Evidence map›Paper›PMID 38907592›Full record

ArticleJournal of primary care & community health

Assessing the Disruption Impact on Healthcare Delivery.

Maymunah Fatani, Abdulrahim Shamayleh, Hussam Alshraideh

Abstract read
In one paragraph

Article in Journal of primary care & community health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

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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

3 authors.

Maymunah FataniBiomedical Engineering Graduate Program, American University of Sharjah, Sharjah UAE.
Abdulrahim ShamaylehBiomedical Engineering Graduate Program, American University of Sharjah, Sharjah UAE.ORCID 0000-0002-0214-7052
Hussam AlshraidehBiomedical Engineering Graduate Program, American University of Sharjah, Sharjah UAE.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Health emergency outbreaks such as the COVID-19 pandemic make it challenging for healthcare systems to ration medical resources and patient care. Such disastrous events have been increasing over the past years and are becoming inevitable, necessitating the need for healthcare to be well-prepared and resilient to unpredictable rises in demand. Quantitative and qualitative based decision support systems increase the effectiveness of planning, alleviating uncertainties associated with the crisis. This study aims to understand how the COVID-19 pandemic has affected the performance of healthcare systems in different areas and to address the associated disruption. A cross-sectional online survey was conducted in the Kingdom of Saudi Arabia and the United Arab Emirates among healthcare workers who worked during the pandemic. The pandemic-related disruption and its psychometric properties were assessed using Structural Equations Modeling (SEM) with 5 latent factors: Staff Mental Health, Communication Level, Planning and Readiness, Healthcare Supply Chain, and Telehealth. Responses from highly qualified participants with many years of experience in hospital settings were collected and analyzed. Results show that the model satisfactorily fits the data with a CLI of 0.91 and TLI of 0.88. The model indicates that enhancing supply chain management, planning, telehealth usage, and communication level across the healthcare system can mitigate the disruption. However, the lack of mental health management for healthcare workers can significantly disrupt the quality of delivered care. Staff mental health and healthcare supply chain, respectively, are the highest contributors to varying degrees of disruption in healthcare delivery. This study provides a direction for more research focusing on determinants of healthcare efficiency. It also provides decision-makers insights into the main factors leading to disruptions in healthcare systems, allowing them to shape their outbreak response and better prepare for future health emergencies.

Indexed as

COVID-19Delivery of Health CareHealth PersonnelAdultCross-Sectional StudiesFemaleHumansMaleMiddle AgedPandemicsSARS-CoV-2Saudi ArabiaSurveys and QuestionnairesTelemedicineUnited Arab EmiratesCOVID-19healthcare delivery disruptionhealthcare supply chainhealthcare workers wellbeingtelehealth

Identifiers

PMID38907592
PMCPMC11193933

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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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.