managed healthcare organization believes they suffer from over $30 million in preventable losses annually due to
the readmission of patients who are discharged from the hospital too soon. However, keeping all patients in the hospital longer is costly and inconvenient to patients.
They hire you to develop a model of readmission risk that doctors can consider when determining when to discharge a patient. (If you find anything else in the data that helps reduce readmissions, they will appreciate that too.)
They want you to start by focusing on readmissions among their diabetic patients, and they have provided a dataset (10kDiabetes.csv) describing this patient population.
A) What model prioritization criteria metrics do you believe are most important for this project? Why?
B) Who uses the model?
C) How much value can the model drive?
D) What are the potential risk scenarios?
E) What feature engineering techniques would you use to potentially improve your model? Why
do you believe this would make an impact? Be specific with which features you would modify
and with which technique.
F) Where could you obtain SME insight for your project?
G) What supplemental data could you add?
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