Readmission Risk Factors

Risks & contraindications

Highlighted claims

• Medication non-adherence was a robust readmission risk factor across COPD, HF, and T2DM cohorts. — Synthetic data-augmented machine learning for 30-day readmission prediction in patients with chronic conditions: a retrospective real-world study
• Age of at least 65 years was associated with higher readmission risk in COPD and HF but not T2DM. — Synthetic data-augmented machine learning for 30-day readmission prediction in patients with chronic conditions: a retrospective real-world study
• Medicaid and uninsured status were consistently associated with greater readmission risk across cohorts. — Synthetic data-augmented machine learning for 30-day readmission prediction in patients with chronic conditions: a retrospective real-world study
• Illness severity, comorbidity, preventive care gaps, medication non-adherence, and social or behavioral factors were central drivers of readmission risk in model explanations. — Synthetic data-augmented machine learning for 30-day readmission prediction in patients with chronic conditions: a retrospective real-world study
• In COPD, influential SHAP features included SOFA score, Charlson Comorbidity Index, Medicare insurance, age, and pneumococcal immunisation status. — Synthetic data-augmented machine learning for 30-day readmission prediction in patients with chronic conditions: a retrospective real-world study
• In HF, influential SHAP features included Charlson Comorbidity Index, SOFA score, kidney disease, alcohol use history, and triglycerides. — Synthetic data-augmented machine learning for 30-day readmission prediction in patients with chronic conditions: a retrospective real-world study