Evidence map›Paper›PMID 42328542›Full record

ArticleFrontiers in medicine2026

Enhancing healthcare quality and management: AI-driven smart consortium practices at Dapeng Medical Group, Shenzhen.

Xiaoxiao Quan, Junjie Pan

Abstract read
In one paragraph

Article in Frontiers in medicine, 2026. 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

2 authors.

Xiaoxiao QuanShenzhen Second People's Hospital (The First Affiliated Hospital of Shenzhen University), Shenzhen, China.
Junjie PanShenzhen Second People's Hospital (The First Affiliated Hospital of Shenzhen University), Shenzhen, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To evaluate the impact of smart healthcare consortium management practices, utilizing artificial intelligence (AI) to enhance healthcare service quality and operational efficiency at Dapeng Medical Group, Shenzhen. Design: A case study analysis of smart healthcare initiatives focusing on AI-driven improvements in patient care and management processes. Site: Dapeng Medical Group, a comprehensive medical institution in Shenzhen, China. Participants: Patients receiving care within the Dapeng Medical Group, along with healthcare providers and administrative staff involved in the implementation of the smart healthcare consortium. Methods: The initiative incorporated advanced technologies, including AI, cloud computing, and the Internet of Things (IoT), to streamline healthcare operations. Key performance metrics such as patient satisfaction, waiting times, diagnostic accuracy, and resource utilization were monitored to assess the effectiveness of the smart healthcare consortium. To clarify the effectiveness of Dapeng Medical Group's artificial intelligence technologies in smart healthcare consortium management, this study compares relevant management data from before AI adoption (2022) and after AI enablement (2025). Results: The implementation led to a 25% increase in patient satisfaction, 14% reduction in average waiting times and 34% reduction in the consultation duration, a 29% reduction in error rate of online pre-diagnostic precision. Conclusion: The integration of AI and smart technologies into healthcare management significantly improved service quality, operational efficiency, and patient outcomes at Dapeng Medical Group. These findings suggest that smart healthcare consortia can serve as a model for future healthcare innovations, ensuring high-quality, efficient, and patient-centered care.

Indexed as

artificial intelligenceconsortium managementinformatization constructionmedical service qualitysmart healthcare consortium

Identifiers

PMID42328542
PMCPMC13278856

What OpenQuestion holds

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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.