AMIR FAGHIH NASIRI - Full-time Faculty Member - Department of Health Applied Science and Technology Institute of Higher Education- College of Science and Technology- Tehran

The increasing complexity of laboratory workflows in healthcare, research, and diagnostic settings demands innovative approaches to enhance quality assurance (QA). Traditional QA measures, while effective in standardized environments, often fall short in addressing inefficiencies, errors, and delays in high-complexity laboratories. Technology-driven solutions, such as laboratory information management systems (LIMS), automation, and Internet of Things (IoT)-enabled devices, offer promising opportunities to optimize workflows and elevate QA processes. This study explores the application of these technologies in high-complexity laboratory environments, analyzing their impact on QA metrics, including error reduction, turnaround times, resource utilization, and regulatory compliance. The research employs a mixed-methods approach, combining quantitative data from case studies and industry reports with qualitative insights from interviews with laboratory professionals. Findings reveal that LIMS significantly reduce manual errors and improve data integrity by streamlining data management and reporting processes. Automation technologies, such as robotic sample handlers, enhance operational efficiency and reduce turnaround times, enabling laboratories to manage higher workloads with greater accuracy. IoT-enabled devices provide real-time monitoring and predictive maintenance, reducing equipment downtime and ensuring continuous operations.However, the study also identifies challenges to the widespread adoption of these technologies, including high implementation costs, integration difficulties with legacy systems, and the need for workforce training. This research concludes that while technology-driven workflow optimization holds transformative potential for improving QA in laboratories, addressing these challenges is critical for successful implementation. The findings provide actionable recommendations for laboratory administrators and policymakers to adopt scalable, cost-effective solutions tailored to the unique needs of their facilities. Future research should focus on overcoming integration barriers and exploring the long-term sustainability of technology-driven QA systems in diverse laboratory settings.

Quality Assurance, Workflow Optimization, Laboratory Information Management Systems, Automation, Internet of Things (IoT)