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Objective: Few published studies have described multidisciplinary therapeutic strategies for lung cancer. This study aims to describe the different approaches used for treating lung cancer in Catalonia in 2014 and 2018 and to assess the associated cost and impact on patient survival. Methods: A retrospective observational cohort study using data of patients with lung cancer from health care registries in Catalonia was carried out. We analyzed change in treatment patterns, costs and survival according to the year of treatment initiation (2014 vs. 2018). The Kaplan–Meier method was used to estimate survival, with the follow-up until 2021. Results: From 2014 to 2018, the proportion of patients undergoing surgery increased and treatments for unresectable tumors decreased, mainly in younger patients. Immunotherapy increased by up to 9% by 2018. No differences in patient survival were observed within treatment patterns. The mean cost per patient in the first year of treatment increased from EUR 14,123 (standard deviation [SD] 4327) to EUR 14,550 (SD 3880) in surgical patients, from EUR 4655 (SD 3540) to EUR 5873 (SD 6455) in patients receiving curative radiotherapy and from EUR 4723 (SD 7003) to EUR 6458 (SD 10,116) in those treated for unresectable disease. Conclusions: From 2014 to 2018, surgical approaches increased in younger patients. The mean cost of treating patients increased, especially in pharmaceutical expenditure, mainly related to the use of several biomarker-targeted treatments. While no differences in overall patient survival were observed, it seems reasonable to expect improvements in this outcome in upcoming years as more patients receive innovative treatments.

ObjectivesTo investigate whether the effect of chronological age on the risk of developing critical illness in COVID-19 hospitalized individuals is attenuated, and to which extent, when adjusting for increasingly exhaustive measures of the comorbidity burden.DesignRetrospective assessment of electronic health records.SettingAll public hospitals of the Catalan Institute of Health (Catalonia; North-East Spain; 7.7 million inhabitants), which account for 30% of all hospital admissions in Catalonia.ParticipantsWe included all individuals admitted to the hospital with COVID-19 as the main diagnosis between March 1, 2020, and January 31, 2022. Vaccinated individuals and those admitted within the first of the six COVID-19 epidemic waves were excluded from the primary analysis but were included in secondary analyses.Main outcome measuresThe primary composite outcome was critical illness, defined as the need for invasive mechanical ventilation, transfer to the intensive care unit (ICU), or in-hospital death (any of them). Explanatory variables included age, sex, and four summary measures of comorbidity burden on admission: the Charlson index (17 diagnostic group codes), the Elixhauser index and count (31 diagnostic group codes), and the Queralt DxS index (3,145 diagnostic group codes). All models were adjusted by wave and center. The proportion of the effect of age attributable to comorbidity burden was assessed using a causal mediation analysis.ResultsThe primary analysis included 10,090 hospitalizations due to COVID-19; of them, 3,524 experienced a critical illness. The frequency of critical illness increased with age and comorbidity burden on admission, irrespective of the measure used. In multivariate analyses, the effect size of age decreased with the number of diagnoses considered to estimate comorbidity burden. When adjusting for the Queralt DxS index, age showed a minimal contribution to critical illness; according to the causal mediation analysis, comorbidity burden on admission explained the 95.3% (95% CI 82.1% −112.7%) of the observed effect of age on critical illness.ConclusionsWhen measured exhaustively, comorbidity burden rather than chronological age explains the increased risk of critical illness observed in patients hospitalized with COVID-19.Summary boxWhat is already known on this topicAge is broadly acknowledged as a critical risk factor for developing critical illness in individuals hospitalized due to COVID-19.When adjusting for other underlying factors, such as comorbidities, the effect size of age for predicting critical illness decreases; nevertheless, most studies have suggested that age remains independently associated with COVID-19 outcomes.What this study addsThe observed contribution of chronological age to the risk of critical illness in hospitalized COVID-19 patients decreases with the exhaustivity of the measure of comorbidity burden.When adjusting for a comprehensive comorbidity index that considers all possible clinical conditions from a weighted list of 3,145 possible diagnostic groups, age has little or no relevant effect on the risk of critical illness.Mediation analyses confirm that the effect of chronological age on COVID-19 outcomes can be explained by comorbidity burden.

