Catalan experience of deadoption of low-value practices in primary care.

Reducing ineffective practices is one way to ensure high-quality and efficient healthcare for the population. For this reason, several initiatives have been implemented worldwide to reduce low-value care. This article describes the experience of the Essencial project, a multifaceted deadoption strategy implemented in the Catalan primary care system. Lessons learnt from this project include the importance of considering the local context in deadoption strategies, providing adequate training and communication material to patients and clinicians and supporting the key role of clinical champions. Given the knowledge gaps regarding the conditions for successful deadoption strategies, the Catalan experience could provide enlightenment on how to implement, evaluate and sustain a large-scale collaborative deadoption strategy in primary healthcare.

[A deprivation index to reform the financing model of primary care in Catalonia (Spain)]. / Un índice de privación para reformar el modelo de financiación de la atención primaria en Cataluña.

OBJECTIVE: To build a deprivation index for the assignation of the budgets of the primary healthcare teams in Catalonia (Spain) valid for both urban and rural environments and updatable with greater frequency than indices built from census variables. METHOD: Starting from a review of the most common deprivation indices, variables were selected from sources that allow frequent updating and are representative at the territorial level of primary care. The correlations were calculated between the chosen variables and variables of need for healthcare and morbidity. principal components analysis was applied. Finally, the correlations of the index built with the MEDEA index and with variables of use of healthcare resources and morbidity was calculated stratifying by geographical dispersion. RESULTS: The variables of income, occupation and education are the ones with the highest correlation with the need for healthcare and morbidity. The composed socioeconomic index (CSI) ranges from -.01 to 5.68, with an average value of 2.60 and a standard deviation of .91. The correlation between the CSI and the MEDEA index is .89. The CSI correlates with use for healthcare in both urban and rural environments, although in rural environments the association is lower. CONCLUSIONS: The CSI was built with data that allow frequent updating and was integrated in the model for allocating resources to primary healthcare starting in 2017.

Differences in Results and Related Factors Between Hospital-at-Home Modalities in Catalonia: A Cross-Sectional Study.

Hospital-at-home (HaH) is a healthcare modality that provides active treatment by healthcare staff in the patient's home for a condition that would otherwise require hospitalization. The aims were to describe the characteristics of different types of hospital-at-home (HaH), assess their results, and examine which factors could be related to these results. A cross-sectional study based on data from all 2014 HaH contacts from Catalonia was designed. The following HaH modalities were considered-admission avoidance (n = 7,214; 75.1%) and early assisted discharge (n = 2,387; 24.9%). The main outcome indicators were readmission, mortality, and length of stay (days). Multivariable models were fitted to assess the association between explanatory factors and outcomes. Hospital admission avoidance is a scheme in which, instead of being admitted to acute care hospitals, patients are directly treated in their own homes. Early assisted discharge is a scheme in which hospital in-care patients continue their treatment at home. In the hospital avoidance modality, there were 8.3% readmissions, 0.9% mortality, and a mean length of stay (SD) of 9.6 (10.6) days. In the early assisted discharge modality, these figures were 7.9%, 0.5%, and 9.8 (11.1), respectively. In both modalities, readmission and mean length of stay were related to comorbidity and type of hospital, and mortality with age. The results of HaH in Catalonia are similar to those observed in other contexts. The factors related to these results identified might help to improve the effectiveness and efficiency of the different HaH modalities.

Socioeconomic inequalities in health and the use of healthcare services in Catalonia: analysis of the individual data of 7.5 million residents.

BACKGROUND: The aim of this study is to analyse the health status, the use of public healthcare services and the consumption of prescription drugs in the population of Catalonia, taking into consideration the socioeconomic level of individuals and paying special attention to vulnerable groups. METHODS: Cross-sectional study of the entire population resident in Catalonia in 2015 (7.5 million people) using administrative records. Twenty indicators are analysed related to health, the use of healthcare services and consumption of prescription drugs. Rates, frequencies and averages are obtained for the different variables stratified by age groups (under 15 years, 15-64 years and 65 years or older), gender and socioeconomic status (calculated on the basis of pharmacy copayment levels and Social Security benefits received). RESULTS: A socioeconomic gradient was observed in all the indicators analysed, in both sexes and in all age groups. Morbidity, use of mental healthcare centres, hospitalisation rates and probability of drug consumption among children is 3-7 times higher for those with low socioeconomic level respect to those with a higher one. In children and adults, the steepest gradient was found in the use of mental health services. Moreover, there are gender inequalities. CONCLUSION: There are significant socioeconomic inequalities in health status and in the use of healthcare services in the population of Catalonia. To respond to this situation, new policies on health and other areas, such as education and employment, are required, especially those that have an impact on early years.

Un índice de privación para reformar el modelo de financiación de la atención primaria en Cataluña / A deprivation index to reform the financing model of primary care in Catalonia (Spain)

OBJETIVO: Construir un índice de privación para la asignación del presupuesto de los equipos de atención primaria de Cataluña, válido tanto para entornos urbanos como rurales y actualizable con más frecuencia que los índices construidos con las variables censales. MÉTODO: A partir de la revisión de los índices de privación más comunes se seleccionaron las variables existentes de fuentes que permiten una actualización frecuente y que son representativas del ámbito territorial de las áreas básicas de salud. Se calcularon las correlaciones entre las variables escogidas y las variables de utilización de atención sanitaria y morbilidad. Se aplicó el análisis de componentes principales. Finalmente, se calcularon las correlaciones entre el índice construido y el índice MEDEA, y con variables de utilización de recursos y morbilidad para diferentes tramos de dispersión poblacional. RESULTADOS: Las variables de renta, ocupación y nivel de estudios son las que tienen más correlación con la utilización de atención sanitaria y la morbilidad. El índice socioeconómico compuesto (ISC) tiene un rango de −0,01 a 5,68, una media de 2,60 y una desviación estándar de 0,91. La correlación entre el ISC y el MEDEA es de 0,89. El ISC se correlaciona con la utilización de atención sanitaria tanto en los entornos urbanos como en los rurales, aunque en estos últimos la asociación es menor. CONCLUSIONES: El ISC se ha construido con datos que permiten una actualización frecuente, y se ha integrado en el modelo de asignación de recursos de la atención primaria a partir de 2017

OBJECTIVE: To build a deprivation index for the assignation of the budgets of the primary healthcare teams in Catalonia (Spain) valid for both urban and rural environments and updatable with greater frequency than indices built from census variables. METHOD: Starting from a review of the most common deprivation indices, variables were selected from sources that allow frequent updating and are representative at the territorial level of primary care. The correlations were calculated between the chosen variables and variables of need for healthcare and morbidity. principal components analysis was applied. Finally, the correlations of the index built with the MEDEA index and with variables of use of healthcare resources and morbidity was calculated stratifying by geographical dispersion. RESULTS: The variables of income, occupation and education are the ones with the highest correlation with the need for healthcare and morbidity. The composed socioeconomic index (CSI) ranges from −.01 to 5.68, with an average value of 2.60 and a standard deviation of .91. The correlation between the CSI and the MEDEA index is .89. The CSI correlates with use for healthcare in both urban and rural environments, although in rural environments the association is lower. CONCLUSIONS: The CSI was built with data that allow frequent updating and was integrated in the model for allocating resources to primary healthcare starting in 2017