The Role of Data for Reliable Quality Management: The American Example
vincenzo iaconianni
CAR-T Organisational System Expert and Assessor presso ICMED SRL
Data are not just numbers: they represent the starting point for informed decisions, targeted strategies, and continuous improvement. The American experience in monitoring Assisted Reproductive Technologies (ART) offers a striking example of how detailed data collection and analysis can drive effective quality management.
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Since the first conception using ART technologies in the United States in 1981, the demand for assisted reproduction treatments has grown exponentially. In 2021 alone, over 246,000 ART cycles were performed, resulting in approximately 97,000 newborns. However, this growth brings significant challenges in terms of safety and quality, highlighting the need for a reliable monitoring system.
The United States’ National ART Surveillance System (NASS) stands out as a model of well-structured data collection. This system gathers information not only on treatment cycles and outcomes but also on critical indicators such as birth weight, prematurity, and the proportion of multiple births. These data are not merely snapshots of clinical activity; they serve as the foundation for evaluating and improving quality standards.
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The collected data revealed that multiple births, a risk associated with ART treatments, account for 12.5% of ART newborns, compared to 3.2% in the general population. This phenomenon, often due to the transfer of multiple embryos, increases the risk of complications for mothers and newborns, including preterm birth and low birth weight. These insights have underscored the importance of single embryo transfer (SET), a practice that, when clinically appropriate, can significantly reduce risks.
In some U.S. states, the SET rate among women under 35 has exceeded 90% (e.g., in the District of Columbia), demonstrating that implementing best practices is achievable with a quality management policy driven by data.
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Another relevant aspect that emerged from the data analysis is the variability in ART usage and outcomes across states. For example, while the District of Columbia reports the highest rate of ART cycles per million women (8,515), other areas like Puerto Rico show significantly lower rates (751 cycles). These disparities highlight the need for more uniform policies and equitable access to high-quality treatments.
The importance of data lies in their ability to inform policy decisions. The collected information has enabled the development of specific recommendations:
- Promote single embryo transfer (SET) to reduce multiple births.
- Integrate ART data with maternal and neonatal health registries for long-term monitoring.
- Focus on health policies that reduce geographic disparities and ensure uniform standards across the country.
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The American case demonstrates that systematic data collection is an essential pillar for reliable quality management. This approach can be replicated in other healthcare contexts where the goal is to improve care standards through evidence. Data not only drive innovation but also ensure that it occurs safely, equitably, and effectively.
The U.S. example in monitoring ART technologies highlights a key lesson: to improve quality and safety, data must come first.