FINAL PROJECT:Structures and Arguments > A Data Science Tutorial: Insights on Medical Appointment No-shows

Beginning: Introduction to data science as a field, as well as background on the importance of the topic (missed clinic appointments) to get the reader interested in the results of the analysis.

Middle: Various data science pipeline techniques, including set-up, data collection and processing, exploratory data analysis, and machine learning analysis.

End: Use results of analysis to provide relevant insights and policy suggestions on the given topic of clinic no-shows.

LOGOS: Links to official documentation of demonstrated programming methods. Anonymized medical appointment data on >100k medical appointments of the public healthcare system for the capital city of Espirito Santo State in Brazil, Vitoria, and the characteristics of each.

PATHOS: The adverse effects of missed clinic appointments both on patient health outcomes as well as provider efficiency.

ETHOS: I have experience both as a data scientist having taken cmsc320 (Data Science), and as someone who can comment on the effects of missed clinic appointments as a medical ER scribe.

STRUCTURE: I will begin with background on the content that is being analyzed (clinic no-shows), then follow with a multi-section tutorial walking through the different steps of the data science pipeline. Each section will have a short intro describing the section and any relevant definitions or concepts followed by code and prose explanation in code and markdown cells respecticely.

GOAL: To teach aspiring data scientists the basics of a dataset analysis and visualization.
May 7, 2018 | Unregistered CommenterJK
J, a good project that weds your two interests. I am really glad you can rewrite this existing work for my class. I imagine that you have new insights, too, that happen after time passes.

You might enjoy this McKinsey report on big data and medicine, https://www.mckinsey.com/industries/pharmaceuticals-and-medical-products/our-insights/the-role-of-big-data-in-medicine
May 7, 2018 | Unregistered CommenterMbS
Here are a few additional links for you to contemplate for your medical school interview, when the committee may want to hear about how you incorporate both interests:

https://www.sciencedirect.com/science/article/pii/S2352914817302253

And, this 1987 piece that you could read and then think about how the predictions panned out.
https://www.sciencedirect.com/science/article/pii/0020710187900353
May 7, 2018 | Unregistered CommenterMbS