• Marcos Estupiñán-Ramírez, Rita Tristancho-Ajamil, María Consuelo Company-Sancho, and Hilda Sánchez-Janáriz.
• Servicio de Atención Primaria. Dirección General de Programas Asistenciales. Servicio Canario de la Salud, Las Palmas de Gran Canaria, España. Electronic address: mestrams@gobiernodecanarias.org.
• Gac Sanit. 2019 Jan 1; 33 (1): 60-65.

ObjectiveTo compare the concordance of complexity weights between Clinical Risk Groups (CRG) and Adjusted Morbidity Groups (AMG). To determine which one is the best predictor of patient admission. To optimise the method used to select the 0.5% of patients of higher complexity that will be included in an intervention protocol.MethodCross-sectional analytical study in 18 Canary Island health areas, 385,049 citizens were enrolled, using sociodemographic variables from health cards; diagnoses and use of healthcare resources obtained from primary health care electronic records (PCHR) and the basic minimum set of hospital data; the functional status recorded in the PCHR, and the drugs prescribed through the electronic prescription system. The correlation between stratifiers was estimated from these data. The ability of each stratifier to predict patient admissions was evaluated and prediction optimisation models were constructed.ResultsConcordance between weights complexity stratifiers was strong (rho = 0.735) and the correlation between categories of complexity was moderate (weighted kappa = 0.515). AMG complexity weight predicts better patient admission than CRG (AUC: 0.696 [0.695-0.697] versus 0.692 [0.691-0.693]). Other predictive variables were added to the AMG weight, obtaining the best AUC (0.708 [0.707-0.708]) the model composed by AMG, sex, age, Pfeiffer and Barthel scales, re-admissions and number of prescribed therapeutic groups.Conclusionsstrong concordance was found between stratifiers, and higher predictive capacity for admission from AMG, which can be increased by adding other dimensions.Copyright © 2017 SESPAS. Publicado por Elsevier España, S.L.U. All rights reserved.

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