A 14-Year Longitudinal Analysis of Healthcare Expenditure on Dementia and Related Factors (DEMENCOST Study).

BACKGROUND: The large number of dementia cases produces a great pressure on health and social care services, which requires efficient planning to meet the needs of patients through infrastructure, equipment, and financial, technical, and personal resources adjusted to their demands. Dementia analysis requires studies with a very precise patient characterization of both the disease and comorbidities present, and long-term follow-up of patients in clinical aspects and patterns of resource utilization and costs generated. OBJECTIVE: To describe and quantify direct healthcare expenditure and its evolution from three years before and up to ten years after the diagnosis of dementia, compared to a matched group without dementia. METHODS: Retrospective cohort design with follow-up from 6 to 14 years. We studied 996 people with dementia (PwD) and 2,998 controls matched for age, sex, and comorbidity. This paper adopts the provider's perspective as the perspective of analysis and refers to the costs actually incurred in providing the services. Aggregate costs and components per patient per year were calculated and modelled. RESULTS: Total health expenditure increases in PwD from the year of diagnosis and in each of the following 7 years, but not thereafter. Health status and mortality are factors explaining the evolution of direct costs. Dementia alone is not a statistically significant factor in explaining differences between groups. CONCLUSION: The incremental direct cost of dementia may not be as high or as long as studies with relatively short follow-up suggest. Dementia would have an impact on increasing disease burden and mortality.

Evaluación de la efectividad de un programa de atención integrada y proactiva a pacientes crónicos complejos / Assessment of the effectiveness of a proactive and integrated healthcare programme for chronic complex patients

Objetivo: Evaluar la efectividad de un programa de atención integrada y proactiva para adecuar el uso de recursos sanitarios en pacientes crónicos complejos con riesgo de alto consumo según un modelo predictivo basado en morbilidad y utilización previa. Métodos: Ensayo clínico controlado aleatorizado con grupo control enmascarado, grupo de intervención parcial informado en la historia clínica y grupo de intervención total informado además a atención primaria, en una organización sanitaria integrada con 128.281 residentes en 2011. Variables dependientes: visitas de atención primaria, urgencias hospitalarias, hospitalización, coste farmacéutico y muerte. Variables independientes: grupo de intervención, edad, sexo, área básica, morbilidad (según grupo de riesgo clínico) y recurrencia como paciente crónico complejo. Análisis bivariado con ANOVA y t de Student, y multivariado mediante regresión logística y regresión lineal múltiple, con un nivel de confianza del 95%. Resultados: Se incluyeron 4.236 y 4.223 pacientes crónicos complejos en el primer y el segundo año de intervención, respectivamente. El 72% eran recurrentes. Edad media: 73,2 años. El 54,2% eran mujeres. Más del 70% tenían al menos dos enfermedades crónicas. El número de visitas a atención primaria fue significativamente mayor en el grupo de intervención total respecto al grupo de intervención parcial y el grupo control. La intervención solo tuvo un efecto significativo independiente en las estancias hospitalarias, que fueron menos en el grupo de intervención parcial. Este efecto diferencial se dio en el primer año y en los pacientes crónicos complejos nuevos del segundo año. Los indicadores asistenciales generales de la organización sanitaria integrada eran buenos, antes y durante la intervención. Conclusiones: Una buena situación general previa y mantenida, y una inevitable contaminación entre grupos, dificultaron la demostración de efectividad marginal del programa (AU)

