• Carmen Arias-López, Mª Pilar Rodrigo Val, Laura Casaña Fernández, Lydia Salvador Sánchez, Ana Dorado Díaz, and Marcos Estupiñán Ramírez.
• Subdirección General de Calidad e Innovación. Ministerio de Sanidad. Madrid. España.
• Rev Esp Salud Publica. 2020 Jul 3; 94.

ObjectiveThis work was performed in order to get objective elements of judgment that support the improvement of a national population morbidity grouper based in the Adjusted Morbidity Groups (AMG). The study compared the performance in terms of predictive power on certain health and resource outcomes, in between the AMG and several existing morbidity groupers (ACG®, Adjusted Clinical Groups and CRG®, Clinical Risk Group) used in some Autonomous Regions in Spain (Aragón, Canarias y Castilla y León).MethodsCross-sectional analytical study in entitled/insured population with respect to rights of healthcare. Predictive capacity of the complexity weight obtained with the different stratification tools in the first year of the study period was evaluated using a simple classification method that compares the areas under the curves ROC for the following outcomes that occurred in the second year of the study period: Probability of death; probability of having at least one urgent hospital admission; total number of visits to hospital emergencies; total number of visits to primary care; total number of visits to hospital care and spending in pharmacy.ResultsThe results showed that AMG complexity weight were good predictors for almost all the analyzed outcomes (AUC ROC>0.7; p<0.05), for the different Autonomous Regions and compared to ACG® or CRG®. Only for the outcome of visits to hospital emergencies in Aragon and Canarias; and visits to specialized care in Aragon, the predictive power was weak for all the compared stratification tools.ConclusionsGMA® is a population stratification tool adequate and as useful as others existing morbidity groupers.

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