Tag Archives: data science training

US Public Health Alphabet Soup Explained: What is the ASPPH?

Go to the ASPPH web page to search for accredited programs in public health higher education in the United States and around the world

Are you aware of the ASPPH as a public health organization, but you just don’t know what it does, or how it fits into the bigger picture? I give a quick explainer of the ASPPH and its role in public health education.

US Public Health Alphabet Soup Explained: What is the APHA?

The American Public Health Association is the professional society for the occupation of public health rather than healthcare.

Curious about the American Public Health Association (APHA) – what it does, and where it fits into the bigger picture of public health organizations? I delve into these topics, and explain how you can get involved.

“Bad Blood” Highlights the Issues with No Administrative Barrier between Research and Clinical Data: Part 5 of 5

Clinical data and research data are governed by different regulations. Therefore, you cannot mix them together, but you can transfer them around from project to project.

Read my last post in a series on data-related misconduct at startup Theranos outlined in the book, “Bad Blood”, where I discuss their lack of administrative barrier between research and clinical data.

Alternative to the PDSA Model for QA/QI in Healthcare? Old-fashioned Epidemiology and Biostatistics! Part 4 of 5

The Plan Do Study Act model does not take into account all functions of a healthcare quality improvement and assurance department

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.

Does the PDSA Model Work? Part 3 of 5

Quality assurance and improvement specialists wonder whether the Plan Do Study Act model works or not

The Plan-Do-Study-Act model is promoted for quality assurance/quality improvement in healthcare. But does it have any peer-reviewed evidence base behind it? I examine that in this blog post.

“Bad Blood” Shows how Theranos was an Abject Failure in Data Stewardship: Part 3 of 5

You need governance in data science whether you are doing clinical research in a healthcare setting or in a laboratory.

The book “Bad Blood” describes the fall of startup unicorn Theranos, but also provides insight into the company’s abject failure at data stewardship, which I talk about in this blog post.

“Bad Blood” Demonstrates how a Lack of Product Description Leads to Data Science Misconduct: Part 2 of 5

You need to write a product description for your computer and business applications. Then, when scientists and marketers do research, they know what endpoints to study.

This blog post talks about how lack of product description led to data-related misconduct at Theranos, because they could never nail down exactly what they were trying to do.

The Stages of the PDSA Model: What do they Really Mean? Part 2 of 5

Implementing the Plan Do Study Act model is very cost- and labor-intensive but it is possible to get a return on investment

What are the stages of the PDSA model, and how do they relate to the functions of a QA/QI department in healthcare? The answers are not straightforward. I examine these issues in this blog post.

“Bad Blood” Reveals Theranos was Guilty of Bad Business and Bad Data Science: Part 1 of 5

Businesses that are chaotic and poorly run do not steward their data properly, and it is inaccurate.

This is my first blog post in a series of five where I talk about data-related misconduct outlined in the book “Bad Blood”, and provide guidance on how to prevent it.

Applying Rothman’s Causal Pie Model to the Death of George Floyd

Weighing relative causes visually is easier with Rothman's causal pie model

In the murder trial of Officer Derek Chauvin, the prosecution must demonstrate that the police officer’s knee on George Floyd’s neck constituted a “substantial” cause of Mr. Floyd’s death “beyond a reasonable doubt”. This presents a challenge in weighing relative causes of death, and this leads us essentially to causal inference. My blog post demonstrates […]

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