Evidence map›Paper›PMID 36407749›Full record

ArticleIranian journal of public health2022

Intelligent Model of Nursing Shift in Tehran University of Medical Sciences, Tehran, Iran.

Mashallah Torabi, Maryam Goodarzi, Maryam Ahmadi, Hamideh Hamidi, Samira Elmi, Fatemeh Golmah, Samira Mortezaie, Parisa Nezari

Abstract read
In one paragraph

Article in Iranian journal of public health, 2022. 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

8 authors.

Mashallah TorabiResearch Center for Science and Technology in Medicine, Tehran University of Medical Sciences, Tehran, Iran.
Maryam GoodarziCentral Intelligent Secretariats, Desk Service and Office Automation, Tehran University of Medical Sciences, Tehran, Iran.
Maryam AhmadiCentral Intelligent Secretariats, Desk Service and Office Automation, Tehran University of Medical Sciences, Tehran, Iran.
Hamideh HamidiCentral Intelligent Secretariats, Desk Service and Office Automation, Tehran University of Medical Sciences, Tehran, Iran.
Samira ElmiCentral Intelligent Secretariats, Desk Service and Office Automation, Tehran University of Medical Sciences, Tehran, Iran.
Fatemeh GolmahCentral Intelligent Secretariats, Desk Service and Office Automation, Tehran University of Medical Sciences, Tehran, Iran.
Samira MortezaieCentral Intelligent Secretariats, Desk Service and Office Automation, Tehran University of Medical Sciences, Tehran, Iran.
Parisa NezariCentral Intelligent Secretariats, Desk Service and Office Automation, Tehran University of Medical Sciences, Tehran, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Nurses play a key role in increasing the efficiency of healthcare systems. Given the 24-hour performance of hospitals and the small number of nurses in the field of treatment, it is quintessential to re-shift them in the hospital. This study set out to achieve coherence in nursing shift planning and justice in the order of shifts in hospital. Methods: This applied and a developmental study was performed from 2019 to 2020. We used genetic algorithm to provide operational solutions and define flexible shifts and plan nurses' working hours in Yas Hospital, Tehran University of Medical Sciences Hospital, Tehran, Iran. Results: Based on the selection of each nurse and determining the approved shifts of each ward, the possibility of appropriate planning was provided to determine the required shifts per month and to estimate the needs of each department. Conclusion: Using genetic algorithm and nursing shift in office automation console provides useful tools for managers at all organizational levels, according to which a good balance between the hospital's need for nurse and nurses' demands in different time periods.

Indexed as

ExploitationGenetic algorithmHospitalNursesShift

Identifiers

PMID36407749
PMCPMC9643239

What OpenQuestion holds

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LicenceCC BY-NC
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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.