Hikmet Can Çubukçu
MD, PhD, MSc, EuSpLM
Sincan Training and Research Hospital
Turkiye
Dr. Hikmet Can Çubukçu graduated from Ufuk University Faculty of Medicine in 2013 and completed his residency (medical specialty training) in Medical Biochemistry at Ankara University Faculty of Medicine in 2019. He was awarded the title of Associate Professor in Medical Biochemistry in 2023. In 2024, he completed a master’s degree in software engineering at Hacettepe University and a Ph.D. in Regenerative Medicine at the Stem Cell Institute of Ankara University. He is a member of the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) Committee on Accreditation and ISO/CEN Standards, and the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) Committee on Artificial Intelligence in Laboratory Medicine. He also serves as an expert in the IFCC Taskforce on Global eLearning/eAcademy. Dr. Hikmet Can Çubukçu currently works at the Turkish Ministry of Health, Department of Rare Diseases within the General Directorate of Health Services, and at the Department of Medical Biochemistry at Sincan Training and Research Hospital. His main research interests include risk-based internal quality control, patient-based quality control, setting analytical performance goals based on indirect clinical outcomes, and the application of artificial intelligence in clinical laboratories.
Topics
Optimizing QC Frequency Using a Risk-Based Approach: Considering Analytical Performance and Potential Harm
Quality in Laboratory Medicine
Analytical Quality Control
5.2.2026 11:00 - 11:35 | Hall 208
Risk-based internal quality control (IQC) planning necessitates a systematic framework to optimize IQC frequency with appropriate IQC rule by considering both analytical performance and the potential harm associated with measurement errors. Analytical performance, commonly expressed by sigma metrics, directly influences the maximum run size between IQC events. In parallel, the clinical severity of harm caused by erroneous results must be incorporated into QC design. Lower sigma metrics or higher severity of harm necessitate more frequent IQC events to ensure patient safety. By integrating sigma performance data and severity classifications into QC planning, laboratories can establish a balanced IQC frequency that minimizes patient risk while maintaining operational feasibility. Furthermore, employing hybrid strategies that combine risk-based internal IQC with patient-based IQC can enhance the early detection of errors. A standardized approach to sigma metric calculation and clearer definitions of severity categories are essential for widespread and reliable application of risk-based IQC planning.
