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Acceptance of electronic referrals across the Kingdom of Saudi Arabia

Results from a national e-health database

Bibliographic Data

ID22077268
AuthorsAbdullah Alharbi (0000-0002-5405-2055, Jazan University), Abdullah A Alharbi, Nawfal A Aljerian, Nawfal Aljerian (0000-0002-3242-0312, King Saud bin Abdulaziz University for Health Sciences), Meshary S Binhotan, Meshary Binhotan (0000-0002-8156-2843, King Saud bin Abdulaziz University for Health Sciences, corresponding author), Hani A Alghamdi (0000-0002-5025-8136, King Saud University), Reem S AlOmar (0000-0003-4899-7965, Imam Abdulrahman Bin Faisal University), Ali K Alsultan (0009-0003-1954-5481, Ministry of Health), Mohammed S Arafat, Mohammed Arafat (0000-0002-6168-4966, Ministry of Health), Abdulrahman Aldhabib (Ministry of Health), Ahmed I Aloqayli, Ahmed Aloqayli (Ministry of Health), Eid B Alwahbi (Ministry of Health), Mohammed K Alabdulaali (Ministry of Health)
Year2024
Volume12
Pages1337138-1337138
Publication date2024-07-17
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueFrontiers in Public Health (JOURNAL)
Journal identifiersISSN: 2296-2565 • E-ISSN: 2296-2565
PublisherFrontiers Media SA (PUBLISHER • CH)
DOI10.3389/fpubh.2024.1337138
PMID39086803
OpenAlexW4400745239
LanguageEN
References cited32

Introduction: An effective referral system is necessary to ensure quality and an optimum continuum of care. In the Kingdom of Saudi Arabia, an e-referral system known as the Saudi Medical Appointments and Referrals Centre (SMARC), has been fully functioning since 2019. This study aims to explore the rate of medical e-referral request acceptance in the KSA, and to study the factors associated with acceptance. Methods: This period cross-sectional study utilised secondary collected data from the SMARC e-referral system. The data spans both 2020 and 2021 and covers the entirety of the KSA. Bivariate analyses and binary logistic regression analyses were performed to compute adjusted Odds Ratios (aORs) and 95% confidence intervals. Results: Of the total 632,763 referral requests across the 2 years, 469,073 requests (74.13%) were accepted. Absence of available machinery was a significant predictor for referral acceptance compared to other reasons. Acceptance was highest for children under 14 with 28,956 (75.48%) and 63,979 (75.48%) accepted referrals, respectively. Patients requiring critical care from all age groups also had the highest acceptance including 6,237 referrals for paediatric intensive care unit (83.54%) and 34,126 referrals for intensive care unit (79.65%). All lifesaving referrals, 42,087 referrals, were accepted (100.00%). Psychiatric patients were observed to have the highest proportion for accepted referrals with 8,170 requests (82.50%) followed by organ transplantations with 1,005 requests (80.92%). Sex was seen to be a significant predictor for referrals, where the odds of acceptances for females increased by 2% compared to their male counterparts (95% CI = 1.01-1.04). Also, proportion of acceptance was highest for the Eastern business unit compared to all other units. External referrals were 32% less likely to be accepted than internal referrals (95% CI = 0.67-0.69). Conclusion: The current findings indicate that the e-referral system is mostly able to cater to the health services of the most vulnerable of patients. However, there remains areas for health policy improvement, especially in terms of resource allocation

Database · Electronic database · Electronic health record · Family medicine · Health care · Political science · Computer Science · Healthcare Systems and Technology · Hospital Admissions and Outcomes · Medicine · Patient Satisfaction in Healthcare

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