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Wang's "What caused Texas' maternal death rate to skyrocket? Inaccurate data."

Writing for the Dallas News, Jackie Wang describes how data entry errors lead to the erroneous belief that Texas pregnancy related death rates were more than double the national rate.

Short story: Texas thought it had terribly high rates of pregnancy related deaths. It didn't. Turns out that folks were just using the online system for reporting cause of death incorrectly. So, human data entry errors lead to what looked like a spike in maternal deaths. Like, whenever I make a change in my grade book columns in Blackboard, I always forget to hit "Save" and then the changes I make aren't saved. Only here, that sort of small error caused Texas to think that death rates for pregnancy complications was 14.6:100,000, not the reported 38.4:100,000. Which is an enormous difference. And a lot of money was spent to rectify the problem, which wasn't a problem, but those actions were probably still good for women and babies and families.

This article details how Texas had its own mini Replication Crisis. After the awful numbers came out, Texas investigated its own data. Instead of needing to radically alter how pregnant women are treated in Texas, they found that they really needed to improve training for the online reporting of deaths.

How to use in class:
-The article I've linked above includes links to peer-reviewed, published research articles about pregnancy related deaths in Texas.
-This is an example of good science writing.
-This is an example of human factors (the data entry method for filing death certificates led to the high error rates).
-This is also a soft example for the need to replicate and follow up on research findings when research findings seem wonky.
-Double check your data entry, kids!

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