Is utilization of health services for HIV patients equal by socioeconomic status? Evidence from the Basque country

Access to ART and health services is guaranteed under universal coverage to improve life expectancy and quality of life for HIV patients. However, it remains unknown whether patients of different socioeconomic background equally use different types of health services

Efficiency assessment of primary care providers: A conditional nonparametric approach

This paper uses a fully nonparametric approach to estimate efficiency measures for primary care units incorporating the effect of (exogenous) environmental factors. This methodology allows us to account for different types of variables (continuous and discrete) describing the main characteristics of patients served by those providers. In addition, we use an extension of this nonparametric approach to deal with the presence of undesirable outputs in data, represented by the rates of hospitalization for ambulatory care sensitive condition (ACSC) and of hospital readmissions. The empirical results show that all the exogenous variables considered have a significant and negative effect on efficiency estimate

¿Es factible que los médicos de primaria utilicen CIE-9-MC?: Calidad de la codificación de diagnósticos en las historias clínicas informatizadas Can primary care physicians use the ICD-9-MC?: An evaluation of the quality of diagnosis coding in computerized medical records

Objetivos: Determinar el grado de exhaustividad y precisión de los códigos CIE-9-MC asignados por los médicos de primaria en sus historias clínicas informatizadas; evaluar el impacto de actividades para su mejora. Métodos: Los códigos de 87.806 pacientes de 56 médicos de Osakidetza/Servicio Vasco de Salud fueron evaluados en 3 ocasiones en 1 año, según los siguientes criterios: correspondencia con un código CIE-9-MC válido; concordancia entre diagnóstico y código; porcentaje de consultas sin diagnóstico. Finalmente, se contrastaron, con un registro previo de morbilidad atendida, los promedios de diagnósticos únicos y tasas anuales de enfermedades de los 84.136 pacientes que permanecieron con el mismo médico al menos 6 meses. Se realizaron 2 intervenciones para mejorar la codificación: corrección central de errores detectados; asesoramiento e información a los médicos de sus resultados individuales. Resultados: En la primera evaluación, el 59% de los diagnósticos no contenía ningún código CIE-9-MC asociado, mientras que a la finalización este porcentaje descendió al 2%. El porcentaje de errores (discrepancia entre diagnóstico del episodio y código CIE9-MC) disminuyó del 17 al 3%. El promedio anual de diagnósticos por paciente fue ligeramente menor que en el archivo de referencia (2,26 frente a 2,43), así como las tasas de diversos grupos de enfermedades. Conclusiones: Es factible que los médicos de atención primaria alcancen un alto grado de calidad en la clasificación de diagnósticos mediante CIE-9-MC. La implantación de medidas de evaluación, corrección de errores e información a los clínicos permitió mejorar notablemente los resultados iniciales.Objectives: To determine the completeness and accuracy of ICD-9-CM codes allocated by primary health care physicians in their computerized medical records and evaluate the effects of improvement procedures. Methods: The codes of 87,806 patients assigned to 56 primary care physicians in the Basque National Health Service in Spain, were evaluated 3 times over a 1-year period according to the following criteria: correspondence to a valid ICD-9-CM code, agreement between diagnosis and code, and the percentage of visits with an unspecified reason for consultation. Finally, the mean number of unique diagnoses and rates of diagnostic groups in the 84,136 patients that remained with the same physician for a minimum of 6 months were contrasted with another previously registered morbidity database. Two interventions were performed to improve coding: detected errors were corrected centrally and physicians were assessed and given information on their individual results. Results: Diagnoses lacking an ICD-9-DIC code decreased from 59% in the first assessment to 2% at the end of the study period. The percentage of coding mistakes (discrepancies in episode diagnosis and ICD-9-CM code) decreased from 17% to 3%. The mean annual number of diagnoses per patient was slightly lower than that in the reference database (2.26 versus 2.43). The same result was observed in the rates of some diagnostic groups. Conclusions: Primary care doctors can achieve a high degree of quality in ICD-9-CM diagnosis coding. Implementing procedures for evaluating coding, rectifying mistakes, and providing information to physicians markedly improved the initial results

Desarrollo de un modelo de predicción de riesgo de hospitalizaciones no programadas en el País Vasco

