A Cost-Effectiveness Analysis evaluates the health and costs of interventions (as opposed to the status quo). Each intervention and the status quo is evaluated by the ratio between net cost and changes in health outcome for each scenario. It is a common tool in Health Decision Science to develop data-driven recommendations.
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- Problem to be Studied
- Methodology
- Results
- Sensitivity Analyses
- Policy Recommendation
- Sources of Data
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Decision Tree Model built in Python
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Decision Tree Visualization
NOTE: C stands for complementary probability, where branch's total probability is 1.