OBJECTIVE: To examine variations in the frequency of discharge of elderly patients to postacute care facilities across multiple intensive care units and identify the influence of institutional and patient factors on the frequency of postacute care discharge. DESIGN: Observational cohort study. SETTING: Consecutive admissions from 65 intensive and coronary care units in 24 US hospitals during 2002-2008. Each hospital had a clinical information system in place. PATIENTS: A total of 13,370 admissions in patients aged≥65 yrs who were alive at hospital discharge and met inclusion criteria. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Demographic, clinical, diagnostic, and physiological variables were obtained on all patients. In addition, information for each hospital and intensive care unit was recorded. Among hospital survivors, 46.2% were discharged to postacute care facilities with a range of 8.8-77.8%. A multivariable logistic regression model was developed that predicted discharge to a postacute care facility. The major variables affecting postacute care discharge were diagnosis, day 5 physiology, and day 5 therapy; these variables accounted for 61% of the model's explanatory power. Patient age, hospital bed size, teaching status, and intensive care unit type also affected postacute care discharge. Physiology and therapy on day 1 had little impact on postacute care discharge. The model accounted for only 31% of the variation in rates across intensive care units, indicating that unmeasured factors play a part in dictating discharge location. CONCLUSION: Discharge of elderly intensive care unit patients to postacute care facilities varies widely by institution. These variations are only partially explained by differences in patient and institutional characteristics and are affected more by diagnosis and physiology on day 5, respectively. Unmeasured factors such as admission from a postacute care facility, postacute care availability, patient preferences, and socioeconomic factors may account for unexplained variations in postacute care discharge.
OBJECTIVE: To examine variations in the frequency of discharge of elderly patients to postacute care facilities across multiple intensive care units and identify the influence of institutional and patient factors on the frequency of postacute care discharge. DESIGN: Observational cohort study. SETTING: Consecutive admissions from 65 intensive and coronary care units in 24 US hospitals during 2002-2008. Each hospital had a clinical information system in place. PATIENTS: A total of 13,370 admissions in patients aged≥65 yrs who were alive at hospital discharge and met inclusion criteria. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Demographic, clinical, diagnostic, and physiological variables were obtained on all patients. In addition, information for each hospital and intensive care unit was recorded. Among hospital survivors, 46.2% were discharged to postacute care facilities with a range of 8.8-77.8%. A multivariable logistic regression model was developed that predicted discharge to a postacute care facility. The major variables affecting postacute care discharge were diagnosis, day 5 physiology, and day 5 therapy; these variables accounted for 61% of the model's explanatory power. Patient age, hospital bed size, teaching status, and intensive care unit type also affected postacute care discharge. Physiology and therapy on day 1 had little impact on postacute care discharge. The model accounted for only 31% of the variation in rates across intensive care units, indicating that unmeasured factors play a part in dictating discharge location. CONCLUSION: Discharge of elderly intensive care unit patients to postacute care facilities varies widely by institution. These variations are only partially explained by differences in patient and institutional characteristics and are affected more by diagnosis and physiology on day 5, respectively. Unmeasured factors such as admission from a postacute care facility, postacute care availability, patient preferences, and socioeconomic factors may account for unexplained variations in postacute care discharge.
Authors: Matthew R Baldwin; Wazim R Narain; Hannah Wunsch; Neil W Schluger; Joseph T Cooke; Mathew S Maurer; John W Rowe; David J Lederer; Peter B Bach Journal: Chest Date: 2013-04 Impact factor: 9.410