• Montse Clèries, David Monterde, Emili Vela, Àlex Guarga, Luis García Eroles, Pol Pérez Sust, and Grupo de validación.
• Unidad de Información y Conocimiento, Servicio Catalán de la Salud, Departamento de Salud de la Generalidad de Cataluña, Barcelona, España. Electronic address: mcleries@catsalut.cat.
• Aten Primaria. 2020 Feb 1; 52 (2): 9610396-103.

IntroductionAdjusted Morbidity Groups (GMAs) and the Clinical Risk Groups (CRGs) are population morbidity based stratification tools which classify patients into mutually exclusive categories.ObjetiveTo compare the stratification provided by the GMAs, CRGs and that carried out by the evaluators according to the levels of complexity.DesignRandom sample stratified by morbidity risk.LocationCatalonia.ParticipantsForty paired general practitioners in the primary care, matched pairs.InterventionsEach pair of evaluators had to review 25 clinical records.Main OutputsThe concordance by evaluators, and between the evaluators and the results obtained by the 2 morbidity tools were evaluated according to the kappa index, sensitivity, specificity, and positive and negative predicted values.ResultsThe concordance between general practitioners pairs was around the kappa value 0.75 (mean value=0.67), between the GMA and the evaluators was similar (mean value=0.63), and higher than for the CRG (mean value=0.35). The general practitioners gave a score of 7.5 over 10 to both tools, although for the most complex strata, according to the professionals' assignment, the GMA obtained better scores than the CRGs. The professionals preferred the GMAs over the CRGs. These differences increased with the complexity level of the patients according to clinical criteria. Overall, less than 2% of serious classification errors were found by both groupers.ConclusionThe evaluators considered that both grouping systems classified the studied population satisfactorily, although the GMAs showed a better performance for more complex strata. In addition, the clinical raters preferred the GMAs in most cases.Copyright © 2019 The Author. Publicado por Elsevier España, S.L.U. All rights reserved.

12 keywords...

hide…