WinTech Owls - Risk Calculator for Expecting Mothers

[#1]

Team Name	WinTech Owls
Track	Health care & Life Sciences
Use Case	A website and/or app for helping pregnant mothers find the best quality care for their pregnancy journey by calculating their risks for various pregnancy complications and what actions they can take to mitigate these risks.
	SAS Viya, Python, and AppFactory.
Region	USA
Team lead	Kaylee Jones
Team members	Joey Roberts, and Anna Dantzler
Social media handles	Kaylee, Anna, and Joey
Is your team interested in participating in an interview?	Yes
Optional: Expand on your technology expertise	We are a group of students and IT professionals from the Women in Technology club at Western Governor's University. We are all pursuing various IT related degrees and have different professional backgrounds.

Jury Video:

Pitch Video:

[LGroves]

Great work, WinTech Owls!  You're tacking an incredibly important issue... one that is surprising in such an industrialized nation such as the U.S.  Moreover, your efforts to connect the statistics/risk factors to an easy-to-use app is impressive!

One question about your sample.  I was very surprised to hear that Asian women, aged 20-24, had the highest risk of morbidity. This runs contrary to many reports, such as this one from the Guttmacher Institute (https://www.guttmacher.org/state-policy/explore/maternal-mortality-review-committees?gad=1&gclid=Cj0...), which claim that African American women have, overall, the highest risk factors in the U.S.

Anyway, please share if I hear this correctly - and why your data might be a bit different.  I suspect it's the sample (I see 10,000 obs), but am curious, nonetheless.

And great work on bringing this important issue to the forefront. And thank you for participating in the Hack!

[jrob_0305]

Dear LGroves,  

Your article is correct in that mothers of color do face the highest maternal death rate. Our data uses the term "maternal morbidity" because our data set comes from the WONDER database and it uses that term to describe the presence of certain complications during childbirth i.e. unplanned hysterectomy, admission to ICU.  I believe that as we begin the actual work of picking apart the PRAMS dataset for the last 5 years, we will be better able to predict maternal risk that includes maternal death and really build an application that will assist all mothers in determining the best prenatal care for them. 

Thank you for your feedback and support of our cause!!

WinTech Owls

[LGroves]

Thanks for the response and clarifications, WinTech Owls!  I look forward to seeing your project advance, as the morbidity trends in the U.S. are alarming.  Hopefully data - and thoughtful analysis such as yours - can help mitigate adverse outcomes. Put simply, the U.S. can do a lot better in terms of better protecting our mothers!

Onwards!