ABSTRACT
Objetivo: Analizar en el contexto de una Zona Básica de Salud (ZBS) la prevalencia de los factores de riesgo cardiovascular (FRCV) y el impacto que generan en la morbilidad y el consumo de recursos sanitarios en la población estratificada según el sistema Clinical Risk Groups (CRG) en Atención Primaria (AP), con la finalidad de identificar la población con multimorbilidad para aplicar medidas preventivas, así como aquella que genera más carga asistencial y necesidades sociales. Diseño: Estudio observacional, de corte transversal y ámbito poblacional para una ZBS durante el año 2013. Emplazamiento: Departamento de salud de Castellón, Comunidad Valenciana (CV). Incluye asistencia ambulatoria en AP y especializada. Participantes: Todos los ciudadanos dados de alta en el Sistema de Información Poblacional (SIP), N = 32.667. Mediciones: Del sistema informatizado Abucasis obtuvimos las variables demográficas, clínicas y de consumo de recursos sanitarios. Consideramos la prevalencia de los FRCV a partir de la presencia o ausencia de los códigos diagnósticos CIE.9.MC. Se analizó la relación de los FRCV con los 9 estados de salud CRG, y se realizó un análisis predictivo con el modelo de regresión logística para evaluar la capacidad explicativa de cada variable. Además, se obtuvo mediante regresión multivariante un modelo explicativo del gasto farmaceútico ambulatorio. Resultados: La población del estado de salud CRG 4 en adelante tenía multimorbilidad. Los estados de salud CRG 7 y CRG 6 tienen mayor prevalencia de FRCV. Fue predictivo que a mayor morbilidad, mayor consumo de recursos, mediante OR superiores a la media, p < 0,05 e intervalos de confianza del 95%. Se observó que un 59,8% del gasto farmacéutico ambulatorio quedaba explicado por el sistema CRG y todos los FRCV (p < 0,05 y R2 corregido = 0,598). En cuanto al efecto de los FRCV sobre los estados de salud CRG, hubo asociación significativa (p < 0,05) para la alteración de la glucemia, dislipidemia e HTA en todos los estados CRG. Conclusiones: El estudio de los FRCV en una población estratificada mediante el sistema CRG identifica y predice dónde se genera mayor impacto en la morbilidad y consumo de recursos sanitarios. Nos permite conocer los grupos de pacientes en quienes desarrollar estrategias de prevención y cronicidad. A nivel de la práctica clínica se aporta un nuevo concepto de multimorbilidad, definido a partir del estado de salud CRG 4 en adelante
Objective: To analyze the prevalence of Cardiovascular Risk Factors (CVRF) in the context of a Basic Health Area and the impact they generate on morbidity and consumption of healthcare resources in the stratified population according to the Clinical System Risk Groups (CRG) in Primary Care, with the purpose of identifying the population with multimorbidity to apply preventive measures, as well as the one that generates the highest care burden and social needs. Design: Observational, cross-sectional and population-based study for a basic health area during 2013. Location: Department of Health 2 (Castellón), Comunidad Valenciana (CV). Includes outpatient care in Primary Care and specialized. Participants: All citizens registered in the Population Information System, N = 32,667. Measurements: From the computerized system Abucasis we obtained the demographic, clinical and consumption variables of health resources. We consider the prevalence of CVRF based on the presence or absence of the ICD.9.MC diagnostic codes. The relationship of the CVRF with the 9 CRG health states was analyzed and a predictive analysis was performed with the logistic regression model to evaluate the explanatory capacity of each variable. In addition, an explanatory model of ambulatory pharmaceutical expenditure was obtained through multivariate regression. Results: The population of health status CRG4 and above had multimorbidity. The CRG7 and 6 health states have a higher prevalence of CVRF; it was predictive that the higher the morbidity, the greater the consumption of resources through OR above the mean, p < 0.05 and the 95% confidence intervals. It was observed that 59.8% of ambulatory pharmaceutical expenditure was explained by the CRG system and all the CVRF (p < 0.05 and R2 corrected = 0.598). Regarding the effect of the CVRF on the CRG health states, there was a significant association (p < 0.05) for the alteration of blood glucose, dyslipidemia and HBP in all the CRG states. Conclusions: The study of CVRF in a stratified population using the CRG system identifies and predicts where the greatest impact on morbidity and consumption of healthcare resources is generated. It allows us to know the groups of patients where to develop prevention and chronicity strategies. At the level of clinical practice, a new concept of multimorbidity is provided, defined from the state of health CRG 4 and above
Subject(s)
Humans , Male , Female , Middle Aged , Cardiovascular Diseases/prevention & control , Primary Health Care/economics , Health Care Costs/statistics & numerical data , Drug Costs/statistics & numerical data , Risk Factors , Health Care Rationing/statistics & numerical data , Cross-Sectional Studies , Risk Groups , Risk Adjustment/organization & administration , Health Status , Multiple Chronic Conditions/epidemiologyABSTRACT
