Impacto de los factores de riesgo cardiovascular en el consumo de recursos en Atención Primaria según los Grupos de Riesgo Clínico / Impact of cardiovascular risk factors on the consumption of resources in Primary Care according to Clinical Risk Groups

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

Predicting healthcare expenditure by multimorbidity groups.

OBJECTIVES: This article has two main purposes. Firstly, to model the integrated healthcare expenditure for the entire population of a health district in Spain, according to multimorbidity, using Clinical Risk Groups (CRG). Secondly, to show how the predictive model is applied to the allocation of health budgets. METHODS: The database used contains the information of 156,811 inhabitants in a Valencian Community health district in 2013. The variables were: age, sex, CRG's main health statuses, severity level, and healthcare expenditure. The two-part models were used for predicting healthcare expenditure. From the coefficients of the selected model, the relative weights of each group were calculated to set a case-mix in each health district. RESULTS: Models based on multimorbidity-related variables better explained integrated healthcare expenditure. In the first part of the two-part models, a logit model was used, while the positive costs were modelled with a log-linear OLS regression. An adjusted R2 of 46-49% between actual and predicted values was obtained. With the weights obtained by CRG, the differences found with the case-mix of each health district proved most useful for budgetary purposes. CONCLUSIONS: The expenditure models allowed improved budget allocations between health districts by taking into account morbidity, as opposed to budgeting based solely on population size.

Measurement of health-related quality by multimorbidity groups in primary health care.

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.

[Impact of cardiovascular risk factors on the consumption of resources in Primary Care according to Clinical Risk Groups]. / Impacto de los factores de riesgo cardiovascular en el consumo de recursos en Atención Primaria según los Grupos de Riesgo Clínico.

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.

[Impact of Morbidity on Health Care Costs of a Department of Health through Clinical Risk Groups. Valencian Community, Spain]. / Impacto de la morbilidad en los costes asistenciales de un Departamento de Salud de la Comunidad Valenciana a través de estudio de Grupos Clínicos de Riesgo.

BACKGROUND: Risk adjustment systems based on diagnosis stratify the population according to the observed morbidity. The aim of this study was to analyze the total health expenditure in a health area, relating to age, gender and morbidity observed in the population. METHODS: Observational cross-sectional study of population and area of health care costs in the Health District of Denia-Marina Salud (Alicante) in 2013. Population (N=156,811) were stratified by Clinical Risk Groups into 9 states of health, state 1 being healthy, and state 9 the highest disease burden. Each inhabitant was charged with the hospital costs, primary care and outpatient pharmacy to obtain the total costs. Health status and severity by age and gender, as well as the costs of each group were analysed. The statistical tests, student t and χ2 were applied to verify the existence of significant differences between and intra groups. RESULTS: The average cost per inhabitant was 983 euros which increased from 240 euros to 42,881 at the state 9 and severity level 6. Patients of health states 5 and 6 caused the largest expenditure by concentration of the population, but health states 8 and 9 had the highest average expenditure, with 80% of hospitalised cost. CONCLUSIONS: A different composition of health expenditure per individual morbidity was corroborated, with an exponential growth in hospital spending.

OBJETIVO: Los sistemas de ajuste de riesgo basados en diagnóstico estratifican la población según la morbilidad observada. El objetivo de este trabajo fue analizar el gasto sanitario total en un área de salud en función de la edad, el sexo y la morbilidad observada en la población. METODOS: Estudio observacional de corte transversal y de ámbito poblacional de los costes de atención sanitaria en el Departamento de salud Dénia-Marina Salud (Alicante) durante el año 2013. Se estratificó a la población (N=156.811) según Grupos de Riesgo Clínico en 9 estados de salud, siendo sano el estado 1 y el 9 el de mayor carga de morbilidad. A cada habitante se le imputaron los costes hospitalarios, de atención primaria y de farmacia ambulatoria para obtener los costes totales. Se analizaron los estados de salud y gravedad por edad y sexo así como los costes de cada grupo. Se aplicaron las pruebas estadísticas t de student y χ2 para verificar la existencia de diferencias significativas entre e intra grupos. RESULTADOS: El coste medio por habitante fue de 983 euros oscilando desde 240 hasta 42.881 en el estado 9 y nivel de gravedad 6. Los pacientes de los estados de salud 5 y 6 realizaron el mayor gasto, pero los estados de salud 8 y 9 tuvieron el mayor gasto medio, siendo el 80% hospitalario. CONCLUSIONES: Se corrobora una diferente composición del gasto sanitario por morbilidad individual, con un crecimiento exponencial del gasto hospitalario.

