Predictors of Home Discharge Among Patients Hospitalized for Acute Respiratory Diseases.

BACKGROUND/PURPOSE: Acute respiratory diseases such as chronic obstructive pulmonary disease and pneumonia often result in functional decline and reduced likelihood of home discharge, yet early predictors of discharge outcomes remain unclear. This study aimed to examine the predictors of discharge of patients with acute respiratory diseases who have been admitted. METHODS: The data of 85 patients with acute respiratory diseases who had been admitted to the hospital were analyzed. The variables assessed included comorbid conditions, biochemical markers, frailty status, activities of daily living, and social background. The relationships between home discharge and these variables were evaluated using independent two-sample tests, multivariate logistic regression, and receiver operating characteristic curve analyses. Statistical significance was set at p < 0.05. RESULTS: The data from 49 participants who were discharged to their homes and nine participants who were not discharged to their homes were analyzed. Individuals who were discharged home were significantly younger (p = 0.044), had shorter hospital stays (p = 0.009), shorter rehabilitation durations (p = 0.020), and lower C-reactive protein levels (p = 0.020) than those who were not discharged home. They also had significantly higher admission Functional Independence Measure (FIM) (p = 0.002) and Barthel Index scores (p = 0.014). The admission FIM score was a significant predictor of home discharge (odds ratio = 1.05; 95% confidence interval = 1.01-1.09; p = 0.015). Receiver operating characteristic curve analysis revealed an area under the curve of 0.825 (p < 0.001) and an optimal cutoff score of 75. CONCLUSION: Admission FIM scores may be associated with the probability of discharge of patients with acute respiratory diseases to their homes. These findings highlight the importance of early functional assessment in discharge planning and suggest that admission FIM scores may serve as a practical tool for optimizing patient-centered care pathways.