Background: Mental illness affects an estimated 25% of the global population, with treatment gaps persisting worldwide. The COVID-19 pandemic has exacerbated these challenges, leading to a significant increase in mental health issues globally. In Saudi Arabia, the lifetime prevalence of mental disorders is estimated at 34.2%, yet 86.1% of those with a 12-month mental disorder report no service use. To address these challenges, digital health solutions, particularly electronic referral (e-referral) systems, have emerged as powerful tools to improve care coordination and access. Saudi Arabia has pioneered the nationwide Saudi Medical Appointments and Referrals Centre (SMARC), a centralized e-referral system using artificial intelligence and predictive analytics. Objectives: This study aims to analyze Saudi Arabia’s novel nationwide e-referral system for mental health services, using SMARC platform data to examine referral patterns, and service accessibility. This study also aims to demonstrate how digital health technology can inform and improve mental health care delivery and policy making. Methods: This retrospective, cross-sectional study used secondary data from SMARC on 10,033 psychiatric e-referrals in Saudi Arabia during 2020‐2021. Referrals were assessed by patient sociodemographic variables, geographic data, and e-referral characteristics including date, type, bed type, and reason for e-referral. Descriptive statistical analyses identified referral patterns, while regression modeling determined predictors of external referrals to other regions. Results: Analysis of 10,033 psychiatric e-referrals revealed that 58.99% (n=5918) were for patients aged 18‐44 years, 63.93% (n=6414) were for men, and 87.10% (n=8739) were for Saudi nationals. The Western Business Unit generated 45.17% (n=4532) of all e-referral requests. Emergency cases were the most common type of referral overall, followed by routine inpatient and routine outpatient department referrals. However, in the Northern Business Unit, routine inpatient referrals were most frequent. Two-thirds of requests were for ward beds, while critical beds were rarely requested. “Unavailable subspecialty” was the primary reason for referrals across all regions. The utilization of the mental health e-referral system varied across regions, with the Northern Border and Albaha regions showing the highest rates, while Madinah, Eastern, and Riyadh regions demonstrated lower use. Temporal analysis showed almost similar monthly patterns in 2020 and 2021. There was an overall increase in referrals in 2021 compared with 2020. Conclusions: This pioneering study of mental health e-referrals in Saudi Arabia demonstrates how digital health transformation, particularly through an e-referral system, has significantly enhanced access to mental health services nationwide in Saudi Arabia. The success of this digital initiative demonstrates how digital health solutions can transform health care access, particularly in mental health services, offering a valuable model for other health care systems.

This study aimed to assess patient-related factors associated with the LOS among adults admitted to the ICU in Saudi Arabia. The Ministry of Health provided a cross-sectional dataset for 2021, which served as the data source for this study. The data included data on adults admitted to different ICUs at various hospitals. The number of days spent in the ICU was the outcome variable of interest. The potential predictors were age, sex, and nationality, as well as clinical data from the time of admission. Descriptive statistics and bivariate analysis were used to analyse the association between the predictors and the ICU LOS and characterize how they were distributed. We used negative binomial regression to examine the relationship between the study predictors and the ICU LOS. A total of 42,884 individuals were included in this study, of whom 25,520 were men and 17,362 were women. The overall median ICU LOS was three days. This study showed that the ICU LOS was highly influenced by the patient’s age, sex, nationality, source of admission, and clinical history. Several predictors that affect how long adults stay in the ICU in Saudi Arabian hospitals were identified in this study. These factors can be attributed to variances in health care delivery systems, patient demographics, and cultural considerations. To allocate resources efficiently, enhance patient outcomes, and create focused treatments to reduce ICU LOS, it is essential to comprehend these elements.

Background/Objectives: Intensive care unit (ICU) e-referrals are an important indicator for exploring potential deficiencies in critical care resources. This study aimed to examine the epidemiology and patterns of ICU e-referrals across all regions of Saudi Arabia during the COVID-19 pandemic using routinely collected data from April 2020 to December 2021. Methods: This descriptive epidemiological study analyzed data from the Saudi Medical Appointments and Referrals Centre (SMARC). This study reveals novel regional ICU e-referral patterns for critical cases using national unique digital health data, adding insights beyond the existing literature. Variables included age, sex, referral timing, reason, specialty, and region of origin. Descriptive statistics and mapping of administrative areas were performed based on e-referral request rates per 10,000 population. Results: During the study period, 36,619 patients had ICU e-referral requests. The mean age was 54.28 years, with males constituting 64.81% of requests. Out-of-scope e-referrals comprised 71.44% of requests. Referrals related to medical specialties, such as cardiology and pulmonology, were the most common (62.48%). Referral patterns showed peaks in July–August 2020 and May 2021. The Northern Border and Albaha areas had the highest request rates per population, potentially reflecting a higher proportion of severe cases requiring ICU-level care compared to other regions. Conclusions: The temporal pattern and geographic distribution of ICU e-referrals mirrored previously reported critical COVID-19 cases in Saudi Arabia. Preventive measures and vaccination programs contributed to a significant decline in ICU e-referral requests, suggesting a positive impact on controlling severe COVID-19 cases. Population-adjusted analysis revealed regional disparities, highlighting the importance of considering population size in healthcare resource management and policy.