Objective: To assess the effectiveness of a proactive and integrated care programme to adjust the use of health resources by chronic complex patients (CCP) identified as potential high consumers according to a predictive model based on prior use and morbidity. Methods: Randomized controlled clinical trial with three parallel groups of CCP: a blinded control group (GC), usual care; a partial intervention group (GIP) reported in the EMR; a total intervention group (GIT), also reported to primary care (PC). Conducted in an integrated health care organization (IHCO), N=128,281 individuals in 2011. Dependent variables: PC visits, emergency attention, hospitalizations, pharmaceutical cost and death. Independent variables: intervention group, age, sex, area of residence, morbidity (by clinical risk group) and recurrence as CCP. Statistical analysis: ANOVA, student's t test; logistic and multiple linear regressions at the 95% confidence level. Results: 4,236 CCP included for the first intervention year and 4,223 for the second; recurrence as CCP 72%. Mean age 73.2 years, 54.2% women and over 70% with 2 or more chronic diseases. The number of PC visits was significantly higher for GIT than for GIP and GC. The hospital stays were significantly lower in GIP. This effect was observed in the first year and in the second year only in the new CCP. The general indicators of the IHCO were good, before and during the intervention. Conclusions: A high standard of quality, previous and during the study, and the inevitable contamination between groups, hindered the assessment of the marginal effectiveness of the program (AU)

[Assessment of the effectiveness of a proactive and integrated healthcare programme for chronic complex patients]. / Evaluación de la efectividad de un programa de atención integrada y proactiva a pacientes crónicos complejos.

OBJECTIVE: To assess the effectiveness of a proactive and integrated care programme to adjust the use of health resources by chronic complex patients (CCP) identified as potential high consumers according to a predictive model based on prior use and morbidity. METHODS: Randomized controlled clinical trial with three parallel groups of CCP: a blinded control group (GC), usual care; a partial intervention group (GIP) reported in the EMR; a total intervention group (GIT), also reported to primary care (PC). Conducted in an integrated health care organization (IHCO), N=128,281 individuals in 2011. Dependent variables: PC visits, emergency attention, hospitalizations, pharmaceutical cost and death. INDEPENDENT VARIABLES: intervention group, age, sex, area of residence, morbidity (by clinical risk group) and recurrence as CCP. STATISTICAL ANALYSIS: ANOVA, student's t test; logistic and multiple linear regressions at the 95% confidence level. RESULTS: 4,236 CCP included for the first intervention year and 4,223 for the second; recurrence as CCP 72%. Mean age 73.2 years, 54.2% women and over 70% with 2 or more chronic diseases. The number of PC visits was significantly higher for GIT than for GIP and GC. The hospital stays were significantly lower in GIP. This effect was observed in the first year and in the second year only in the new CCP. The general indicators of the IHCO were good, before and during the intervention. CONCLUSIONS: A high standard of quality, previous and during the study, and the inevitable contamination between groups, hindered the assessment of the marginal effectiveness of the program.

Los grupos de morbilidad ajustados: un debate pendiente / Adjusted morbidity groups: A pending debate

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¿Son los grupos de morbilidad ajustados concordantes con el criterio clínico de intervención en una estrategia de crónicos? / Are adjusted morbidity groups concordant with the clinical judgment of intervention in a chronic strategy?

No disponible

Efectividad e impacto económico de un programa de atención integrada con soporte de telemedicina a pacientes diabéticos tipo 2 tratados con insulina (estudio GITDIABE) / Effectiveness and economic impact of a program of integrated care with telemedicine support on insulin-treated type 2 diabetic patients (Study GITDIABE)

OBJETIVO: Evaluar si pacientes diabéticos tipo 2 con insulina y autocontrol (DIA) incluidos en un programa de gestión integrada de la diabetes mellitus (DM) con seguimiento telemático alcanzan un grado de control metabólico a los 12 meses mejor que los no incluidos, así como el impacto en la utilización y el coste de servicios sanitarios, consumo de fármacos y tiras reactivas. DISEÑO: Estudio prospectivo de cohortes paralelas. Emplazamiento: Cuatro áreas básicas de salud de una organización sanitaria integrada. PARTICIPANTES: Ciento veintiséis pacientes DIA de 15 o más años en tratamiento con insulina rápida o intermedia con autocontroles: 42 casos y 84 controles emparejados según edad, sexo, grado de control de la DM y perfil de morbilidad. Intervención: Comunicación telemática médico-paciente y volcado de glucemias mediante la plataforma Emminens eConecta®; suministro a domicilio de tiras reactivas según consumo. Controles ocultos, con seguimiento habitual. Mediciones principales: Hemoglobina glucosilada (% HbA1c); percepción de calidad de vida (EuroQol-5 y EsDQOL); riesgo cardiovascular; utilización de recursos sanitarios; consumo de tiras reactivas y medicamentos; gasto sanitario total. RESULTADOS: Reducción de %HbA1c en casos respecto a controles de 0,38% (IC95% −0,89% a 0,12%). Sin diferencias significativas respecto a ninguna de las actividades registradas, ni cambios significativos en la calidad de vida. CONCLUSIONES: Los resultados obtenidos no difieren de otros estudios equiparables. El perfil es de un paciente anciano y pluripatológico que tiene todavía limitaciones tecnológicas. Para superar estas barreras se debería dedicar más tiempo a la formación y a la resolución de problemas tecnológicos

