Three events can be considered of major importance for patients after a hospitalization in an AGU: death, hospital readmission, and institutionalization. Current published data do not allow the clinician to simultaneously estimate the risk of hospital readmission, institutionalization and death of an older patient according to his/her characteristics and various complications that occurred during the hospitalization. However, clinicians often need to estimate these risks at hospital discharge to adapt their therapeutic choices, their proposals post-hospital care, and provide reliable and fair information to the patient and his relatives. Estimating simultaneously the hazard for each of these three events can be complex. Indeed, a death event hinder the observation of re-hospitalization or institutionalization if death occurs before these events. The death should be considered a competing risk in these analyzes. Hospital readmission may modify the risk of death or institutionalization and should be considered as an intermediate factor for these event. This complexity cannot be accounted with classical statistical models, like logistic regression models. The purpose of this study is to use more appropriate statistical models (multi-state models) to better estimate simultaneously the risks of hospital readmission, institutionalization, and death of a patient given after hospitalization in AGU, and to show that accuracy of these estimations can be improved by taking into account complications that occurred during the stay in AGU.
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Number of death after discharge
Timeframe: 3 months