Development and validation of predictive MoSaiCo (Modello Statistico Combinato) on emergency admissions: can it also identify patients at high risk of frailty?

The prospective historical cohort study develops and validates a method of identifying patients at high risk of emergency admission to hospital in the population of the Province of Ravenna (no. = 296 641). The main outcome measure is: emergency hospital admission analyzed using multivariate logistic regression (MoSaiCo - Modello Statistico Combinato). To validate the findings, the coefficients for 30 most powerful variables found on half of the population (derivation data set) were then applied to the rest of the population (validation data set). The key predicting factors included some demographic variables, social variables, clinical variables and use of health/social services. Discriminatory power and validation both reached good results. Risk score increases when variables indicating the individual vulnerability raise. The predictive frailty risk resulting from MoSaiCo allows to stratify the population, to organize care services, to provide a practical planning tool in the field of case management and management of frail patients.