Characterization of the Change in Physical Function in Adults From Acute Hospitalization to Home Health Care Across Diagnostic Categories

This is the authors' abstract. We don't add key points for this paper.

Objective: To characterize changes in mobility and activities of daily living (ADLs) from acute hospitalization through home health care across diagnostic categories, and to identify demographic and clinical factors associated with these changes. Design: Retrospective cohort study. Setting: Acute hospitalization and home health care. Participants: A total of 2060 adults in the mobility cohort (67.8±13.6 years old; 53.7% female); 614 adults in the ADL cohort (69.6±12.9 years old; 56.2% female). Interventions: Not applicable. Main Outcome Measures: Physical function was measured using the Activity Measure for Post-Acute Care (AM-PAC) "6-Clicks" Basic Mobility (BM) and Daily Activity (DA) short forms in both hospital and home health settings. Results: <.05). After controlling for all other variables (including time), older age and higher body mass index were associated with lower functional scores. Diagnostic category significantly influenced both baseline function and rate of improvement for both BM and DA. For example, individuals in the Metabolic/Cancer diagnosis group improved more slowly in BM when compared with all other diagnosis groups. Conclusions: Physical function improves from hospital admission through home health care, but recovery trajectories through home health care vary by age, body mass index, and diagnostic category. These findings demonstrate trajectories of change across care settings, highlight the importance of standardized functional assessments across care settings, and suggest a need for individualized prognostic models. This study informs clinicians, patients, and caregivers about expected recovery trajectories in mobility and ADLs that could support discharge planning and goal setting. Future research should explore the role of therapy dosage and timing and develop individualized models to better predict functional recovery.