Fertility Success Rates

Great Patient-Focused Explanation Of SART Report Data

I just finished an excellent patient blog post entitled, How To Get SART Smart.

It is written by a, "28 year old married couple facing early Ovarian Failure and discussing our options of IVF or the possibility of Donor Eggs."

If medical professionals have any doubts about the patient's ability to understand success rate data and use this information as part of a larger treatment decision process, you should definitely give this a read. It is informative and covers many of the data manipulation techniques used by some clinics to boost their success rates.

While we cover similar information here, it was great to see such a detailed and informative article posted by a young patient.

Read the full post here.

2 responses to “Great Patient-Focused Explanation Of SART Report Data

  1. Thanks for the comment and blog entry!! I have to say that being turned away by so many doctors due to low egg reserve will force patients into looking much harder at exactly what all these numbers REALLY mean. If they wanna cherry pick me, I'll cherry pick them right back!!
     
    And just so you know, I refer people here all the dadgum time! And my clinic, the one that not only does not turn away patients due to FSH or egg reserve, made it on your top 25 this year. Guess I really do understand SART finally! A clinic that turns away no patient and can still produce high enough rates to land above the other clinic's out there really know what they're doing. I post a link constantly to you guys so people can narrow down the information and the clinics much more easily.
     
    I also seem to notice a trend that the top IVF centers that seem to produce year after year are typically concentrated in the same 3 regions- NorthEast (New Jersey, New York, Pennsylvania), SouthWest (Houston, some Dallas) and the West Coast, Oregon, California. Those are the 3 major regions I note year after year that turn out consistently high producing numbers, with good confidence levels and statistically significant patients (non-cherry picked). I think your list seems to corroborate that theory.

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