Aims To evaluate the burden of cardiovascular risk factors and disease (CVD) among five Asian groups living in Catalonia (Spain): Indian, Pakistani, Bangladeshi, Filipino, and Chinese. Methods and results Retrospective cohort study using the Catalan Health Surveillance System database including 42 488 Pakistanis, 40 745 Chinese, 21 705 Indians, 9544 Filipinos, and 6907 Bangladeshis; and 5.3 million native individuals (‘locals’). We estimated the age-adjusted prevalence (as of 31 December 2019) and incidence (during 2019) of diabetes, hypertension, hyperlipidaemia, obesity, tobacco use, coronary heart disease (CHD), cerebrovascular disease, atrial fibrillation, and heart failure (HF). Bangladeshis had the highest prevalence of diabetes (17.4% men, 22.6% women) followed by Pakistanis. Bangladeshis also had the highest prevalence of hyperlipidaemia (23.6% men, 18.3% women), hypertension among women (24%), and incident tobacco use among men. Pakistani women had the highest prevalence of obesity (28%). For CHD, Bangladeshi men had the highest prevalence (7.3%), followed by Pakistanis (6.3%); and Pakistanis had the highest prevalence among women (3.2%). For HF, the prevalence in Pakistani and Bangladeshi women was more than twice that of locals. Indians had the lowest prevalence of diabetes across South Asians, and of CHD across South Asian men, while the prevalence of CHD among Indian women was twice that of local women (2.6% vs. 1.3%). Filipinos had the highest prevalence of hypertension among men (21.8%). Chinese men and women had the lowest prevalence of risk factors and CVD. Conclusions In Catalonia, preventive interventions adapted to the risk profile of different Asian immigrant groups are needed, particularly for Bangladeshis and Pakistanis.

Introduction and objectives Potassium derangements are frequent among patients with chronic cardiovascular conditions. Studies on the associations between potassium derangements and clinical outcomes have yielded mixed findings, and the implications for health care expenditure are unknown. We assessed the population-based associations between hyperkalemia, hypokalemia and clinical outcomes and health care costs, in patients with chronic heart failure, chronic kidney disease, diabetes mellitus, hypertension, and ischemic heart disease. Methods Population-based, longitudinal study including up to 36 269 patients from a health care area with at least one of the above-mentioned conditions. We used administrative, hospital and primary care databases. Participants were followed up between 2015 and 2017, were aged ≥ 55 years and had at least 1 potassium measurement. Four analytic designs were used to evaluate prevalent and incident cases and the use of renin-angiotensin-aldosterone system inhibitors. Results Hyperkalemia was twice as frequent as hypokalemia. On multivariable-adjusted analyses, hyperkalemia was robustly and significantly associated with an increased risk of all-cause death (HR from Cox regression models ranging from 1.31–1.68) and with an increased odds of a yearly health care expenditure > 85th percentile (OR, 1.21–1.29). Associations were even stronger in hypokalemic patients (HR for all-cause death, 1.92–2.60; OR for health care expenditure > percentile 85th, 1.81–1.85). Conclusions Experimental studies are needed to confirm whether the prevention of potassium derangements reduces mortality and health care expenditure in these chronic conditions. Until then, our findings provide observational evidence on the potential importance of maintaining normal potassium levels.