Impacto de la morbilidad en los costes asistenciales de un departamento de salud de la Comunidad Valenciana a través de los grupo de riesgo clínico / Impact of morbidity on health care costs of a department of health through clinic

Fundamentos: Los sistemas de ajuste de riesgo basados en diagnóstico estratifican la población según la morbilidad observada. El objetivo de este trabajo fue analizar el gasto sanitario total en un área de salud en función de la edad, el sexo y la morbilidad observada en la población. Métodos: Estudio observacional de corte transversal y de ámbito poblacional de los costes de atención sanitaria en el Departamento de salud Dénia-Marina Salud (Alicante) durante el año 2013. Se estratificó a la población (N=156.811) según Grupos de Riesgo Clínico en 9 estados de salud, siendo sano el estado 1 y el 9 el de mayor carga de morbilidad. A cada habitante se le imputaron los costes hospitalarios, de atención primaria y de farmacia ambulatoria para obtener los costes totales. Se analizaron los estados de salud y gravedad por edad y sexo así como los costes de cada grupo. Se aplicaron las pruebas estadísticas t de student y χ2 para verificar la existencia de diferencias significativas entre e intra grupos. Resultados: El coste medio por habitante fue de 983 euros oscilando desde 240 hasta 42.881 en el estado 9 y nivel de gravedad 6. Los pacientes de los estados de salud 5 y 6 realizaron el mayor gasto, pero los estados de salud 8 y 9 tuvieron el mayor gasto medio, siendo el 80% hospitalario. Conclusiones: Se corrobora una diferente composición del gasto sanitario por morbilidad individual, con un crecimiento exponencial del gasto hospitalario (AU)

Background: Risk adjustment systems based on diagnosis stratify the population according to the observed morbidity. The aim of this study was to analyze the total health expenditure in a health area, relating to age, gender and morbidity observed in the population. Methods: Observational cross-sectional study of population and area of health care costs in the Health District of Denia-Marina Salud (Alicante) in 2013. Population (N=156,811) were stratified by Clinical Risk Groups into 9 states of health, state 1 being healthy, and state 9 the highest disease burden. Each inhabitant was charged with the hospital costs, primary care and outpatient pharmacy to obtain the total costs. Health status and severity by age and gender, as well as the costs of each group were analysed. The statistical tests, student t and χ2 were applied to verify the existence of significant differences between and intra groups. Results: The average cost per inhabitant was 983 euros which increased from 240 euros to 42,881 at the state 9 and severity level 6. Patients of health states 5 and 6 caused the largest expenditure by concentration of the population, but health states 8 and 9 had the highest average expenditure, with 80% of hospitalised cost. Conclusions: A different composition of health expenditure per individual morbidity was corroborated, with an exponential growth in hospital spending (AU)

[Impact of Teriparatide on Quality of Life in Osteoporotic Patients]. / Impacto del tratamiento con teriparatida en la calidad de vida de las personas con osteoporosis.

BACKGROUND: Lost bone in osteoporotic patients increases the risk of fractures and back pain, and decreases quality of life. The aim of this study was to analyse the effect of teriparatide (TPTD) in osteoporotic patients with vertebral pain. METHODS: A prospective observational study between April 2006 and February 2014 was done with 77 patients treated with teriparatide in the Pain Unit of Hospital Obispo Polanco of Teruel (Spain). Treatment duration was 18 or 24 months. Pain was assessed by the Visual Analogue Scale (VAS). Health-related quality of life was measured using the European Quality of Life Questionnaire (EuroQol-5D) in order to obtain the social tariff (ST). Pre and post-treatment values were collected respectively. A descriptive and regression analysis was done. RESULTS: Improvement in pain was observed (80%) and in health-related quality of life (65%). The mean VAS improved (from 5.42 to 3.47 points) and the mean health status value too (from 0.36 to 0.58 points). The regression indicated an improvement of VAS in 0.441 for each initial VAS point, and of ST in 0.0528 points for each 0.1 initial ST point. The probability of VAS reduction in 3 points (OR = 2.021) was greater than in 2 points (OR = 1.695). CONCLUSIONS: TPTD reduces pain and improves quality of life of osteoporotic patients. The worse the baseline situation, the more patients' health improved, so it could be used as criteria for therapeutic decisions and health management.

