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      Los grupos de morbilidad ajustados: nuevo agrupador de morbilidad poblacional de utilidad en el ámbito de la atención primaria Translated title: Adjusted morbidity groups: A new multiple morbidity measurement of use in Primary Care

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          Resumen

          Se ha desarrollado un agrupador de morbilidad adaptado a nuestro entorno sanitario que permite clasificar a la población en 6 grupos de morbilidad, divididos a su vez en 5 niveles de complejidad, más un grupo de población sana; de este modo la población queda agrupada en 31 categorías mutuamente excluyentes.

          Se presentan resultados de la estratificación en Cataluña.

          Los grupos de morbilidad ajustados (GMA) son un agrupador de morbilidad comparable a otros existentes en el mercado, pero desarrollado con los datos de nuestro sistema sanitario. Permite generar una adecuada estratificación poblacional y es capaz de identificar a poblaciones diana. Muestra buenos resultados explicativos en indicadores de uso de recursos sanitarios.

          El Ministerio de Sanidad está impulsando la implantación del agrupador en el Sistema Nacional de Salud.

          Translated abstract

          The Adjusted Morbidity Groups (GMA) is a new morbidity measurement developed and adapted to the Spanish healthcare System. It enables the population to be classified into 6 morbidity groups, and in turn divided into 5 levels of complexity, along with one healthy population group. Consequently, the population is divided into 31 mutually exclusive categories.

          The results of the stratification in Catalonia are presented. GMA is a method for grouping morbidity that is comparable to others in the field, but has been developed with data from the Spanish health system. It can be used to stratify the population and to identify target populations. It has good explanatory and predictive results in the use of health resources indicators.

          The Spanish Ministry of Health is promoting the introduction of the GMA into the National Health System.

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          Most cited references5

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          Development and application of a population-oriented measure of ambulatory care case-mix.

          This article describes a new case-mix methodology applicable primarily to the ambulatory care sector. The Ambulatory Care Group (ACG) system provides a conceptually simple, statistically valid, and clinically relevant measure useful in predicting the utilization of ambulatory health services within a particular population group. ACGs are based on a person's demographic characteristics and their pattern of disease over an extended period of time, such as a year. Specifically, the ACG system is driven by a person's age, sex, and ICD-9-CM diagnoses assigned during patient-provider encounters; it does not require any special data beyond those collected routinely by insurance claims systems or encounter forms. The categorization scheme does not depend on the presence of specific diagnoses that may change over time; rather it is based on broad clusters of diagnoses and conditions. The presence or absence of each disease cluster, along with age and sex, are used to classify a person into one of 51 ACG categories. The ACG system has been developed and tested using computerized encounter and claims data from more than 160,000 continuous enrollees at four large HMOs and a state's Medicaid program. The ACG system can explain more than 50% of the variance in ambulatory resource use if used retrospectively and more than 20% if applied prospectively. This compares with 6% when age and sex alone are used. In addition to describing ACG development and validation, this article also explores some potential applications of the system for provider payment, quality assurance, utilization review, and health services research, particularly as it relates to capitated settings.
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            Ambulatory care groups: a categorization of diagnoses for research and management.

            This article describes a case-mix measure for application in ambulatory populations. The method is based primarily on categorization of diagnoses according to their likelihood of persistence. Fifty-one combinations (the ambulatory care groups or ACGs) result from applying multivariate techniques to maximize variance explained in use of services and ambulatory care charges. The method is tested in four different HMOs and a large Medicaid population. The percentage of the population in each of the 51 categories is similar across the HMOs; the Medicaid population has higher burdens of morbidity as measured by more numerous types of diagnoses. Mean visit rates for individuals within each of the 51 morbidity categories are generally similar across the five facilities, but these visit rates vary markedly from one category to another, even within groupings that are similar in the number of types of diagnoses within them. Visit rates for individuals who stay in the same ACG were similar from one year to the next. The ACG system is found useful in predicting both concurrent and subsequent ambulatory care use and charges as well as subsequent morbidity. It provides a way to specify case mix in enrolled populations for research as well as administration and reimbursement for ambulatory care.
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              Multimorbidity in primary care: developing the research agenda.

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                Author and article information

                Contributors
                Journal
                Aten Primaria
                Aten Primaria
                Atencion Primaria
                Elsevier
                0212-6567
                1578-1275
                03 August 2016
                December 2016
                03 August 2016
                : 48
                : 10
                : 674-682
                Affiliations
                [a ]Instituto Catalán de la Salud, Departamento de Salud, Generalidad de Cataluña, Barcelona, España
                [b ]Servicio Catalán de la Salud, Departamento de Salud, Generalidad de Cataluña, Barcelona, España
                Author notes
                [* ]Autor para correspondencia. dmonterde@ 123456gencat.cat
                [◊]

                Los nombres de los componentes del grupo colaborativo GMA están relacionados en el anexo.

                Article
                S0212-6567(16)30210-4
                10.1016/j.aprim.2016.06.003
                6879171
                27495004
                02ddc945-df25-4b32-8f0d-d6bd201b101c
                © 2016 Elsevier España, S.L.U.

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 26 January 2016
                : 3 June 2016
                Categories
                Artículo especial

                multimorbilidad,cronicidad,agrupador de morbilidad,atención primaria,multiple morbidity,chronic diseases,morbidity measurements,primary care

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