Quality Management in Assisted Reproductive Technologies
Summary
Quality management in assisted reproductive technologies encompasses the systematic application of policies, procedures and continuous monitoring to ensure consistency, safety and effectiveness across clinical and laboratory processes. It integrates quality assurance and quality control measures—from patient preparation and ovarian stimulation to gamete handling, embryo culture, transfer and long-term cryostorage. Standardised protocols, performance metrics and risk management frameworks are used to prevent errors, enhance reproducibility and maintain regulatory compliance. Recent innovations include automation of critical steps, digital tracking of specimens and objective assessment techniques, all designed to improve clinical outcomes and patient confidence. With fertility services expanding globally, robust quality management underpins ethical practice, reduces laboratory variability and supports evidence-based decision-making.
Research from Nature Portfolio
A multi-centre evaluation of an automated software-guided cryostorage device demonstrated reliable specimen identification, storage and retrieval across three active IVF laboratories. Continuous temperature monitoring confirmed consistent ultra-low conditions with no detrimental excursions, while radio-frequency identification tracking and workflow interruption logs revealed improved traceability and reduced manual errors. Embryologists integrating this system for over five months reported seamless adoption, highlighting advantages in automation of routine tasks and reduction of sample handling risks. This work illustrates how digital cryostorage solutions can be embedded into existing clinical settings to reinforce specimen safety and operational efficiency.
Quality Management in Assisted Reproductive Technologies publication trend
The graph below shows the total number of articles in quality management in assisted reproductive technologies across all publications each year (not limited to Nature Index journals).
Technical terms
Cryostorage systems: Equipment and protocols for preserving gametes and embryos at ultra-low temperatures to maintain viability.
Clinical decision support algorithm: A software-based tool that analyses clinical and laboratory data to guide treatment decisions and improve outcomes.
Key performance indicator (KPI): A quantifiable metric used to assess the efficiency, accuracy and quality of laboratory or clinical processes.
Non-invasive assessment techniques: Methods for evaluating cell or embryo characteristics without physical sampling, preserving specimen integrity.
Quality management: The coordinated activities and procedures established to ensure consistency, safety and efficacy across all stages of ART.
References
- A multi-center evaluation of a novel IVF cryostorage device in an active clinical setting. Scientific Reports (2024).
- Artificial Intelligence, Clinical Decision Support Algorithms, Mathematical Models, Calculators Applications in Infertility: Systematic Review and Hands-On Digital Applications. Mayo Clinic Proceedings Digital Health (2024).
- Future perspectives of non-invasive techniques for evaluating oocyte and embryo quality. The Innovation Medicine (2024).
- Comprehensive assessment of cryogenic storage risk and quality management concerns: best practice guidelines for ART labs. Journal of Assisted Reproduction and Genetics (2018).
About these summaries
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