Evidence map›Paper›PMID 30074199›Full record

ArticleCurrent medical science2018

Implementation of Knowledge Management in Chinese Hospitals.

Qiao-Yuan Yan, Fei Xiang, Xiao-Xu Shi, Qin Zhu

Abstract read
PubMed Publisher
In one paragraph

Article in Current medical science, 2018. 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
1.1field-weighted citation impact, top 17% 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, 11 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
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  5. 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

4 authors at 1 institution in 1 country.

Qiao-Yuan YanUnion Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
Fei XiangSchool of Medicine and Health Management, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China. xiangfei@hust.edu.cn.
Xiao-Xu ShiSchool of Medicine and Health Management, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
Qin ZhuSchool of Nursing, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
Huazhong University of Science and Technology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The implementation of knowledge management (KM) in hospitals affects efficiency and outcomes of hospitals. However, few studies explored the implementation of KM in China. Twenty-two questions were designed concerning KM implementation status in over 50 hospitals. In order to understand the KM level and attitude to KM of the hospital's managers, a random sampling survey was conducted among 138 managers from 50 different scales of hospitals in 15 provinces of China. The survey showed that overall level of KM implementation in Chinese hospitals was still low and differed among different scales of hospitals (P<0.05, or P<0.01). In all the hospitals investigated, 63.8% did not implement KM yet, among which 46% even had not planned for that. 49.8% of the hospitals investigated had no training program about KM ever and the main source of hospital staff to get knowledge was internet. It suggested that hospital managers should make much more efforts to get to know and understand theories on KM, so that hospital KM could be promoted more rapidly.

Indexed as

HospitalsKnowledge ManagementChinaHealth Knowledge, Attitudes, PracticeHealth PersonnelHospital AdministrationHumansSurveys and Questionnaireshospital knowledge managementimplementationknowledge management

Identifiers

PMID30074199
OpenAlexW2802650065

What OpenQuestion holds

Textmetadata
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.