AIM: To evaluate if insulin-treated type 2 diabetic patients with blood glucose self-monitoring (DIA), included in a program of integrated management of diabetes mellitus (DM), achieve a better level of metabolic control with telemedicine support than with conventional support, after 12 months follow-up. The impact on the use and cost of healthcare services, pharmaceutical expenditure, and consumption of test strips for blood glucose, was also assessed. DESIGN: A prospective parallel cohorts study. Field: Four basic health areas of an integrated healthcare organisation. PARTICIPANTS: The study included 126 DIA patients aged 15 or more years, treated with rapid or intermediate Insulin and blood glucose self-monitoring, grouped into 42 cases and 84 controls, matched according to age, sex, level of metabolic control, and morbidity profile. Intervention: Telematics physician-patient communication and download of blood glucose self-monitoring data through the Emminens eConecta® platform; test strips home delivered according to consumption. Hidden controls with usual follow-up. MAIN MEASUREMENTS: Glycosylated haemoglobin (%HbA1c); perception of quality of life (EuroQol-5 and EsDQOL); cardiovascular risk; use of healthcare resources; consumption of test strips; pharmaceutical and healthcare expenditure. RESULTS: Reduction of 0.38% in HbA1c in the cases (95% CI:−0.89% to 0.12%). No significant differences with regard to any of the activities registered, or any significant change in the quality of life. CONCLUSIONS: The results obtained are similar to other equivalent studies. The profile of the patient is elderly and with multiple morbidities, who still have technological limitations. To surpass these barriers, it would be necessary to devote more time to the training and to the resolution of possible technological problems

[Effectiveness and economic impact of a program of integrated care with telemedicine support on insulin-treated type 2 diabetic patients (Study GITDIABE)]. / Efectividad e impacto económico de un programa de atención integrada con soporte de telemedicina a pacientes diabéticos tipo 2 tratados con insulina (estudio GITDIABE).

AIM: To evaluate if insulin-treated type 2 diabetic patients with blood glucose self-monitoring (DIA), included in a program of integrated management of diabetes mellitus (DM), achieve a better level of metabolic control with telemedicine support than with conventional support, after 12 months follow-up. The impact on the use and cost of healthcare services, pharmaceutical expenditure, and consumption of test strips for blood glucose, was also assessed. DESIGN: A prospective parallel cohorts study. FIELD: Four basic health areas of an integrated healthcare organisation. PARTICIPANTS: The study included 126 DIA patients aged 15 or more years, treated with rapid or intermediate Insulin and blood glucose self-monitoring, grouped into 42 cases and 84 controls, matched according to age, sex, level of metabolic control, and morbidity profile. INTERVENTION: Telematics physician-patient communication and download of blood glucose self-monitoring data through the Emminens eConecta® platform; test strips home delivered according to consumption. Hidden controls with usual follow-up. MAIN MEASUREMENTS: Glycosylated haemoglobin (%HbA1c); perception of quality of life (EuroQol-5 and EsDQOL); cardiovascular risk; use of healthcare resources; consumption of test strips; pharmaceutical and healthcare expenditure. RESULTS: Reduction of 0.38% in HbA1c in the cases (95% CI:-0.89% to 0.12%). No significant differences with regard to any of the activities registered, or any significant change in the quality of life. CONCLUSIONS: The results obtained are similar to other equivalent studies. The profile of the patient is elderly and with multiple morbidities, who still have technological limitations. To surpass these barriers, it would be necessary to devote more time to the training and to the resolution of possible technological problems.