Resumen Introduccion y objetivos Las alteraciones de la potasemia son frecuentes en las enfermedades cardiovasculares cronicas. El objetivo del estudio es evaluar las asociaciones de la hiperpotasemia y la hipopotasemia con eventos clinicos y costes sanitarios en pacientes con insuficiencia cardiaca, enfermedad renal cronica, diabetes mellitus, hipertension y cardiopatia isquemica. Metodos Estudio longitudinal que incluyo a 36.269 pacientes de un Area de Salud que tuvieran al menos una de las afecciones mencionadas. Se utilizaron bases de datos administrativas, hospitalarias y de atencion primaria. Se siguio a los participantes entre 2015 y 2017; estos tenian 55 o mas anos y al menos 1 medicion de potasio. Se utilizaron 4 disenos analiticos para evaluar la prevalencia y la incidencia y el uso de inhibidores del sistema renina-angiotensina-aldosterona. Resultados La hiperpotasemia fue 2 veces mas frecuente que la hipopotasemia. En los analisis ajustados, la hiperpotasemia se asocio de manera significativa con un mayor riesgo de muerte por todas las causas (HR de los modelos de regresion de Cox entre 1,31 y 1,68) y con un aumento de las probabilidades de que los gastos anuales de atencion sanitaria superen el 85% (OR entre 1,21 y 1,29). Las asociaciones fueron aun mayores en los pacientes hipopotasemicos (HR para la muerte por todas las causas, 1,92-2,60; OR para los gastos de atencion sanitaria > percentil 85, 1,81-1,85). Conclusiones Se necesitarian estudios experimentales para confirmar si la prevencion de los trastornos del potasio reduce la mortalidad y los gastos sanitarios en estas enfermedades cronicas. Hasta entonces, nuestros hallazgos proporcionan conclusiones observacionales sobre la importancia de mantener normales las concentraciones de potasio.

The centralization of complex surgical procedures for cancer in Catalonia may have led to geographical and socioeconomic inequities. In this population-based cohort study, we assessed the impacts of these two factors on 5-year survival and quality of care in patients undergoing surgery for rectal cancer (2011–12) and pancreatic cancer (2012–15) in public centers, adjusting for age, comorbidity, and tumor stage. We used data on the geographical distance between the patients’ homes and their reference centers, clinical patient and treatment data, income category, and data from the patients’ district hospitals. A composite ‘textbook outcome’ was created from five subindicators of hospitalization. We included 646 cases of pancreatic cancer (12 centers) and 1416 of rectal cancer (26 centers). Distance had no impact on survival for pancreatic cancer patients and was not related to worse survival in rectal cancer. Compared to patients with medium–high income, the risk of death was higher in low-income patients with pancreatic cancer (hazard ratio (HR) 1.46, 95% confidence interval (CI) 1.15–1.86) and very-low-income patients with rectal cancer (HR 5.14, 95% CI 3.51–7.52). Centralization was not associated with worse health outcomes in geographically dispersed patients, including for survival. However, income level remained a significant determinant of survival.

BackgroundComorbidity burden has been identified as a relevant predictor of critical illness in patients hospitalized with coronavirus disease 2019 (COVID-19). However, comorbidity burden is often represented by a simple count of few conditions that may not fully capture patients’ complexity.PurposeTo evaluate the performance of a comprehensive index of the comorbidity burden (Queralt DxS), which includes all chronic conditions present on admission, as an adjustment variable in models for predicting critical illness in hospitalized COVID-19 patients and compare it with two broadly used measures of comorbidity.Patients and methodsWe analyzed data from all COVID-19 hospitalizations reported in eight public hospitals of Catalonia (North-East Spain) between June 15 and December 8 2020. The primary outcome was a composite of critical illness that included the need for invasive mechanical ventilation, transfer to ICU, or in-hospital death. Predictors included age, sex, and comorbidities present on admission measured using three indices: the Charlson index, the Elixhauser index, and the Queralt DxS index for comorbidities on admission. The performance of different fitted models was compared using various indicators, including the area under the receiving operating characteristics curve (AUC).ResultsOur analysis included 4,607 hospitalized COVID-19 patients. Of them, 1,315 experienced critical illness. Comorbidities significantly contributed to predicting the outcome in all summary indices used. The AUC for prediction of critical illness was 0.641 (95% CI 0.624-0.660) for the Charlson index, 0.665 (0.645-0.681) for the Elixhauser index, and 0.787 (0.773-0.801) for Queralt DxS. Other metrics of model performance also showed Queralt DxS being consistently superior to the other indices.ConclusionIn our analysis, the ability of comorbidity indices to predict hospital outcomes in hospitalized COVID-19 patients increased with their exhaustivity. The comprehensive Queralt DxS index may improve the accuracy of predictive models for resource allocation and clinical decision-making in the hospital setting.

