Evidence map›Paper›PMID 34786319›Full record

ArticleIEEE access : practical innovations, open solutions2021

IoT MEMS: IoT-Based Paradigm for Medical Equipment Management Systems of ICUs in Light of COVID-19 Outbreak.

Abdulaziz Aborujilah, Abubaker-Eseddig Fathi Mahmoud Elsebaie, Shamsul Anuar Mokhtar

Abstract read
In one paragraph

Article in IEEE access : practical innovations, open solutions, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
–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

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
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

3 authors.

Abdulaziz AborujilahMalaysian Institute of Information Technology (MIIT), University of Kuala Lumpur Kuala Lumpur 50250 Malaysia.
Abubaker-Eseddig Fathi Mahmoud ElsebaieMalaysian Institute of Information Technology (MIIT), University of Kuala Lumpur Kuala Lumpur 50250 Malaysia.
Shamsul Anuar MokhtarMalaysian Institute of Information Technology (MIIT), University of Kuala Lumpur Kuala Lumpur 50250 Malaysia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recently, COVID-19 has infected a lot of people around the world. The healthcare systems are overwhelmed because of this virus. The intensive care unit (ICU) as a part of the healthcare sector has faced several challenges due to the poor information quality provided by current ICUs' medical equipment management. IoT has raised the ability for vital data transfer in the healthcare sector of the new century. However, most of the existing paradigms have adopted IoT technology to track patients' health statuses. Therefore, there is a lack of understanding on how to utilize such technology for ICUs' medical equipment management. This paper proposes a novel IoT-based paradigm called IoT Based Paradigm for Medical Equipment Management Systems (IoT MEMS) to manage medical equipment of ICUs efficiently. It employs IoT technology to enhance the information flow between medical equipment management systems (THIS) and ICUs during the COVID-19 outbreak to ensure the highest level of transparency and fairness in reallocating medical equipment. We described in detail the theoretical and practical aspects of IoT MEMS. Adopting IoT MEMS will enhance hospital capacity and capability in mitigating COVID-19 efficiently. It will also positively influence the information quality of (THIS) and strengthen trust and transparency among the stakeholders.

Indexed as

and intensive care unitCoronavirus (COVID-19 Pandemic)ICUInternet of ThingsIoTmedical equipment management systemMEMSTHIStotal hospital information systems

Identifiers

PMID34786319
PMCPMC8545208

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.