Morbilidad y costes sanitarios: hacia un benchmarking? / Morbidity and healthcare costs: towards a benchmarking?

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Predicción del riesgo individual de alto coste sanitario para la identificación de pacientes crónicos complejos / Predicting individual risk of high healthcare cost to identify complex chronic patients

Objetivo: Construir y validar un modelo predictivo del riesgo de consumo de recursos sanitarios elevado, y evaluar su capacidad para identificar pacientes crónicos complejos. Métodos: Estudio transversal realizado en una organización sanitaria integrada sobre datos individuales de residentes 2 años consecutivos (88.795 personas). Variable dependiente: coste sanitario real superior al percentil 95 (P95), incluyendo todos los servicios de la organización sanitaria integrada y las recetas de farmacia. Variables predictoras: edad, sexo, morbilidad (según los clinical risk groups [CRG]) y datos seleccionados de utilización previa (uso de hospitalización, uso de medicación hospitalaria ambulatoria, gasto en recetas de farmacia). Análisis univariado descriptivo. Construcción de un modelo de regresión logística con nivel de confianza del 95%; análisis de validez mediante sensibilidad, especificidad, valor predictivo positivo (VPP) y área bajo la curva ROC (AUC). Resultados: Las personas con coste >P95 acumulan el 44% del coste sanitario total y se concentran en las categorías ACRG3 (aggregated CRG level 3) de enfermedades crónicas múltiples o graves. La carga de morbilidad aumenta con la edad. En el modelo, todas las variables fueron estadísticamente significativas excepto el sexo. Se obtuvo una sensibilidad del 48,4% (intervalo de confianza [IC]: 46,9%-49,8%), una especificidad del 97,2% (IC: 97,0%-97,3%), un VPP del 46,5% (IC: 45,0%-47,9%) y un AUC de 0,897 (IC: 0,892-0,902). Conclusiones: El consumo sanitario elevado se relaciona con la morbilidad crónica compleja. Un modelo basado en la edad, la morbilidad y la utilización previa es válido para predecir el riesgo de alto consumo, y así identificar la población diana de estrategias de atención proactiva para pacientes crónicos complejos (AU)

Objective: To develop a predictive model for the risk of high consumption of healthcare resources, and assess the ability of the model to identify complex chronic patients. Methods: A cross-sectional study was performed within a healthcare management organization by using individual data from 2 consecutive years (88,795 people). The dependent variable consisted of healthcare costs above the 95th percentile (P95), including all services provided by the organization and pharmaceutical consumption outside of the institution. The predictive variables were age, sex, morbidity-based on clinical risk groups (CRG)-and selected data from previous utilization (use of hospitalization, use of high-cost drugs in ambulatory care, pharmaceutical expenditure). A univariate descriptive analysis was performed. We constructed a logistic regression model with a 95% confidence level and analyzed sensitivity, specificity, positive predictive values (PPV), and the area under the ROC curve (AUC). Results: Individuals incurring costs >P95 accumulated 44% of total healthcare costs and were concentrated in ACRG3 (aggregated CRG level 3) categories related to multiple chronic diseases. All variables were statistically significant except for sex. The model had a sensitivity of 48.4% (CI: 46.9%-49.8%), specificity of 97.2% (CI: 97.0%-97.3%), PPV of 46.5% (CI: 45.0%-47.9%), and an AUC of 0.897 (CI: 0.892 to 0.902). Conclusions: High consumption of healthcare resources is associated with complex chronic morbidity. A model based on age, morbidity, and prior utilization is able to predict high-cost risk and identify a target population requiring proactive care (AU)

[Predicting individual risk of high healthcare cost to identify complex chronic patients]. / Predicción del riesgo individual de alto coste sanitario para la identificación de pacientes crónicos complejos.

