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Objective The objective of this study was to determine the ability of the Activity Measure for Post-Acute Care “6-Clicks” Basic Mobility Short Form to predict patient discharge destination (home vs postacute care [PAC] facility) from the cardiac intensive care unit (ICU), including patients from the cardiothoracic surgical ICU and coronary care unit. Methods This retrospective cohort study utilized electronic medical records of patients in cardiac ICU (n = 359) in an academic teaching hospital in the southeastern region of United States from September 1, 2017, through August 31, 2018. Results The median interquartile range age of the sample was 68 years (75–60), 55% were men, the median interquartile range 6-Clicks score was 16 (20–12) at the physical therapist evaluation, and 79% of the patients were discharged to home. Higher score on 6-Clicks indicates improved function. A prediction model was constructed based on a machine learning approach using a classification tree. The classification tree was constructed and evaluated by dividing the sample into a train-test split using the Leave-One-Out cross-validation approach. The classification tree split the data into 4 distinct groups along with their predicted outcomes. Patients with a 6-Clicks score >15.5 and a score between 11.5 and 15.5 with primary insurance other than Medicare were discharged to home. Patients with a 6-Clicks score between 11.5 and 15.5 with Medicare insurance and those with a score ≤11.5 were discharged to a PAC facility. Conclusion Patients with lower 6-Clicks scores were more likely to be discharged to a PAC facility. Patients without Medicare insurance had to be significantly lower functioning, as indicated by lower 6-Clicks scores for PAC facility placement than those with Medicare insurance. Impact The ability of 6-Clicks along with primary insurance to determine discharge destination allows for early discharge planning from cardiac ICUs.

Background The proposed Centers for Medicare & Medicaid Services (CMS) 30-day readmission risk standardization models for inpatient rehabilitation facilities establish readmission risk for patients at admission based on a limited set of core variables. Considering functional recovery during the rehabilitation stay may help clinicians further stratify patient groups at high risk for hospital readmission. Objective The purpose of this study was to identify variables in the full administrative medical record, particularly in regard to physical function, that could help clinicians further discriminate between patients who are and are not likely to be readmitted to an acute care hospital within 30 days of rehabilitation discharge. Design This study used an observational cohort with a 30-day follow-up of Medicare patients who were deconditioned and had medically complex diagnoses and who were receiving postacute inpatient rehabilitation in 2010 to 2011. Methods Patients in the highest risk quartile for readmission (N=25,908) were selected based on the CMS risk prediction model. Hierarchical generalized linear models were built to compare the relative effectiveness of motor functional status ratings in predicting 30-day readmission. Classification and regression tree analysis was used to create a hierarchical order among predictors based on variable importance in classifying patients based on readmission status. Results Approximately 34% of patients in the high-risk quartile were readmitted within 30 days. Functional outcomes and rehabilitation length of stay were the best predictors of 30-day rehospitalization. A 3-variable algorithm classified 4 clinical subgroups with readmission probabilities ranging from 28% to 75%. Limitations Although planned readmissions were accounted for in the outcome, potentially preventable readmissions were not distinguished from unpreventable readmissions. Conclusion For older patients who are deconditioned and have medically complex diagnoses admitted to postacute inpatient rehabilitation, information on functional status measures that are easily monitored by health care providers may improve plans for care transition and reduce the risk of hospital readmission.