Improving success rates by applying interventions in clinical practice and measuring their impact: A multicenter retrospective analysis of more than 240,000 cycles.

BACKGROUND: Systematic monitoring of key performance indicators (KPI) is an important component of quality management within the IVF laboratory and, as success of assisted reproduction depends on many variables, it is important to examine how each variable can be optimized to achieve the best possible outcome for patients.

OBJECTIVE: To analyze how the design of a QMS impacts homogenization, safety, and efficacy in multiple fertility centers. Study Design Multicenter, retrospective cohort study with 188,251 patients who underwent 246,988 assisted reproductive treatments at 14 private centers belonging to IVI-RMA clinics between January 2005 and December 2019. Data were stratified by year, clinic, and patient group (standard patient cycles with no PGT-A, standard patients with PGT-A, and oocyte donation patients). Unadjusted and adjusted logistic regression models with other known predictors were made to analyze the impact and the interactions of policies. Main outcomes were determined per clinic and summarized per year as the median of the rates of the clinics; each clinic had the same weight independent of the number of cycles.

RESULTS: Up to 188,251 patients were treated, for a total of 246,988 IVF cycles and 356,433 procedures. The introduction of standard operating procedures, trophectoderm biopsies, and blastocyst-stage transfers, coupled with an increased proportion of PGT-A cycles, led to improved outcomes while maximizing the number of single embryo transfers, driving a significant decrease in the number of multiple pregnancies while improving live birth rates. In terms of the live-birth rate per transfer, the interventions with greater impact over time in logistic regression analysis were 24-chromosome analysis and the introduction of benchtop incubators (odds ratio 1.92 [95% confidence interval 1.81 to 2.05]; p < 0.001). The odd ratios of the policies remained significant and very similar in the unadjusted and adjusted models.

CONCLUSIONS: The greatest impact on live-birth rate per cycle was obtained with a cumulative effect of all policies, especially in egg donation patients. In patients without PGT-A changing embryo culture conditions and blastocyst stage transfer had the greatest impact; in patients with PGT-A, trophectoderm biopsy. Standardizing procedures was essential in reducing variability among clinics and implementing changes.