OBJECTIVE: To develop a predictive model for the risk of high consumption of healthcare resources, and assess the ability of the model to identify complex chronic patients. METHODS: A cross-sectional study was performed within a healthcare management organization by using individual data from 2 consecutive years (88,795 people). The dependent variable consisted of healthcare costs above the 95th percentile (P95), including all services provided by the organization and pharmaceutical consumption outside of the institution. The predictive variables were age, sex, morbidity-based on clinical risk groups (CRG)-and selected data from previous utilization (use of hospitalization, use of high-cost drugs in ambulatory care, pharmaceutical expenditure). A univariate descriptive analysis was performed. We constructed a logistic regression model with a 95% confidence level and analyzed sensitivity, specificity, positive predictive values (PPV), and the area under the ROC curve (AUC). RESULTS: Individuals incurring costs >P95 accumulated 44% of total healthcare costs and were concentrated in ACRG3 (aggregated CRG level 3) categories related to multiple chronic diseases. All variables were statistically significant except for sex. The model had a sensitivity of 48.4% (CI: 46.9%-49.8%), specificity of 97.2% (CI: 97.0%-97.3%), PPV of 46.5% (CI: 45.0%-47.9%), and an AUC of 0.897 (CI: 0.892 to 0.902). CONCLUSIONS: High consumption of healthcare resources is associated with complex chronic morbidity. A model based on age, morbidity, and prior utilization is able to predict high-cost risk and identify a target population requiring proactive care.

Análisis de la población diabética de una comarca: perfil de morbilidad, utilización de recursos, complicaciones y control metabólico / An analysis of the diabetic population in a Spanish rural are: morbidity profile, use of resources, complications and metabolic control

Objetivo: Describir las características de una población diabética, perfil de morbilidad, consumo de recursos, complicaciones y grado de control. Diseño: Estudio transversal durante 2010.EmplazamientoCuatro Áreas Básicas de Salud (91.301 personas) donde la organización sanitaria integrada Serveis de Salut Integrats Baix Empordà cubre la asistencia. Participantes: Se han identificado 4.985 diabéticos, utilizando la codificación clínica de los contactos mediante CIE-9-MC y Clinical Risk Groups. Mediciones principales: Perfil de morbilidad de los diabéticos, complicaciones y grado de control metabólico. Se analiza el consumo de recursos asistenciales, farmacéutico y de tiras reactivas de glucemia. Todas las mediciones a nivel individual. Resultados: El 99,3% de los diabéticos acudió al menos una vez al centro de salud (14,9% del total de visitas). El 39,5% de las visitas de atención primaria y menos del 10% del resto de recursos analizados se dedicaron a la gestión de la diabetes. El coste de farmacia representa el 25,4% del consumo total de la población (coste medio 1.014,57?). El 36,5% de los diabéticos consumió tiras reactivas (coste medio 120,65?). Los CRG base más comunes son 5424-Diabetes (27%); 6144-Diabetes and Hypertension (25,5%) y 6143-Diabetes and Other Moderate Chronic Disease (17,2%). El grado de control de la enfermedad es mejor en pacientes que no toman fármacos o toman antidiabéticos orales no secretagogos. Conclusiones: La comorbilidad es determinante en el consumo de recursos. Solo una parte de este consumo está dedicado al manejo de la diabetes. Los resultados obtenidos son consistentes y complementan desde un punto de vista poblacional los estudios existentes de ámbito estatal y autonómico (AU)

Objective: To describe the characteristics of a diabetic population, morbidity profile, resource consumption, complications and degree of metabolic control. Design: Cross-sectional study during 2010.Location: Four Health Areas (91.301 people) where the integrated management organization Serveis de Salut integrated Baix Empordà completely provide healthcare assistance. Participants: 4.985 diabetic individuals, identified through clinical codes using the ICD-9-MC classification and the 3M? Clinical Risk Groups software. Main measurements: Morbidity profile, related complications and degree of metabolic control were obtained for the target diabetic population. We analyzed the consumption of healthcare resources, pharmaceutical and blood glucose reagent strips. All measurements obtained at individual level. Results: 99.3% of the diabetic population were attended at least once at a primary care center (14.9% of visits). 39.5% of primary care visits and less than 10% of the other scanned resources were related to the management of diabetes. The pharmaceutical expenditure was 25.4% of the population consumption (average cost ? 1.014,57). 36.5% of diabetics consumed reagents strips (average cost ?120,65). The more frequent CRG are 5424-Diabetes (27%); 6144-Diabetesand Hypertension (25,5%) and 6143-Diabetes and Other Moderate Chronic Disease (17,2%). The degree of disease control is better in patients not consumers of antidiabetic drugs or treated with oral antidiabetic agents not secretagogues. Conclusions: Comorbidity is decisive in the consumption of resources. Just a few part of this consumption is specifically related to the management of diabetes. Results obtained provide a whole population approach to the main existing studies in our national and regional context (AU)

