OBJECTIVES: to develop and validate a predictive model of mortality or emergency hospitalization in all subjects aged 65 years and over. DESIGN: cohort study based on 9 different databases linked with each other. SETTING AND PARTICIPANTS: the model was developed on the population aged 65 years and over resident at 01.01.2011 for at least two years in the city of Bologna (Emilia-Romagna Region, Northern Italy); 96,000 persons were included. MAIN OUTCOME MEASURES: the outcome was defined in case of emergency hospitalization or death during the one-year follow-up and studied with a logistic regression model. The predictive ability of the model was evaluated by using the area under the Roc curve, the Hosmer-Lemeshow test, and the Brier score in the derivation sample (2/3 of the population). These tests were repeated in the validation sample (1/3 of the population) and in the population of Bologna aged 65 years and over on 01.01.2012, after applying the coefficients of the variables obtained in the derivation model. By using the regression coefficients, a frailty index (risk score) was calculated for each subject later categorized in risk classes. RESULTS: the model is composed of 28 variables and has good predictive abilities. The area under the Roc curve of the derivation sample is 0.77, the Hosmer-Lemeshow test is not significant, and the Brier score is 0.11. Similar performances are obtained in the other two samples. With increasing risk class, the mean age, number of hospitalizations, emergency room service consultations, and multiple drug prescriptions increase, while the average income decreases. CONCLUSION: the model has good predictive ability. The frailty index can be used to support a proactive medicine and stratify the population, plan clinical and preventive activities or identify the potential beneficiaries of specific health promotion projects.
OBJECTIVES: to develop and validate a predictive model of mortality or emergency hospitalization in all subjects aged 65 years and over. DESIGN: cohort study based on 9 different databases linked with each other. SETTING AND PARTICIPANTS: the model was developed on the population aged 65 years and over resident at 01.01.2011 for at least two years in the city of Bologna (Emilia-Romagna Region, Northern Italy); 96,000 persons were included. MAIN OUTCOME MEASURES: the outcome was defined in case of emergency hospitalization or death during the one-year follow-up and studied with a logistic regression model. The predictive ability of the model was evaluated by using the area under the Roc curve, the Hosmer-Lemeshow test, and the Brier score in the derivation sample (2/3 of the population). These tests were repeated in the validation sample (1/3 of the population) and in the population of Bologna aged 65 years and over on 01.01.2012, after applying the coefficients of the variables obtained in the derivation model. By using the regression coefficients, a frailty index (risk score) was calculated for each subject later categorized in risk classes. RESULTS: the model is composed of 28 variables and has good predictive abilities. The area under the Roc curve of the derivation sample is 0.77, the Hosmer-Lemeshow test is not significant, and the Brier score is 0.11. Similar performances are obtained in the other two samples. With increasing risk class, the mean age, number of hospitalizations, emergency room service consultations, and multiple drug prescriptions increase, while the average income decreases. CONCLUSION: the model has good predictive ability. The frailty index can be used to support a proactive medicine and stratify the population, plan clinical and preventive activities or identify the potential beneficiaries of specific health promotion projects.