The shortage of recently approved vaccines against the severe acute respiratory syndrome coronavirus (SARS-CoV-2) has highlighted the need for evidence-based tools to prioritize healthcare resources for people at higher risk of severe coronavirus disease 2019 (COVID-19). Current evidence indicates that age is far from accurate in identifying the risk of severe illness; furthermore, the count of individual risk factors has limited applicability to population-based “stratify-and-shield” strategies. We developed a COVID-19 risk stratification system that allows allocating people into four mutually-exclusive risk categories based on multivariate models for hospital admissions, transfer to intensive care unit (ICU), and mortality among the general population. The model was developed using clinical, hospital, and epidemiological data from the entire population of Catalonia (North-East Spain; 7.5 million people) and validated using an independent dataset of 218,329 individuals with PCR-confirmed COVID-19, who were infected after developing the model. This showed high discrimination capacity, with an area under the curve of the receiving operating characteristics of 0.85 (95% CI 0.85–0.85) for hospital admissions, 0.86 (0.86–0.97) for ICU transfers, and 0.96 (0.96–0.96) for deaths. Our results provide clinicians and policymakers with an evidence-based tool for prioritizing COVID-19 healthcare resources other population groups aside from those with higher exposure to SARS-CoV-2 and frontline workers.

We evaluated the association between individual-level socioeconomic status (SES), life expectancy, and mortality, in adult men and women from the general population living in Catalonia, a universal healthcare coverage setting. We used the Catalan Health Surveillance System database, which includes individual-level information on sociodemographic characteristics and mortality for all residents of Catalonia (Spain). We categorized individuals as high, medium, low or very low SES based on annual personal income and welfare receipt. We used 2016 mortality data to estimate life expectancy at age 18, and the probability of death by age, sex and SES categories. We followed a total of 6,027,424 Catalan residents in 2016. Men and women of very low SES had 12.0 and 9.4 years lower life expectancy compared to men and women of high SES, respectively. Low SES was also strongly associated with mortality in both men and women of any age. In the entire adult population of Catalonia, despite the availability of universal, high quality healthcare coverage, low SES is associated with lower life expectancy and higher mortality. Solutions to these large inequalities may combine tailored health promotion and management interventions, with solutions coming from outside of the health sector.

To evaluate the associations between individual income, all-cause mortality and use of healthcare resources in a very large population of chronic heart failure (CHF) patients living in Catalonia (Spain), where access to public healthcare is granted by law.We used 2016 data from the Catalan Health Surveillance System, a large, exhaustive, administrative healthcare database which includes information on medical diagnoses, healthcare resource use, and individual income for all Catalan residents (N = 7,638,524). Individual annual income was categorized as high (100,000€), medium (18,000-100,000€), low (18,000€), and very low (welfare support). Among 155,883 CHF patients, lower individual income was associated with a shorter life expectancy at age 50 (life expectancy for high income patients 22.2 years, for very low income patients 12.8), and were independently associated with higher all-cause mortality adjusting for age, sex, comorbidities, and duration of the CHF diagnosis (odds ratio very low vs. medium income 1.21 [95% CI 1.11, 1.33]). Also, in patients with lower income levels the burden of public healthcare resource use was displaced towards urgent hospitalizations and frequent emergency department visits, as opposed to regular, specialized CHF ambulatory-based care.In a very large population of CHF patients with access to universal healthcare, lower income was independently associated with higher mortality and with lower use of ambulatory-based healthcare resources. Our findings suggest that CHF patients may benefit from systematic assessment of their socioeconomic status, as this may aid the identification of vulnerable subgroups who may benefit from tailored health education and management.