Impacto del tratamiento con teriparatida en la calidad de vida de las personas con osteoporosis / Impact of teriparatide on quality of life in osteoporotic patients

Fundamentos: La pérdida ósea en pacientes osteoporóticos, conlleva riesgo de fracturas, dolor óseo vertebral y disminución de la calidad de vida. El objetivo de este trabajo fue analizar el efecto de la teriparatida (TPTD) en pacientes osteoporóticos y con dolor vertebral. Métodos: Estudio observacional longitudinal prospectivo, entre abril de 2006 y febrero de 2014, en los 77 pacientes tratados con TPTD en la Unidad del Dolor del Hospital de Teruel. La duración del tratamiento fue de 18 o 24 meses. Se utilizó la Escala Visual Analógica (EVA) para la medición del dolor y el cuestionario europeo de calidad de vida (EuroQol-5D) para obtener la tarifa social (TS), antes y después el tratamiento. Se realizó un análisis descriptivo, de regresión lineal y logística. Resultados: Se observó una mejoría del dolor (80%) y de la calidad de vida (65 %). Se mejoró la EVA media (5,42 a 3,47 puntos) y el EuroQol-5D (0,36 a 0,58 puntos). La regresión indicó una mejora de la EVA en 0,441 puntos por cada punto de EVA inicial, y de la TS en 0,0528 puntos por cada 0,1 puntos de TS inicial. La probabilidad de mejorar la EVA en 3 puntos (OR=2,021), fue mayor que de mejorar 2 puntos (OR=1,695). Conclusiones: La TPTD en pacientes osteoporóticos reduce el dolor óseo y mejora la calidad de vida. Su efecto es mayor en pacientes con peor estado de salud inicial, pudiendo ser utilizado como criterio para las decisiones terapéuticas y de gestión clínica (AU)

Background: Lost bone in osteoporotic patients increases the risk of fractures and back pain, and decreases quality of life. The aim of this study was to analyse the effect of teriparatide (TPTD) in osteoporotic patients with vertebral pain. Methods: A prospective observational study between April 2006 and February 2014 was done with 77 patients treated with teriparatide in the Pain Unit of Hospital Obispo Polanco of Teruel (Spain). Treatment duration was 18 or 24 months. Pain was assessed by the Visual Analogue Scale (VAS). Health-related quality of life was measured using the European Quality of Life Questionnaire (EuroQol-5D) in order to obtain the social tariff (ST). Pre and post- treatment values were collected respectively. A descriptive and regression analysis was done. Results: Improvement in pain was observed (80%) and in health-related quality of life (65%). The mean VAS improved (from 5.42 to 3.47 points) and the mean health status value too (from 0.36 to 0.58 points). The regression indicated an improvement of VAS in 0.441 for each initial VAS point, and of ST in 0.0528 points for each 0.1 initial ST point. The probability of VAS reduction in 3 points (OR=2.021) was greater than in 2 points (OR=1.695). Conclusions: TPTD reduces pain and improves quality of life of osteoporotic patients. The worse the baseline situation, the more patients’ health improved, so it could be used as criteria for therapeutic decisions and health management (AU)

Pharmaceutical cost management in an ambulatory setting using a risk adjustment tool.

BACKGROUND: Pharmaceutical expenditure is undergoing very high growth, and accounts for 30% of overall healthcare expenditure in Spain. In this paper we present a prediction model for primary health care pharmaceutical expenditure based on Clinical Risk Groups (CRG), a system that classifies individuals into mutually exclusive categories and assigns each person to a severity level if s/he has a chronic health condition. This model may be used to draw up budgets and control health spending. METHODS: Descriptive study, cross-sectional. The study used a database of 4,700,000 population, with the following information: age, gender, assigned CRG group, chronic conditions and pharmaceutical expenditure. The predictive model for pharmaceutical expenditure was developed using CRG with 9 core groups and estimated by means of ordinary least squares (OLS). The weights obtained in the regression model were used to establish a case mix system to assign a prospective budget to health districts. RESULTS: The risk adjustment tool proved to have an acceptable level of prediction (R2 ≥ 0.55) to explain pharmaceutical expenditure. Significant differences were observed between the predictive budget using the model developed and real spending in some health districts. For evaluation of pharmaceutical spending of pediatricians, other models have to be established. CONCLUSION: The model is a valid tool to implement rational measures of cost containment in pharmaceutical expenditure, though it requires specific weights to adjust and forecast budgets.

