Discrete-Event Simulation to Model the Thrombolysis Process for Acute Ischemic Stroke Patients at Urban and Rural Hospitals

Improving Acute Ischemic Stroke Care in Kazakhstan: Cross-Sectional Survey

Background: Acute ischemic stroke (AIS) is a leading cause of mortality and long-term disability worldwide, with upper-middle-income countries (UMICs) facing a disproportionate burden due to systemic inefficiencies in healthcare delivery. Kazakhstan reports the highest global age-standardized mortality rate from ischemic stroke, underscoring the need to evaluate current stroke care practices and identify areas for improvement. Objective: This study aimed to assess the current state of acute ischemic stroke care in Kazakhstan by examining key time metrics, protocol adherence, and the utilization of advanced technologies such as artificial intelligence (AI) and telemedicine. Additionally, this study sought to identify regional disparities in care and propose actionable recommendations to improve patient outcomes. Methods: A multi-center cross-sectional survey was conducted across 79 stroke centers in Kazakhstan. Data were collected from 145 healthcare professionals, including neurologists, neurosurgeons, and interventional radiologists, through a validated 23-question online questionnaire. Statistical analysis was performed to identify significant associations between variables. Results: Significant regional disparities were observed in stroke care timelines and technology adoption. Remote and rural areas experienced prolonged prehospital delays, with transport times ranging from 120 to 180 min, contributing to door-to-needle times exceeding the recommended benchmark. Urban centers with higher adoption of AI and telemedicine demonstrated faster treatment initiation and better protocol compliance. Staff training was significantly associated with improved treatment outcomes, with trained centers more likely to implement direct-to-angiography suite protocols, reducing in-hospital delays. Conclusions: Addressing acute ischemic stroke care disparities in Kazakhstan requires a multifaceted approach, including expanding AI and telemedicine, implementing targeted staff training programs, and establishing standardized national stroke protocols. These strategies can help reduce treatment delays, bridge the urban-rural healthcare divide, and improve patient outcomes. The findings have implications for other UMICs facing similar challenges in delivering equitable stroke care.