Comparative models on low multiplier DRG classification for advanced lung cancer

Based on comorbidity severity, the DRG classification for advanced lung cancer patients receiving internal medicine treatment under ER1 appeared reasonably structured and provided a valid basis for subgroup comparisons. Additionally, according to the predictive model's findings, potential signs of upcoding and intentional underuse of reimbursable medications were observed, highlighting the need to monitor examination fee reductions across ER1 subgroups and to track medication costs in ER11 throughout the hospital stay. Lastly, in predicting low multiplier DRGs, larger datasets improve model stability. Model choice should align with the analytical goal: Random Forest offers higher precision and robustness, while logistic regression or SVM may be preferred for higher recall.