Estimating lifetime healthcare costs with morbidity data.

BACKGROUND: In many developed countries, the economic crisis started in 2008 producing a serious contraction of the financial resources spent on healthcare. Identifying which individuals will require more resources and the moment in their lives these resources have to be allocated becomes essential. It is well known that a small number of individuals with complex healthcare needs consume a high percentage of health expenditures. Conversely, little is known on how morbidity evolves throughout life. The aim of this study is to introduce a longitudinal perspective to chronic disease management. METHODS: Data used relate to the population of the county of Baix Empordà in Catalonia for the period 2004-2007 (average population was N = 88,858). The database included individual information on morbidity, resource consumption, costs and activity records. The population was classified using the Clinical Risk Groups (CRG) model. Future morbidity evolution was simulated under different assumptions using a stationary Markov chain. We obtained morbidity patterns for the lifetime and the distribution function of the random variable lifetime costs. Individual information on acute episodes, chronic conditions and multimorbidity patterns were included in the model. RESULTS: The probability of having a specific health status in the future (healthy, acute process or different combinations of chronic illness) and the distribution function of healthcare costs for the individual lifetime were obtained for the sample population. The mean lifetime cost for women was €111,936, a third higher than for men, at €81,566 (all amounts calculated in 2007 Euros). Healthy life expectancy at birth for females was 46.99, lower than for males (50.22). Females also spent 28.41 years of life suffering from some type of chronic disease, a longer period than men (21.9). CONCLUSIONS: Future morbidity and whole population costs can be reasonably predicted, combining stochastic microsimulation with a morbidity classification system. Potential ways of efficiency arose by introducing a time perspective to chronic disease management.

[An analysis of the diabetic population in a Spanish rural are: morbidity profile, use of resources, complications and metabolic control]. / Análisis de la población diabética de una comarca: perfil de morbilidad, utilización de recursos, complicaciones y control metabólico.

OBJECTIVE: To describe the characteristics of a diabetic population, morbidity profile, resource consumption, complications and degree of metabolic control. DESIGN: Cross-sectional study during 2010. LOCATION: Four Health Areas (91.301 people) where the integrated management organization Serveis de Salut integrated Baix Empordà completely provide healthcare assistance. PARTICIPANTS: 4.985 diabetic individuals, identified through clinical codes using the ICD-9-MC classification and the 3M? Clinical Risk Groups software. MAIN MEASUREMENTS: Morbidity profile, related complications and degree of metabolic control were obtained for the target diabetic population. We analyzed the consumption of healthcare resources, pharmaceutical and blood glucose reagent strips. All measurements obtained at individual level. RESULTS: 99.3% of the diabetic population were attended at least once at a primary care center (14.9% of visits). 39.5% of primary care visits and less than 10% of the other scanned resources were related to the management of diabetes. The pharmaceutical expenditure was 25.4% of the population consumption (average cost ?1.014,57). 36.5% of diabetics consumed reagents strips (average cost ?120,65). The more frequent CRG are 5424-Diabetes (27%); 6144-Diabetes and Hypertension (25,5%) and 6143-Diabetes and Other Moderate Chronic Disease (17,2%). The degree of disease control is better in patients not consumers of antidiabetic drugs or treated with oral antidiabetic agents not secretagogues. CONCLUSIONS: Comorbidity is decisive in the consumption of resources. Just a few part of this consumption is specifically related to the management of diabetes. Results obtained provide a whole population approach to the main existing studies in our national and regional context.

