Evidence map›Paper›PMID 38338290›Full record

ArticleHealthcare (Basel, Switzerland)2024

A Study on Decision-Making for Improving Service Efficiency in Hospitals.

Su-Wen Huang, Shao-Jen Weng, Shyue-Yow Chiou, Thi-Duong Nguyen, Chih-Hao Chen, Shih-Chia Liu, Yao-Te Tsai

Open access · goldAbstract read
In one paragraph

Article in Healthcare (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
8.2field-weighted citation impact, top 2% 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

6 citing papers in PubMed, 11 citations in OpenAlex.

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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

7 authors at 5 institutions in 1 country.

Su-Wen HuangDepartment of General Affairs, Taichung Veterans General Hospital, Taichung 40705, Taiwan.
Shao-Jen WengDepartment of Industrial Engineering and Enterprise Information, Tunghai University, Taichung 40704, Taiwan.
Shyue-Yow ChiouDepartment of General Affairs, Taichung Veterans General Hospital, Taichung 40705, Taiwan.
Thi-Duong NguyenDepartment of Business Administration, National Chung Hsing University, Taichung 402202, Taiwan.
Chih-Hao ChenDepartment of Industrial Engineering and Enterprise Information, Tunghai University, Taichung 40704, Taiwan.
Shih-Chia LiuDepartment of Industrial Engineering and Enterprise Information, Tunghai University, Taichung 40704, Taiwan.
Yao-Te TsaiDepartment of Information Management, National Kaohsiung University of Science and Technology, Kaohsiung 82445, Taiwan.ORCID 0000-0003-3158-1517
Tunghai University · TWChaoyang University of Technology · TWNational Chung Hsing University · TWNational Kaohsiung University of Science and TechnologyTaichung Veterans General Hospital · TW

Funding

Taichung Veterans General Hospital TCVGH-T1107801
6 · The paper itself

Abstract

The provision of efficient healthcare services is essential, driven by the increasing demand for healthcare resources and the need to optimize hospital operations. In this context, the motivation to innovate and improve services while addressing urgent concerns is critical. Hospitals face challenges in managing internal dispatch services efficiently. Outsourcing such services can alleviate the burden on hospital staff, reduce costs, and introduce professional expertise. However, the pressing motivation lies in enhancing service quality, minimizing costs, and exploring innovative approaches. With the rising demand for healthcare services, there is an immediate need to streamline hospital operations. Delays in internal transportation services can have far-reaching implications for patient care, necessitating a prompt and effective solution. Drawing upon dispatch data from a healthcare center in Taiwan, this study constructed a decision-making model to optimize the allocation of hospital service resources. Employing simulation techniques, we closely examine how hospital services are currently organized and how they work. In our research, we utilized dispatch data gathered from a healthcare center in Taichung, Taiwan, spanning from January 2020 to December 2020. Our findings underscore the potential of an intelligent dispatch strategy combined with deployment restricted to the nearest available workers. Our study demonstrates that for cases requiring urgent attention, delay rates that previously ranged from 5% to 34% can be notably reduced to a much-improved 3% to 18%. However, it is important to recognize that the realm of worker dispatch remains subject to a multifaceted array of influencing factors. It becomes evident that a comprehensive dispatching mechanism must be established as part of a broader drive to enhance the efficiency of hospital service operations.

Indexed as

healthcare qualityhealthcare resource allocationintelligent dispatchpatient safetyservice efficiencysystem simulation

Identifiers

PMID38338290
PMCPMC10855065
OpenAlexW4391542200

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.