Dr. Deming's sentiments are echoed by every infertility specialist. Each Center makes a maximal effort to achieve the best possible results. Yet some units do better than others. Why? Because it takes more than effort - it takes an efficient system and a stable process.
How to improve success without objective measures of quality? How to understand both the limitations and potential of your IVF lab?
The objective of this website is to disseminate information about IVF quality control methods and to support research into these techniques.
Modern cloud-based electronic medical record systems make it possible to collect information at the granular level of individual embryos and incorporate this data into quality management programs. We are assembling a community of researchers to gather data for research purposes. It is our expectation that this work will lead to the development of simple Statistical Process Analysis tools for realtime assessment of IVF system quality.
We encourage readers to contribute their ideas and participate in research to further to goal of developing these tools for clinical practice.
Statistical Process Control
Edwards Deming was a leader of a school of industrial engineers that developed the analytic tools of Statistical Process Control over 50 years ago to quantify process stability and optimize production methods. It is well known that a stable process results in high quality while an unstable process yields variable results - both good and bad - and ultimately poor quality. Statistical Process Control analysis has revolutionized quality management in diverse fields from manufacturing to medicine.
Dr. Deming famously quipped, "In God We Trust. All others must bring data." A rigorous system of data collection and analysis provides the foundation for quality improvement.
Investigation: Statistical Process Control in IVF
We are sponsoring an international study of 100 Centers to gather normative data describing process variation in IVF. Participating units will be provided a year's subscription to a cloud-based IVF laboratory electronic medical record for data collection at no cost. Clinics that presently use an EMR system may participate by downloading data via an Excel-based data transmission tool.
At the conclusion of the study data will be evaluated in a clinic-identity and patient-identity obscured fashion. Statistical Process Control analysis will be applied to each step of the ART process from egg retrieval to embryo transfer and pregnancy outcome. Our goals are to confirm that Statistical Process Control results correlate with clinical pregnancy success and to determine if excess process variation in specific aspects of the IVF process is correlated with impaired performance and hence may identify points for remediation.
to participate in our study of Statistical Process Control in IVF.
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