenjin@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundValue-Based Care (VBC) is increasingly recognized as a pivotal approach in healthcare, aiming to improve patient outcomes while optimizing costs. Understanding the knowledge, attitudes, and practices (KAP) of nurses towards VBC is crucial for its successful implementation.

methodsThis study adopts a multi-center, online, cross-sectional design to survey registered nurses across China to evaluate their KAP related to VBC.The survey was disseminated through the platform Wenjuanxing (SoJump) targeting professional nursing groups, utilizing a structured questionnaire on a five-point Likert scale.

resultThe survey received a total of 1,825 valid responses from 82 hospitals across 18 provinces, with the majority coming from female nurses (95.02%), and a significant portion of the nurses having 10-19 years of clinical experience. 41.32% of the participants indicated they were familiar with Value-Based Care (VBC), and 68% expressed a willingness to participate in relevant training. There was a significant difference (p < 0.001) in the reported incidence of low-value services between nurses' self-reports and their reports about colleagues, with a lower incidence reported by nurses themselves. The highest incidence of low-value services reported by nurses themselves was "Unnecessary Lab testing" (6.52%), while the highest incidence reported by nurses about their colleagues was "Insufficient Treatment" (12.75%).

conclusionThis survey showed that Chinese nurses have a relatively low level of understanding of value-based healthcare, and that low-value medical practices may be prevalent in China.

Indexed as

AttitudesChinese nursesCross-sectional studyHealthcareKnowledgePracticesValue-based care

Identifiers

PMID39183270
PMCPMC11346283

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.