Background: Hospitalizations are undesirable events that can be avoided to some degree through proactive interventions. The objective of this study is to determine the capability of models based on Adjusted Clinical Groups (ACG), in our milieu, to identify patients who will present unplanned admissions in the following months to their classification, in both the general population and in subpopulations of chronically ill patients (diabetes mellitus, chronic obstructive pulmonary disease and heart failure). Methods: Cross-sectional study which analyzes data from a two year period, of all residents over 14 years old in the Basque Country (N = 1,964,337). Data from the first year (demographic, deprivation index, diagnoses, prescriptions, procedures, admissions and other contacts with the health service) were used to construct the independent variables; hospitalizations of the second year, the dependent ones. We used the area under the ROC curve (AUC) to evaluate the capability of the models to discriminate patients with hospitalizations and calculated the positive predictive value and sensitivity of different cutoffs. Results: In the general population, models for predicting admission at 6 and 12 months, as well as long-term hospitalizations showed a good performance (AUC> 0.8), while it was acceptable (AUC 0.7 to 0.8) in the groups of chronic patients. Conclusions: A hospitalization risk stratification system, based on ACG, is valid and applicable in our milieu. These models allow classifying the patients on a scale of high to low risk, which makes possible the implementation of the most expensive preventive interventions to only a small subset of patients, while other less intensive ones can be provided to larger groups.Fundamentos: La hospitalizaciones son eventos indeseables que en ocasiones pueden ser evitados mediante intervenciones proactivas. El objetivo del estudio es determinar la capacidad de modelos basados en Adjusted Clinical Groups (ACGs) en nuestro medio para identificar a los pacientes que presentarán ingresos no programados en los meses siguientes a su clasificación, tanto en la población general como en subpoblaciones de enfermos crónicos (diabetes mellitus, enfermedad pulmonar obstructiva crónica e insuficiencia cardiaca). Métodos: Estudio transversal que analizó información de un periodo de 2 años, de todos los residentes en Euskadi mayores de 14 años de edad (n=1.964.337). Los datos del primer año (demográficos, índice de privación socioeconómica, diagnósticos, prescripciones, procedimientos, ingresos y otros contactos con el servicio de salud) sirvieron para construir las variables independientes. Las hospitalizaciones del segundo año, las dependientes. Se empleó el área bajo la curva ROC (AUC) para evaluar la capacidad de los modelos en discriminar a los pacientes con hospitalizaciones y se calculó el valor predictivo positivo y la sensibilidad en diferentes puntos de corte. Resultados: En la población general, los modelos para predecir ingresos a los 6 y 12 meses así como hospitalizaciones prolongadas mostraron un comportamiento bueno (AUC>0,8), mientras que fue aceptable (AUC 0,7-0,8) en los grupos de pacientes crónicos. Conclusiones: Un sistema de estratificación de riesgo de ingresos, basado en ACGs resulta válido y aplicable en nuestro medio. Estos modelos permiten clasificar a los pacientes en una escala de mayor a menor riesgo, lo cual hace posible la aplicación de las intervenciones preventivas más costosas solamente a un pequeño subgrupo de pacientes, mientras que otras menos intensivas pueden proporcionarse a grupos más amplios

Comorbidity and Healthcare Expenditure in Women with Osteoporosis Living in the Basque Country (Spain)

Objectives. This study aimed to establish the prevalence of multimorbidity in women diagnosed with osteoporosis and to report it by deprivation index. The characteristics of comorbidity in osteoporotic women are compared to the general female chronic population, and the impact on healthcare expenditure of this population group is estimated. Methods. A cross-sectional analysis that included all Basque Country women aged 45 years and over (N = 579,575) was performed. Sociodemographic, diagnostic, and healthcare cost data were extracted from electronic databases for a one-year period. Chronic conditions were identified from their diagnoses and prescriptions. The existence of two or more chronic diseases out of a list of 47 was defined as multimorbidity. Results. 9.12% of women presented osteoporosis and 85.04% of them were multimorbid. Although multimorbidity in osteoporosis increased with age and deprivation level, prevalence was higher in the better-off groups. Women with osteoporosis had greater risk of having other musculoskeletal disorders but less risk of having diabetes (RR = 0.65) than chronic patients without osteoporosis. People with poorer socioeconomic status had higher healthcare cost. Conclusions. Most women with osteoporosis have multimorbidity. The variety of conditions emphasises the complexity of clinical management in this group and the importance of maintaining a generalist and multidisciplinary approach to their clinical care

Socio-economic inequalities in occurrence and health care costs in rheumatic and musculoskeletal diseases: results from a Spanish population-based study including 1.9 million persons

Objective To explore and compare the impact of socio-economic deprivation on the occurrence of the major rheumatic and musculoskeletal diseases (RMDs) and health care costs. Methods Data on diagnoses, socio-demographics and health care costs of the entire adult population of the Basque Country (Spain) was used. Area deprivation index included five categories (1 to 5 (most deprived)). Cost categories included primary and specialist care, emergency room, hospitalisations, and drug prescriptions. Twenty-nine RMDs were grouped into seven groups: Rheumatoid Arthritis, Spondyloarthritis, Crystal Arthropathies, Osteoarthritis, Soft Tissue Diseases, Connective Tissue Diseases, and Vasculitis. The relations between the deprivation and the occurrence of RMD and costs were explored in regression models adjusted for relevant confounders. Results Data from 1,923,156 adults were analysed. Mean age was 49.9 (SD18.4) years, 49% were males. Soft tissue diseases were the most prevalent RMD (5.5%, n=105,656), followed by osteoarthritis (2.2%, n=41,924). Socio-economic deprivation was associated with higher likelihood to have any of the 29 RMDs. The strongest socio-economic gradient was seen for the soft tissue diseases (OR 1.82 [95% CI 1.78; 1.85], most vs. least deprived), followed by osteoarthritis (OR 1.59 [1.54; 1.64]). Deprivation was also associated with higher costs across the majority of the conditions however patterns were more blurred, and inverse relationship was observed for connective tissue diseases, gout, hip osteoarthritis and undifferentiated (poly) arthritis. Conclusion Socio-economic deprivation is associated with increased occurrence of all RMDs, and in most cases more deprived patients incur higher health care costs