BACKGROUND: The objectives of the study were to estimate the incidence of readmission one month after discharge, to determine the proportion of planned readmissions and of those avoidable, and to identify risk factors associated with early readmissions in elderly admitted to an acute geriatric unit. METHODS: A prospective study was conducted on a sample of 322 patients, 75 years of age or older, discharged from an acute geriatric service. A phone follow-up was realized one month after discharge. A multivariate logistic regression model was used to identify risk factors for readmission. RESULTS: Global incidence of early readmission was 16.2% (that is 50 rehospitalizations), 18.0% of which were planned. Among the 21 readmissions to the same service, five were avoidable according to the Appropriateness Evaluation Protocol. Logistic regression analysis identified three patient characteristics that were independent predictors of early readmission, which were: a need of help for locomotion (OR=4.38, p=0.002), a negative answer to the question "do you feel that your life is empty?" (OR=2.22, p=0.02) and a short length of stay (p<0.02). CONCLUSION: A better knowledge of risk factors should allow targeting patients at high risk of early hospital readmission, which should profit by preventive interventions during the first hospitalization. Two domains of possible action were identified in this study: a sufficient length of stay and a better attention to patients with reduced autonomy, especially for those who go back home after discharge.
BACKGROUND: The objectives of the study were to estimate the incidence of readmission one month after discharge, to determine the proportion of planned readmissions and of those avoidable, and to identify risk factors associated with early readmissions in elderly admitted to an acute geriatric unit. METHODS: A prospective study was conducted on a sample of 322 patients, 75 years of age or older, discharged from an acute geriatric service. A phone follow-up was realized one month after discharge. A multivariate logistic regression model was used to identify risk factors for readmission. RESULTS: Global incidence of early readmission was 16.2% (that is 50 rehospitalizations), 18.0% of which were planned. Among the 21 readmissions to the same service, five were avoidable according to the Appropriateness Evaluation Protocol. Logistic regression analysis identified three patient characteristics that were independent predictors of early readmission, which were: a need of help for locomotion (OR=4.38, p=0.002), a negative answer to the question "do you feel that your life is empty?" (OR=2.22, p=0.02) and a short length of stay (p<0.02). CONCLUSION: A better knowledge of risk factors should allow targeting patients at high risk of early hospital readmission, which should profit by preventive interventions during the first hospitalization. Two domains of possible action were identified in this study: a sufficient length of stay and a better attention to patients with reduced autonomy, especially for those who go back home after discharge.