[Measurement of morbidity attended in an integrated health care organization]. / La medida de la morbilidad atendida en una organización sanitaria integrada.

INTRODUCTION: Understanding the quality, costs and outcomes of healthcare services requires precise determination of the morbidity in a population. Measurement of morbidity in a population and its association with the services provided remains to be performed. The aim of this article was to present our experience of using clinical risk groups (CRGs) to measure morbidity in an integrated healthcare organization (IHO). METHODS: We studied the population attended by an IHO in a county (approximately 120,000 patients) from 2002 to 2005. CRGs were used to measure morbidity. A descriptive analysis was performed of the population's distribution in CRG categories and utilization rates. RESULTS: One or more chronic diseases was found in 15.5% of the population, significant acute illness was found in 9%, minor chronic diseases was found in 7% and very severe diseases was found in 0.5%. Between 2002 and 2005, the number of individuals with chronic disease increased by 8%. The burden of illness increased with age. However, at all ages, at least 40% of the population remained healthy. Comorbidity in chronic illnesses was a crucial factor in explaining healthcare resource utilization. CONCLUSIONS: The CRG grouping system aids analysis at different levels for clinical administration. Due to its composition, this system allows better understanding of the use, costs and quality of the set of services received by a population.

La medida de la morbilidad atendida en una organización sanitaria integrada / Measurement of morbidity attended in an integrated health care organization

Introducción: La comprensión de la calidad, los costes y los resultados de los servicios de salud obliga a conocer con precisión la morbilidad de la población. La medida de la morbilidad atendida en una población y su relación con los servicios recibidos es una tarea pendiente. El objetivo de este artículo es presentar la experiencia de utilización de los grupos de riesgo clínico (clinical risk groups [CRG]) como sistema de medida de la morbilidad atendida en una organización sanitaria integrada (OSI). Métodos: Se estudia la población de una comarca (unas 120.000 personas) atendida por una OSI durante los años 2002¿2005. Se utilizan los CRG como sistema de medida de la morbilidad poblacional. Se efectúa un análisis descriptivo de las diferentes posibilidades de utilización que ofrece este sistema. Resultados: El 15,5% de la población presenta una o más enfermedades crónicas dominantes, un 9% presenta enfermedades agudas significativas, un 7% presenta enfermedades crónicas menores y un 0,5% enfermedades muy graves. Entre 2002 y 2005, en un 8% de la población se identifica la aparición de alguna enfermedad crónica. La carga de enfermedad se incrementa con la edad, pero en cualquier grupo de edad al menos un 40% de las personas permanecen sanas. La comorbilidad en enfermedades crónicas es un factor determinante en la explicación del consumo de recursos sanitarios. Conclusiones: Los CRG son una herramienta que facilita el análisis a diferentes niveles para la gestión clínica y, por su configuración, permiten una mejor comprensión de la utilización, los costes y la calidad del conjunto de servicios recibidos por una población(AU)

Introduction: Understanding the quality, costs and outcomes of healthcare services requires precise determination of the morbidity in a population. Measurement of morbidity in a population and its association with the services provided remains to be performed. The aim of this article was to present our experience of using clinical risk groups (CRGs) to measure morbidity in an integrated healthcare organization (IHO). Methods: We studied the population attended by an IHO in a county (approximately 120,000 patients) from 2002 to 2005. CRGs were used to measure morbidity. A descriptive analysis was performed of the population's distribution in CRG categories and utilization rates. Results: One or more chronic diseases was found in 15.5% of the population, significant acute illness was found in 9%, minor chronic diseases was found in 7% and very severe diseases was found in 0.5%. Between 2002 and 2005, the number of individuals with chronic disease increased by 8%. The burden of illness increased with age. However, at all ages, at least 40% of the population remained healthy. Comorbidity in chronic illnesses was a crucial factor in explaining healthcare resource utilization. Conclusions: The CRG grouping system aids analysis at different levels for clinical administration. Due to its composition, this system allows better understanding of the use, costs and quality of the set of services received by a population(AU)