Resumen: Introducción: Los grupos de morbilidad ajustados (GMA) y los clinical risk groups (CRG) son herramientas de estratificación poblacional basada en la morbilidad que permiten clasificar a los pacientes en categorías mutuamente excluyentes. Objetivo: Comparar la estratificación, según niveles de complejidad, proporcionada por los GMA con la de los CRG y con la realizada ad-hoc por los evaluadores. Diseño: Muestra aleatoria por estratos de riesgo de morbilidad. Emplazamiento: Cataluña. Participantes: Cuarenta médicos de atención primaria emparejados 2 a 2. Intervenciones: Cada pareja de evaluadores tuvo que validar 25 historias. Mediciones principales: Se evaluó la concordancia entre evaluadores, y entre los evaluadores y los resultados obtenidos por los 2 agrupadores de morbilidad con el índice kappa, la sensibilidad, la especificidad, el valor predictivo positivo y el negativo. Resultados: La concordancia entre evaluadores se situó alrededor del valor kappa 0,75 (valor medio = 0,67), entre los GMA y los evaluadores fue similar (valor medio = 0,63), y más elevada que para los CRG (valor medio = 0,35). Los profesionales otorgaron una puntuación de 7,5 a la bondad de ambos agrupadores, aunque para los estratos de mayor complejidad, según asignación de los profesionales, los GMA obtuvieron mejores puntuaciones que los CRG. Los profesionales prefirieron mayoritariamente los GMA frente a los CRG. Estas diferencias se incrementaron con el aumento de la complejidad de los pacientes según el criterio clínico.Globalmente, se encontró menos de un 2% de errores graves de clasificación proporcionada por ambos agrupadores. Conclusión: Los profesionales consideraron que ambos agrupadores clasificaban adecuadamente a la población, aunque los GMA tienen un mejor comportamiento en los estratos que los profesionales identifican como de mayor complejidad. Además, en la mayoría de los casos, los evaluadores clínicos prefirieron los GMA. Abstract: Introduction: Adjusted Morbidity Groups (GMAs) and the Clinical Risk Groups (CRGs) are population morbidity based stratification tools which classify patients into mutually exclusive categories. Objetive: To compare the stratification provided by the GMAs, CRGs and that carried out by the evaluators according to the levels of complexity. Design: Random sample stratified by morbidity risk. Location: Catalonia. Participants: Forty paired general practitioners in the primary care, matched pairs. Interventions: Each pair of evaluators had to review 25 clinical records. Main outputs: The concordance by evaluators, and between the evaluators and the results obtained by the 2 morbidity tools were evaluated according to the kappa index, sensitivity, specificity, and positive and negative predicted values. Results: The concordance between general practitioners pairs was around the kappa value 0.75 (mean value = 0.67), between the GMA and the evaluators was similar (mean value = 0.63), and higher than for the CRG (mean value = 0.35). The general practitioners gave a score of 7.5 over 10 to both tools, although for the most complex strata, according to the professionals’ assignment, the GMA obtained better scores than the CRGs. The professionals preferred the GMAs over the CRGs. These differences increased with the complexity level of the patients according to clinical criteria.Overall, less than 2% of serious classification errors were found by both groupers. Conclusion: The evaluators considered that both grouping systems classified the studied population satisfactorily, although the GMAs showed a better performance for more complex strata. In addition, the clinical raters preferred the GMAs in most cases. Palabras clave: Agrupador de morbilidad, Multimorbilidad, Validación clínica, Keywords: Morbidity grouper, Multimorbidity, Clinical Validation

