Phys Ther. 2025 Jul 13:pzaf093. doi: 10.1093/ptj/pzaf093. Online ahead of print.ABSTRACTIMPORTANCE: Identifying patients most likely to benefit from physical therapy in the hospital could aid physical therapists in optimizing treatment allocation for the purpose of increasing discharge to home.OBJECTIVE: The aims of this study were to develop and externally validate a predictive model for discharge to home on the basis of physical therapy frequency for patients who were hospitalized.DESIGN: A predictive model was developed using retrospective cohort data collected between April 2017 and August 2022, with external validation conducted in a separate sample.SETTING: The setting was a large health system.PARTICIPANTS: Participants were adult patients who were hospitalized and received physical therapy.MAIN OUTCOME AND MEASURES: Predictors were extracted from the electronic health record and included demographics, clinical characteristics, and therapist-entered variables such as home set-up and prehospital level of function. Physical therapy frequency was quantified as once daily, defined as ≥5 times per week. The outcome was discharge to home. Variables were included in the final multivariable logistic regression model on the basis of associations with physical therapy frequency and/or outcome and clinical relevance. Calibration and discrimination of the models were assessed.RESULTS: The development sample included 205,659 adult patient (average age = 72.2 [SD = 14.3] years; 55.3% female) hospitalizations, with 52.5% of patients receiving physical therapy daily and an overall proportion of 67.1% being discharged to home. The final multivariable model included 8 variables, with good calibration and discrimination. Internal validity was established with an optimism-corrected concordance statistic of 0.874 (95% CI = 0.872-0.875). The external sample included 102,311 patient (average age = 67.7 [SD = 16.5] years; 50.9% female) admissions, with 64.5% of patients receiving physical therapy daily and 77.8% being discharged to home. Predictive performance was high (calibration slope = 0.908), and discrimination was good (concordance statistic = 0.851).CONCLUSIONS AND RELEVANCE: This study developed and externally validated the underlying prediction model for a clinical decision support tool, termed Physical Therapy Frequency Clinical Decision Support Tool (PT-PENCIL), to identify patients most likely to benefit from daily physical therapy to discharge to home. Future work will evaluate the implementation of PT-PENCIL to determine its effect on patient-centered outcomes.PMID:40652311 | DOI:10.1093/ptj/pzaf093