[Incidence and variability of temporary disability due to anxiety disorders during 2009 in the Valencia Community, Spain].

BACKGROUND: Anxiety, dissociative and somatoform disorders (WHO-e 300) are the second cause of Temporary Disability (TD) in Spain. This is the main reason that justifies the analysis of the variability among primary health care centers (PHC) of the Valencian Community in the prescription processes of Temporary Disability for these disorders. METHODS: Epidemiological cross-sectional descriptive study of variability of TD processes initiated in 2009 corresponding to diagnosis e 300 in 739 PHC from 23 health districts in the Valencian Community, where 25,859 TD processes for the diagnosis e 300 were prescribed. Traditional indicators of variation developed for the analysis of small areas were used to determine variability in the incidence rate of TD processes. The analysis of variance was used to determine the percentage of explanation of the factors studied. RESULTS: The average incidence rate obtained was of 1.08 for 100 individuals. The variation range was between 0.01 and 1.97 for percentiles P(5) to P(95). In the variance components analysis, the factor of health district explains the highest percentage of variability (22.12), followed by the factor province (20.21%), coastal areas (4.65%), teaching accreditation (2.44%) and the size of population assigned to each PHC (2.40%). CONCLUSIONS: Significant differences were observed in the incidence rate of TD processes for the diagnosis e 300. The PHCs with greater population pressure and those that are accredited had the highest rates of incidence.

Incidencia y variabilidad de la incapacidad temporal por trastornos de ansiedad en la Comunidad Valenciana durante el 2009 / Incidence and variability of temporary disability due to anxiety disorders during 2009 in the Valencia Community, Spain

Fundamentos: Los trastornos de ansiedad, disociativos y somatomorfos (Cod300) constituyen la segunda causa de incapacidad temporal (IT) en España. Esta razón justifica que el presente trabajo se centre en analizar la variabilidad en la prescripción de procesos de IT por estas patologías en los centros de salud y consultorios (CS) de la Comunidad Valenciana (CV). Métodos: Se realizó un estudio epidemiológico poblacional transversal de variabilidad de los procesos de IT iniciados en 2009 correspondientes al Cod300 en los 739 CS, de los 23 departamentos de salud de la CV, donde se prescribieron un total de 25.859 procesos de IT por Cod300. Se utilizaron los estadísticos de variabilidad habituales en el análisis de áreas pequeñas para determinar la variabilidad observada en la tasa de incidencia (TI) de los procesos de IT. El análisis de la varianza se utilizó para determinar el porcentaje de explicación de cada factor estudiado. Resultados: La TI media por 100 individuos es de 1,08 con un rango de variación de 0,01 a 1,97 entre los percentiles P5 a P95. En el análisis de componentes de la varianza, el factor departamento de salud es el que explica mayor porcentaje de variabilidad (22,12%) seguido del factor provincia (20,21%), litoralidad (4,65%), acreditación para la docencia (2,44%) y tamaño poblacional asignado al CS (2,40%). Conclusiones: Se observa una variabilidad notable en las TI de las prescripciones de IT por Cod300. Los factores departamento y provincia son los que más explican esta variabilidad. Los CS con mayor presión poblacional y los acreditados tienen mayores tasas de incidencia(AU)

Background: Anxiety, dissociative and somatoform disorders (WHO-Code 300) are the second cause of Temporary Disability (TD) in Spain. This is the main reason that justifies the analysis of the variability among primary health care centers (PHC) of the Valencian Community in the prescription processes of Temporary Disability for these disorders. Methods: Epidemiological cross-sectional descriptive study of variability of TD processes initiated in 2009 corresponding to diagnosis code 300 in 739 PHC from 23 health districts in the Valencian Community, where 25,859 TD processes for the diagnosis code 300 were prescribed. Traditional indicators of variation developed for the analysis of small areas were used to determine variability in the incidence rate ofTD processes. The analysis of variance was used to determine the percentage of explanation of the factors studied. Results: The average incidence rate obtained was of 1.08 for 100 individuals. The variation range was between 0.01 and 1.97 for percentiles P5 to P95. In the variance components analysis, the factor of health district explains the highest percentage of variability (22.12), followed by the factor province (20.21%), coastal areas (4.65%), teaching accreditation (2.44%) and the size of population assigned to each PHC (2.40%). Conclusions: Significant differences were observed in the incidence rate of TD processes for the diagnosis code 300. The PHCs with greater population pressure and those that are accredited had the highest rates of incidence(AU)