1734: Scaling Critical Care: Tele-Icu Consultation Patterns Across Diverse Hospital Settings in Pakistan

Introduction: Tele-ICUs are transforming critical care delivery by extending specialist support to hospitals lacking intensivists. In low- and middle-income countries (LMICs), where infrastructure and workforce disparities are pronounced, Tele-ICUs offer a vital bridge to quality care. Yet, how hospital size influences the nature and intensity of care delivered via telemedicine remains poorly understood. Understanding these dynamics is essential to tailor scalable, equitable, and context-sensitive solutions. Our study analyzes patterns in patient characteristics, consultation frequency, and clinical decision-making across hospitals in a national Tele-ICU network in Pakistan. Methods: We analyzed 2,058 unique consults. Hospitals were classified by bed capacity as small (< 100 beds), medium (100–249), large (250–499), and very large (≥500). Variables compared across hospital categories included patient age, gender, number and timing of consults (weekend vs. weekday), active clinical issues, number of interventions recommended, and ICU size using Chi-square and Kruskal-Wallis tests for analysis. Results: Distinct differences emerged across hospitals. Very large hospitals were more likely to have high-capacity ICUs (>30 beds: 80.2%, p< 0.001). Patients in small hospitals more often received >3 consults than those in very large hospitals (32.4% vs. 5.0%). Median patient age declined with increasing hospital size (small: 54 [IQR 22–70] vs. very large: 25 [IQR 9–48], p=0.0001), while gender distribution remained similar. Weekend consults were more common in small hospitals (30.6%) than in very large ones (19.7%, p< 0.001). Respiratory diseases were the most frequent active issue (32.41%–41.04%, p=0.002). Most consults led to 1–3 interventions (50.4%–54.1%, p< 0.001); anti-infectives for systemic use were the most prescribed drug class (49.5%–64.6%, p< 0.001). Conclusions: Tele-ICU engagement and responses vary systematically by hospital size, reflecting broader contextual and structural differences. These findings support the need for models that adapt to institutional capacity. As LMICs expand digital health solutions, such insights can guide design, investment, and policy to optimize equitable access. Future work should explore flexible service models responsive to evolving clinical and health system needs.