Evidence map›Paper›PMID 40201767›Full record

ArticleRisk management and healthcare policy2025

Evaluation of Nosocomial Infection Management Efficiency Based on the Data Envelopment Analysis Model.

Jin Wang, Gan Wang, Chaoyi Qi

Abstract read
In one paragraph

Article in Risk management and healthcare policy, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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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

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2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

3 authors.

Jin Wang *Department of Healthcare-associated Infection Management, Qingdao Municipal Hospital, Qingdao, People's Republic of China.ORCID 0009-0008-8168-2643
Gan Wang *Shanghai Institute of Infectious Disease and Biosecurity, Fudan University, Shanghai, People's Republic of China.ORCID 0000-0002-3353-3829
Chaoyi QiDepartment of Anorectal Surgery, Taian Hospital of Traditional Chinese Medicine, Taian, People's Republic of China.ORCID 0009-0000-4373-4483

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: This study used data envelopment analysis (DEA), to assess relative efficiency of infection control in different clinical departments of the hospital for performance evaluation purposes. Methods: All wards and departments from January to December 2022 were selected as decision units, and five input and two output indicators related to infection prevention and control were determined using DEA. Pure technical efficiency was evaluated using the Banker-Charnes-Cooper (BCC) model. Results: In the study, the input-output indexes of the 27 clinical departments varied significantly. The average values of technical efficiency, pure technical efficiency, scale efficiency, and comprehensive benefit were 0.987, 0.995, 0.992, and 0.980, respectively. Among the 27 departments, 52% exhibited constant returns to scale, 44% showed increasing returns to scale, and 4% had decreasing returns to scale. In the context of DEA, 44% of the departments were classified as highly efficient, indicating that their input-output ratios had reached an optimal state. Meanwhile, 56% of the departments were identified as non-DEA efficient, suggesting that there was room for improvement in their input-output efficiency. Conclusion: The improvement of input-output indexes of non-DEA effective clinical departments was defined by the BCC model. Use of DMUs could improve the efficiency of inventory control by optimizing the allocation of inventory control resources and refining inventory control measures.

Indexed as

data envelopment analysisefficiencyhospital infectionperformance evaluation

Identifiers

PMID40201767
PMCPMC11977550

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