BACKGROUND: Increased life expectancy in Western societies does not necessarily mean better quality of life. To improve resources management, management systems have been set up in health systems to stratify patients according to morbidity, such as Clinical Risk Groups (CRG). The main objective of this study was to evaluate the effect of multimorbidity on health-related quality of life (HRQL) in primary care. METHODS: An observational cross-sectional study, based on a representative random sample (n = 306) of adults from a health district (N = 32,667) in east Spain (Valencian Community), was conducted in 2013. Multimorbidity was measured by stratifying the population with the CRG system into nine mean health statuses (MHS). HRQL was assessed by EQ-5D dimensions and the EQ Visual Analogue Scale (EQ VAS). The effect of the CRG system, age and gender on the utility value and VAS was analysed by multiple linear regression. A predictive analysis was run by binary logistic regression with all the sample groups classified according to the CRG system into the five HRQL dimensions by taking the "healthy" group as a reference. Multivariate logistic regression studied the joint influence of the nine CRG system MHS, age and gender on the five EQ-5D dimensions. RESULTS: Of the 306 subjects, 165 were female (mean age of 53). The most affected dimension was pain/discomfort (53%), followed by anxiety/depression (42%). The EQ-5D utility value and EQ VAS progressively lowered for the MHS with higher morbidity, except for MHS 6, more affected in the five dimensions, save self-care, which exceeded MHS 7 patients who were older, and MHS 8 and 9 patients, whose condition was more serious. The CRG system alone was the variable that best explained health problems in HRQL with 17%, which rose to 21% when associated with female gender. Age explained only 4%. CONCLUSIONS: This work demonstrates that the multimorbidity groups obtained by the CRG classification system can be used as an overall indicator of HRQL. These utility values can be employed for health policy decisions based on cost-effectiveness to estimate incremental quality-adjusted life years (QALY) with routinely e-health data. Patients under 65 years with multimorbidity perceived worse HRQL than older patients or disease severity. Knowledge of multimorbidity with a stronger impact can help primary healthcare doctors to pay attention to these population groups.
Subject(s)
Health Status , Multimorbidity , Primary Health Care/statistics & numerical data , Quality of Life , Adult , Aged , Case-Control Studies , Cross-Sectional Studies , Female , Humans , Logistic Models , Male , Middle Aged , SpainABSTRACT
OBJECTIVE: To analyze the prevalence of Cardiovascular Risk Factors (CVRF) in the context of a Basic Health Area and the impact they generate on morbidity and consumption of healthcare resources in the stratified population according to the Clinical System Risk Groups (CRG) in Primary Care, with the purpose of identifying the population with multimorbidity to apply preventive measures, as well as the one that generates the highest care burden and social needs. DESIGN: Observational, cross-sectional and population-based study for a basic health area during 2013. LOCATION: Department of Health 2 (Castellón), Comunidad Valenciana (CV). Includes outpatient care in Primary Care and specialized. PARTICIPANTS: All citizens registered in the Population Information System, N=32,667. MEASUREMENTS: From the computerized system Abucasis we obtained the demographic, clinical and consumption variables of health resources. We consider the prevalence of CVRF based on the presence or absence of the ICD.9.MC diagnostic codes. The relationship of the CVRF with the 9 CRG health states was analyzed and a predictive analysis was performed with the logistic regression model to evaluate the explanatory capacity of each variable. In addition, an explanatory model of ambulatory pharmaceutical expenditure was obtained through multivariate regression. RESULTS: The population of health status CRG4 and above had multimorbidity. The CRG7 and 6 health states have a higher prevalence of CVRF; it was predictive that the higher the morbidity, the greater the consumption of resources through OR above the mean, p<0.05 and the 95% confidence intervals. It was observed that 59.8% of ambulatory pharmaceutical expenditure was explained by the CRG system and all the CVRF (p<0.05 and R2 corrected=0.598). Regarding the effect of the CVRF on the CRG health states, there was a significant association (p<0.05) for the alteration of blood glucose, dyslipidemia and HBP in all the CRG states. CONCLUSIONS: The study of CVRF in a stratified population using the CRG system identifies and predicts where the greatest impact on morbidity and consumption of healthcare resources is generated. It allows us to know the groups of patients where to develop prevention and chronicity strategies. At the level of clinical practice, a new concept of multimorbidity is provided, defined from the state of health CRG 4 and above.
