4.3.13 Healthcare Costs - Video 7: Baseline Method and Penalty Matrix

TL;DR

The baseline method for predicting healthcare costs in 2009 based on costs in 2008 had an accuracy of 68% and a penalty error of 0.74.

Transcript

Let's now see how the baseline method used by D2Hawkeye would perform on this data set. The baseline method would predict that the cost bucket for a patient in 2009 will be the same as it was in 2008. So let's create a classification matrix to compute the accuracy for the baseline method on the test set. So we'll use the table function, where the a... Read More

Key Insights

• 🪣 The baseline method is a simple approach that assumes the cost bucket for a patient in 2009 will be the same as it was in 2008.
• 🪣 The accuracy of the baseline method is determined by comparing the predicted cost buckets with the actual cost buckets in a classification matrix.
• ⚾ The penalty matrix assigns penalties based on the difference between predicted and actual cost buckets, determining the penalty error of the baseline method.
• 🇨🇷 The penalty error of the baseline method is 0.74, indicating the cost predictions were penalized for incorrect categorization.
• 😘 The next step is to develop a CART model with higher accuracy and lower penalty error than the baseline method.
• 🇨🇷 Improving the accuracy and reducing the penalty error of the CART model will provide more reliable predictions for healthcare costs.
• 😒 CART models use decision trees to make predictions based on independent variables.

Questions & Answers

Q: What is the accuracy of the baseline method for predicting healthcare costs in 2009?

The accuracy of the baseline method is 0.68, meaning it correctly classified 68% of observations in the test set based on their cost buckets in 2008.

Q: How is the penalty error computed for the baseline method?

The penalty error is computed by multiplying the classification matrix by a penalty matrix, which assigns penalties for predicting a different cost bucket than the actual outcome. The penalty error for the baseline method is 0.74.

Q: What is the goal for the upcoming CART model?

The goal for the next video is to create a CART model that outperforms the baseline method by achieving a higher accuracy than 68% and a lower penalty error than 0.74 in predicting healthcare costs.

Summary & Key Takeaways

• The baseline method predicts that the cost bucket for a patient in 2009 will be the same as it was in 2008.

• An accuracy classification matrix is created to measure the accuracy of the baseline method on a test set.

• A penalty matrix is created to compute the penalty error of the baseline method by multiplying the classification matrix by the penalty matrix.