The dataset focused on readmission of Diabetes patients in the U.S. from 1999-2008. As we explored the data, we noticed many unspecified data points, specifically in weight, age, medication, and other categories. Our goal was to evaluate how choices in data formatting/presentation can hinder our ability to understand relationships between crucial factors, reducing a patient to vague statistics, thus neglecting a holistic, comprehensive understanding of their life.

This dataset is not representative of the patient or provider experience with diabetes and patients readmission into the hospital or what causes it, but instead the data set is a limited insurance/administrative dataset from the time during a push for more profitable medicine in America. Diabetes is limited to medicated, and shorter inpatients stays, which reflects an institutional press for efficiency in hospitals. By not including weight, and making other variable limited in their categories or nearly, researchers generalize and clean the data and ignore the complex reality of the disease.

Members:

Angela Mehta

Naomi Moehn-Aguayo

Tyler Paik

Summary: