Predicting Hospital Readmission in Medicaid Patients With COPD Using Administrative and Claims Data

Area of Science:

• Health Services Research
• Pulmonology
• Health Informatics

Background:

• Hospitalized patients with Chronic Obstructive Pulmonary Disease (COPD) face high readmission rates.
• Medicaid beneficiaries with COPD represent a vulnerable population with significant healthcare utilization.
• Predicting 30-day all-cause readmissions is crucial for improving patient outcomes and managing healthcare costs.

Purpose of the Study:

• To develop and validate a predictive model for 30-day all-cause readmission in hospitalized Medicaid patients diagnosed with COPD.
• To identify key factors contributing to readmission risk in this specific patient cohort.
• To provide a tool for healthcare providers to proactively manage COPD patients post-discharge.

Main Methods:

• Retrospective analysis of Medicaid claims data from 7 US states (2016-2019).
• Inclusion criteria: International Classification of Diseases, Tenth Revision (ICD-10) codes for COPD.
• A mixed-effects logistic regression model was used to predict 30-day readmissions, incorporating patient demographics, comorbidities, healthcare utilization, and hospitalization details.
• Model performance was assessed using graphical evaluation and the area under the receiver operating characteristic (ROC) curve.

Main Results:

• The study analyzed 12,283 COPD hospitalizations from 9,437 subjects.
• A total of 2,534 (20.6%) patients experienced 30-day readmissions.
• The final predictive model incorporated demographics, comorbidities, claims history, admission/discharge variables, length of stay, and admission/discharge seasons.
• The model demonstrated acceptable predictive accuracy with an area under the ROC curve of 0.702.

Conclusions:

• The developed model accurately identifies hospitalized Medicaid patients with COPD at high risk for 30-day readmission.
• This predictive tool can inform the development of targeted post-discharge interventions to reduce readmissions.
• The model can aid in standardizing comparisons of readmission rates across different sites or over time.
• It supports a patient-centered approach to care for individuals with COPD.