Evidence map›Paper›PMID 37550351›Full record

ArticleScientific reports2023

Vendor evaluation platform for acquisition of medical equipment based on multi-criteria decision-making approach.

Neven Saleh, Mohamed N Gaber, Mohamed A Eldosoky, Ahmed M Soliman

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2023. 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
3.0field-weighted citation impact, top 9% 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, 15 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

4 authors at 3 institutions in 1 country.

Neven SalehBiomedical Engineering Department, Higher Institute of Engineering, Shorouk Academy, Cairo, Egypt.
Mohamed N GaberMilitary Technical College, Cairo, Egypt.
Mohamed A EldosokyBiomedical Engineering Department, Faculty of Engineering, Helwan University, Cairo, Egypt.
Ahmed M SolimanBiomedical Engineering Department, Faculty of Engineering, Helwan University, Cairo, Egypt. ahmed_soliman05@h-eng.helwan.edu.eg.
Helwan University · EGHigher Institute of Engineering · EGMilitary Technical College · EG

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The purchase of medical equipment is a critical issue that should be planned properly. The selection of the most appropriate vendor impacts time, effort, and expenses. Therefore, the challenge is to strike a balance between the available budget and the required equipment. The study aims to select the best vendor for supplying medical equipment based on Emergency Care Research Institute (ECRI) standards. The multi-criteria decision-making approach has been adopted through three methods; Multi-Objective Optimization by Ratio Analysis (MOORA), Simple Additive Weighting (SAW), and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The criteria of selection are divided into general, technical, and financial. The criteria are weighted using three methods: CRITIC, entropy, and expert judgment. The Vendor Evaluation Program for Medical Equipment (VEPME) is designed to automatically select the best vendor. Medical imaging equipment is selected to test the program by four modalities: X-ray equipment, CT, MRI, and ultrasound. The best scenario was given by the entropy-TOPSIS. As a result, this methodology was adopted by the program. The results demonstrate the robustness of the proposed methodology by comparing the VEPME output to expert judgment.

Indexed as

Decision Support TechniquesEmergency Medical ServicesAcademies and InstitutesCommerceProgram Evaluation

Identifiers

PMID37550351
PMCPMC10406946
OpenAlexW4385635324

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.