Background/Objectives: Saudi Arabia implemented the Saudi Medical Appointments and Referrals Centre (SMARC) e-referral system to coordinate patient transfers and enhance healthcare access across the country. This nationwide system was established to improve coordination between healthcare facilities and provide timely access to specialized services. SMARC operates as a centralized coordination hub connecting secondary and tertiary care facilities across all specialties nationwide. This study evaluates SMARC’s evolution since 2020–2021 and efficiency improvements through 2023–2024 after major expansion efforts. Methods: This retrospective analysis examined 755,145 e-referrals across all 13 administrative regions of Saudi Arabia during 2023–2024. The study analyzed data extracted from the SMARC database covering two consecutive years. Outcomes assessed included acceptance rates, referral destinations (internal within the same region vs. external to other regions), and factors associated with system performance. Results: The total volume of e-referrals through SMARC increased substantially by 19.34% to 755,145 in 2023–2024. Acceptance rates for referrals improved markedly from 74.13% to 90.19% over this period. The proportion of internal referrals increased from 80.13% of total referrals to 87.52%. In contrast, external referrals to other regions declined from 19.87% to 12.48% of the total. Critical care referrals (ICU, CCU, NICU, PICU) decreased from 12.39% to 9.91%. Referrals for life-saving emergency conditions showed a noticeable decrease from 6.65% to 2.18%. Referrals to hospital outpatient departments (OPD) also showed an increase from 48.07% to 66.66% of total referrals. Conclusions: SMARC demonstrated considerable improvements in key metrics including referral acceptance rates and growth in regional self-sufficiency. This progress is associated with the Kingdom’s goals for advancing its healthcare system under Vision 2030 initiatives. The system has enabled more effective care coordination and access to specialized services across regions. These achievements were observed during a period of significant healthcare infrastructure expansion documented during this period, including growth in specialized centers, increased ICU bed capacity following governmental regulation after the COVID-19 pandemic, and expansion of trained medical subspecialists.

Background/Objectives: Poisoning represents a significant global public health challenge, particularly with its complex manifestations in adult populations. Understanding regional epidemiology through digital health systems is crucial for developing evidence-based prevention and management strategies. This nationwide study analyzes hospital-based toxicology teleconsultation data from the Toxicology Consultation Service-Saudi Medical Appointments and Referrals Center (TCS-SMARC) platform to characterize the epidemiological patterns, clinical features, and outcomes of adult poisoning cases across Saudi regions. Methods: We conducted a retrospective cross-sectional analysis of 6427 adult poisoning cases where hospitals sought teleconsultation from the Saudi Toxicology Consultation Service (TCS) from January to December 2023. Descriptive statistics were used to analyze poisoning rates by demographic characteristics, agents responsible for the poisoning, clinical presentations, and management decisions. Population-adjusted rates were calculated using the national census data. Associations between variables were analyzed using cross-tabulations and chi-square tests. Results: Young adults aged 18–35 years constituted most cases (58.67%), with the highest population-adjusted rates observed among those aged 18–24 (5.15 per 10,000). Medicine-related poisonings were the most common across all regions (50.04%), followed by bites and stings (15.31%). Regional analysis indicated relatively uniform poisoning rates across Business Units (BUs) (2.02–2.74 per 10,000). Most cases (87.44%) were asymptomatic, with 91.71% exhibiting normal Glasgow Coma Scale scores, although substance abuse cases had higher rate of severe manifestations (24.34%). Significant seasonal variations were observed (p < 0.001), with peak incidents occurring in the summer (29.25%). Management decisions primarily involved hospital observation (40.27%) and admission (30.34%), with agent-specific variations in care requirements (p < 0.001). Conclusions: This comprehensive analysis demonstrates the effectiveness of Saudi Arabia’s digital health infrastructure in capturing and managing nationwide poisoning data. The integrated digital platform enables real-time surveillance, standardized triage, enhanced access to specialized toxicology services, and coordinated management across diverse geographical contexts. Our findings inform evidence-based recommendations for targeted prevention strategies, particularly for young adults and medicine-related poisonings, while establishing a scalable model for digital health-enabled poisoning management.

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.