Evidence map›Paper›PMID 40357423›Full record

ArticleJournal of healthcare leadership2025

Challenges of Healthcare Systems in Saudi Arabia to Delivering Vision 2030: An Empirical Study From Healthcare Workers Perspectives.

Fahad M Al-Anezi

Abstract read
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In one paragraph

Article in Journal of healthcare leadership, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
29citing 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

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

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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

1 author.

Fahad M Al-AneziCollege of Business Administration, Department Management Information Systems, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia.ORCID 0000-0002-5458-7818

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and Aim: This study explores the key challenges affecting the healthcare system in Saudi Arabia as it strives to achieve the objectives of Vision 2030. Unlike previous research, which has primarily focused on policy and structural reforms, this study provides empirical insights from healthcare workers, offering a frontline perspective on the barriers to effective healthcare transformation. Methods: A cross-sectional survey was conducted among 383 healthcare professionals from public and private hospitals. The questionnaire covered challenges related to capacity and infrastructure, workforce shortages, digital transformation, preventive healthcare, coordination and integration, healthcare financing, public awareness, quality of care, and disease prevention. Data were analyzed using descriptive statistics, t-tests, and ANOVA to assess variations in perceptions based on professional roles, work experience, gender, and hospital type. Results: The findings reveal workforce shortages, infrastructure limitations, and digital transformation gaps as the most pressing concerns. Notable differences in perceptions highlight the need for tailored interventions across different healthcare roles and settings. Addressing these challenges requires strategic workforce planning, investment in infrastructure, digital innovation, and sustainable financing models. Conclusion: This study contributes to the literature by offering evidence-based recommendations for policymakers and healthcare administrators, aligning healthcare system improvements with Vision 2030 objectives. The insights provided can help shape targeted strategies to enhance healthcare efficiency, accessibility, and resilience in Saudi Arabia.

Indexed as

digital healthhealthcare challengespolicy reformSaudi ArabiatransformationVision 2030workforce

Identifiers

PMID40357423
PMCPMC12067643

What Socratic holds

Textmetadata
LicenceCC BY-NC
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 Socratic graph.