What question did this study set out to answer?

The study aims to analyze obstetrics and gynecology e-referral patterns to inform healthcare capacity planning.

April 1, 2026Open Access

Healthcare Access Through Digital Coordination: A Nationwide Analysis of Obstetrics and Gynecology E-Referral Patterns in Saudi Arabia

Key Points

The study aims to analyze obstetrics and gynecology e-referral patterns to inform healthcare capacity planning.
Conducted a retrospective descriptive analysis of 39,526 OB/GYN referrals using the MRC platform.
Applied descriptive statistics, chi-square tests, and one-way ANOVA for data analysis.
Employed multivariable logistic regression to examine trends in referral direction.
Achieved an overall acceptance rate of 91.81% for referrals.
General OB/GYN accounted for 60.68% of referrals, followed by obstetrics and fetal medicine at 16.37%.
71.35% of referrals were for outpatient care, with obstetrics and fetal medicine showing 55.62% NICU utilization.
Internal referral odds increased by 1.7% monthly during the study period.

Abstract

Background/Objectives: Obstetrics and gynecology healthcare represents a global health concern requiring coordinated, accessible services across diverse populations. The Saudi Medical Referrals Centre (MRC) functions as a comprehensive digital health surveillance and coordination platform managing nationwide obstetrics and gynecology (OB/GYN) services. This study characterizes national OB/GYN e-referral patterns coordinated through the MRC platform to describe subspecialty utilization and inform capacity planning, and examines temporal trends in referral direction over the study period. Methods: A retrospective descriptive analysis of the MRC’s digital coordination platform examined 39,526 OB/GYN referrals across Saudi Arabia’s healthcare system (2023–2024). Descriptive statistics, chi-square tests, and one-way ANOVA tests were used to analyze patient demographics, subspecialty distribution, referral types, bed requirements, acceptance rates, geographic patterns, and multivariable logistic regression examined temporal trends in referral direction. Results: The platform achieved 91.81% overall acceptance rates. Platform surveillance revealed referral request distribution by subspecialty: general OB/GYN (60.68%), obstetrics and fetal medicine (16.37%), and reproductive endocrinology and infertility (14.94%). Most referral requests were for outpatient care (71.35%), though obstetrics and fetal medicine demonstrated relatively high NICU utilization (55.62%). Urgent referral requests constituted 22.05% of cases. Internal referral odds increased 1.7% monthly over the study period (OR = 1.017; p < 0.001). Conclusions: This nationwide descriptive analysis of 39,526 OB/GYN e-referrals reveals distinct subspecialty-specific referral patterns, with high overall acceptance rates and predominantly internal referral coordination. These system-level findings provide a baseline for future studies within digital referral platforms.

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