Prevalencia de las enfermedades reumáticas en el Baix Empordà / Prevalence of rheumatic diseases in Baix Empordà

Introducción: En España, la prevalencia de diferentes enfermedades reumáticas se conoce principalmente a través de los estudios EPISER coordinados desde la Sociedad Española de Reumatología y que parten de encuestas en una muestra poblacional. Nuestro estudio tiene por objetivo describir la prevalencia en 2016 de las distintas enfermedades reumáticas en la población residente en el Baix Empordà según registros de codificación asistencial. Materiales y métodos: Estudio observacional, descriptivo y transversal realizado sobre la población residente durante los años 2016-2017 en la comarca del Baix Empordà, donde una organización sanitaria integrada (Serveis de Salut Integrats Baix Empordà) gestiona todos los dispositivos asistenciales públicos con un sistema de información unificado. Se seleccionaron los pacientes ≥ 20 años y se analizó la codificación CIE-9-CM de sus contactos asistenciales en función de 11 agrupaciones diagnósticas de 28 enfermedades reumáticas. Las agrupaciones fueron: poliartritis, espondiloartritis, artritis microcristalinas, artrosis (excepto localización vertebral), reumatismos de partes blandas, fibromialgia, dolor vertebral crónico (incluyendo artrosis), osteoporosis, enfermedades del tejido conectivo, vasculitis y otros. La población estudiada se asignó a tres categorías: «con enfermedad reumática», «posible enfermedad reumática» y «sin enfermedad reumática». Resultados: La muestra final fue de 71.785 personas, así distribuidas: «con enfermedad reumática» (n=25.990; 36,2%); «posible enfermedad reumática» (n=4.406; 6,1%) y «sin enfermedad reumática» (n=41.389; 57,7%). El grupo «con enfermedad reumática» mostró un predominio de mujeres (59,8% vs. 44,9%) y mayor edad (59,1±17,7 vs. 45,1±16,2; p<0,001) en comparación al grupo «sin enfermedad reumática». Conclusiones: El 36,2% de nuestra población presenta algún tipo de enfermedad reumática.(AU)

Background: In Spain, the prevalence of different rheumatic diseases is known mainly through the EPISER studies coordinated by the Spanish Society of Rheumatology and based on surveys in a population sample. The aim of our study is to describe the prevalence in 2016 of different rheumatic diseases in the population residing in Baix Empordà according to healthcare coding records. Materials and methods: Observational, descriptive and cross-sectional study carried out on the population attended from 2016-2017 in Serveis de Salut Integrats del Baix Empordà, an organizational service that includes all the healthcare facilities in the Baix Empordà area with a unique information system. Patients ≥ 20 years of age were selected and the ICD9-CM coding of all their healthcare contacts was analysed according to 11 entities and 28 diseases. The entities were: polyarthritis, spondyloarthritis, microcrystalline arthritis, osteoarthritis, soft tissue rheumatism, fibromyalgia, chronic spinal pain, osteoporosis, connective tissue diseases, vasculitis and others. The studied population was assigned to the categories: “with rheumatic disease”, “possible rheumatic disease” and “without rheumatic disease”. Results: In total, 71,785 patients were distributed as: 36.2% “with rheumatic disease (n=25,990); 6.1% with “possible rheumatic disease” (n=4,406) and 57.7% “without rheumatic disease” (n=41,389). The group “with rheumatic disease” showed a predominance of women (59.8% vs. 44.9%) and older age (59.1±17.7 vs. 45.1±16.2; P <.001) compared to the group “without rheumatic disease”. The presence of rheumatic disease increased progressively with age, being maximum in the group between 55-75 years. Conclusions: 36.2% of our population has some type of rheumatic disease.(AU)

Prevalence of rheumatic diseases in Baix Empordà.

BACKGROUND: In Spain, the prevalence of different rheumatic diseases is known mainly through the EPISER studies coordinated by the Spanish Society of Rheumatology and based on surveys in a population sample. The aim of our study is to describe the prevalence in 2016 of different rheumatic diseases in the population residing in Baix Empordà according to healthcare coding records. MATERIALS AND METHODS: Observational, descriptive and cross-sectional study carried out on the population attended from 2016 to 2017 in SIBBE (Serveis de Salut Integrats del Baix Empordà), an organizational service that includes all the healthcare facilities in the Baix Empordà area with a unique information system. Patients ≥ 20 years of age were selected and the ICD9-CM coding of all their healthcare contacts was analysed according to 11 entities and 28 diseases. The entities were: polyarthritis, spondyloarthritis, microcrystalline arthritis, osteoarthritis, soft tissue rheumatism, fibromyalgia, chronic spinal pain, osteoporosis, connective tissue diseases, vasculitis and others. The studied population was assigned to the categories: "with rheumatic disease", "possible rheumatic disease" and "without rheumatic disease". RESULTS: In total, 71,785 patients were distributed as: 36.2% "with rheumatic disease (n = 25,990); 6.1% with "possible rheumatic disease" (n = 4406) and 57.7% "without rheumatic disease" (n = 41,389). The group "with rheumatic disease" showed a predominance of women (59.7% vs. 44.9%) and older age (59.1 ±â€¯17.7 vs. 45.1 ±â€¯16.2; p < .001) compared to the group "without rheumatic disease". The presence of rheumatic disease increased progressively with age, being maximum in the group between 55-75 years. CONCLUSIONS: 36.2% of our population has some type of rheumatic disease. The estimated prevalence of some rheumatic diseases in the Baix Empordà population is partially consistent with that estimated by the EPISER 2016 study. Rheumatic disease affects women in a greater proportion and is more frequent in patients over 45 years of age.

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.

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.