Evidence mapPaperPMID 38148352Full record

ArticleJournal of medical systems2023

The Application of Computer Technology to Clinical Practice Guideline Implementation: A Scoping Review.

Xu-Hui Li, Jian-Peng Liao, Mu-Kun Chen, Kuang Gao, Yong-Bo Wang, Si-Yu Yan, Qiao Huang, Yun-Yun Wang, Yue-Xian Shi, Wen-Bin Hu and 1 more

Abstract readScoping Review
PubMed Publisher
In one paragraph

Article in Journal of medical systems, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

11 authors.

Xu-Hui Li *Center for Evidence-Based and Translational Medicine, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China.
Jian-Peng Liao *School of Public Health, Wuhan University, Wuhan, 430071, China.
Mu-Kun ChenSchool of Computer Science, Wuhan University, Wuhan, 430071, China.
Kuang GaoSchool of Computer Science, Wuhan University, Wuhan, 430071, China.
Yong-Bo WangCenter for Evidence-Based and Translational Medicine, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China.
Si-Yu YanCenter for Evidence-Based and Translational Medicine, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China.
Qiao HuangCenter for Evidence-Based and Translational Medicine, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China.
Yun-Yun WangCenter for Evidence-Based and Translational Medicine, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China.
Yue-Xian ShiSchool of Nursing, Peking University, Beijing, 100191, China.
Wen-Bin HuSchool of Computer Science, Wuhan University, Wuhan, 430071, China. hwb@whu.edu.cn.
Ying-Hui JinCenter for Evidence-Based and Translational Medicine, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China. jinyinghui0301@163.com.

Funding

Fundamental Research Funds for the Central Universities 2042022kf1213National Natural Science Foundation of China 82174230
6 · The paper itself

Abstract

Implementation of clinical practice guidelines (CPG) is a complex and challenging task. Computer technology, including artificial intelligence (AI), has been explored to promote the CPG implementation. This study has reviewed the main domains where computer technology and AI has been applied to CPG implementation. PubMed, Embase, Web of science, the Cochrane Library, China National Knowledge Infrastructure database, WanFang DATA, VIP database, and China Biology Medicine disc database were searched from inception to December 2021. Studies involving the utilization of computer technology and AI to promote the implementation of CPGs were eligible for review. A total of 10429 published articles were identified, 117 met the inclusion criteria. 21 (17.9%) focused on the utilization of AI techniques to classify or extract the relative content of CPGs, such as recommendation sentence, condition-action sentences. 47 (40.2%) focused on the utilization of computer technology to represent guideline knowledge to make it understandable by computer. 15 (12.8%) focused on the utilization of AI techniques to verify the relative content of CPGs, such as conciliation of multiple single-disease guidelines for comorbid patients. 34 (29.1%) focused on the utilization of AI techniques to integrate guideline knowledge into different resources, such as clinical decision support systems. We conclude that the application of computer technology and AI to CPG implementation mainly concentrated on the guideline content classification and extraction, guideline knowledge representation, guideline knowledge verification, and guideline knowledge integration. The AI methods used for guideline content classification and extraction were pattern-based algorithm and machine learning. In guideline knowledge representation, guideline knowledge verification, and guideline knowledge integration, computer techniques of knowledge representation were the most used.

Indexed as

Artificial IntelligenceDecision Support Systems, ClinicalAlgorithmsComputersHumansTechnologyArtificial intelligenceClinical practice guidelineComputer technologyImplementationReview

Identifiers

PMID38148352

What Socratic 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 Socratic graph.