CDC Wonder is an online query portal that serves as a gateway to many government datasets. Although antiquated, it still works for extracting data, and my blog post shows you how.
Tag Archives: data quality
16
Jun
Jun
Front-end decisions are made when applications are designed. They are even made when you design a survey in SurveyMonkey. What health data analysts often don’t realize is that these decisions have a profound impact on the quality and accuracy of the data that are collected through these front-ends, which is the focus of this blog […]
06
May
May
What does the SAMHSA actually do for mental health and substance abuse patients in the US? The answer is, “nothing directly” – however, indirectly, SAMHSA has had a profound impact on behavioral health patients, and the result has not always been positive, as you can read in my blog post.
08
Apr
Apr
Data curation solution that I posted recently with my blog post showing how to do upset plots in R using the UpSetR package was itself kind of a masterpiece. Therefore, I thought I’d dedicate this blog post to explaining how and why I did it.
11
Sep
Sep
Watch a video of my presentation on data collection from chronic disease patients for healthcare quality control and quality improvement – and download the slides!
23
Jul
Jul
Want to know what AHRQ stands for, what it does, and how all that relates to US public health? AHRQ is a main player in public health – even though it is technically supposed to be focused on healthcare.
Quality Assurance/Quality Improvement (QA/QI)
Alternative to the PDSA Model for QA/QI in Healthcare? Old-fashioned Epidemiology and Biostatistics! Part 4 of 5
07
Jul
Jul
Want an alternative to the Plan-Do-Study-Act (PDSA) model for quality assurance/quality improvement (QA/QI) in healthcare? I recommend approaching QA/QI a different way, by thinking about the various functions of the QA/QI department.
Quality Assurance/Quality Improvement (QA/QI)
“Bad Blood” is a Lesson in How Bad Leadership Leads to Bad Data: Part 4 of 5
05
Jul
Jul
As a data science leader, what should you put in place so your organization doesn’t end up a data mess like startup Theranos? This blog posts provides guidance.