Resumen: Objetivo: Analizar la distribución del gasto sanitario según el ámbito asistencial y las características de los pacientes, utilizando microdatos del uso de servicios sanitarios del total de la población de Cataluña (España). Método: Se ha aplicado una tarifa o un gasto indirecto a todos los actos sanitarios financiados por CatSalut durante 2014, computando el gasto sanitario realizado por cada persona y sumando para todos los habitantes de Cataluña. Resultados: La suma del gasto sanitario realizado por todos los habitantes de Cataluña representa el 97,0% del presupuesto de CatSalut. La mitad de la población origina el 3,6% del gasto sanitario total (71 € por persona); un 1% de la población gastó el 23% del gasto (22.852 € por persona). El gasto medio más elevado, tanto en mujeres como en hombres, se da entre los 80 y los 89 años de edad. La población con una enfermedad crónica tiene un gasto medio anual de 413 €; con cinco, de 2413 €; y con 10, de 9626€. El gasto medio varía según patologías, desde los 2854 € en los pacientes con depresión grave a los 8097 € de los pacientes con infección por el virus de la inmunodeficiencia humana/sida. Conclusiones: Los resultados son sumamente útiles para la planificación de los servicios sanitarios y para la priorización de intervenciones de política sanitaria en los colectivos con más necesidades. Abstract: Objective: To analyse the distribution of the expenditure according to the healthcare services and characteristics of patients, using the microdata of the Catalan population's use of healthcare services. Methods: A fee or an indirect cost has been applied to all healthcare activities financed by CatSalut during 2014, computing the health expenditure made up by each person and adding it all up for the inhabitants of Catalonia (Spain). Results: The sum of the healthcare expenditure made by all the inhabitants of Catalonia represents 97.0% of the CatSalut budget. Half of the population accounts for 3.6% of total healthcare expenditure (71€ per person); 1% of the population spends 23% of the expenditure (22,852€ per person). The highest average expenditure, in both women and men, occurs between the age of 80 and 89. The population with a chronic disease has an average annual expenditure of 413€, with 5 of 2,413€, and 10 of 9,626€. The average cost varies according to pathologies, from 2,854€ in patients with severe depression to 8,097€ in patients with HIV-AIDS. Conclusions: The results are extremely useful for healthcare planning and for the prioritization of health policy interventions in groups with most needs. Palabras clave: Gasto sanitario, Política sanitaria, Planificación sanitaria, Poblacional, Estado de salud, Keywords: Health care cost, Health policy, Health planning, Population-based, Health status

BackgroundMultimorbidity measures are useful for resource planning, patient selection and prioritization, and factor adjustment in clinical practice, research, and benchmarking. We aimed to compare the explanatory performance of the adjusted morbidity group (GMA) index in predicting relevant healthcare outcomes with that of other quantitative measures of multimorbidity.MethodsThe performance of multimorbidity measures was retrospectively assessed on anonymized records of the entire adult population of Catalonia (North-East Spain). Five quantitative measures of multimorbidity were added to a baseline model based on age, gender, and socioeconomic status: the Charlson index score, the count of chronic diseases according to three different proposals (i.e., the QOF, HCUP, and Karolinska institute), and the multimorbidity index score of the GMA tool. Outcomes included all-cause death, total and non-scheduled hospitalization, primary care and ER visits, medication use, admission to a skilled nursing facility for intermediate care, and high expenditure (time frame 2017). The analysis was performed on 10 subpopulations: all adults (i.e., aged > 17 years), people aged > 64 years, people aged > 64 years and institutionalized in a nursing home for long-term care, and people with specific diagnoses (e.g., ischemic heart disease, cirrhosis, dementia, diabetes mellitus, heart failure, chronic kidney disease, and chronic obstructive pulmonary disease). The explanatory performance was assessed using the area under the receiving operating curves (AUC-ROC) (main analysis) and three additional statistics (secondary analysis).ResultsThe adult population included 6,224,316 individuals. The addition of any of the multimorbidity measures to the baseline model increased the explanatory performance for all outcomes and subpopulations. All measurements performed better in the general adult population. The GMA index had higher performance and consistency across subpopulations than the rest of multimorbidity measures. The Charlson index stood out on explaining mortality, whereas measures based on exhaustive definitions of chronic diagnostic (e.g., HCUP and GMA) performed better than those using predefined lists of diagnostics (e.g., QOF or the Karolinska proposal).ConclusionsThe addition of multimorbidity measures to models for explaining healthcare outcomes increase the performance. The GMA index has high performance in explaining relevant healthcare outcomes and may be useful for clinical practice, resource planning, and public health research.

OBJECTIVETo identify the different subpopulations that are susceptible for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and hospitalisation or death due to coronavirus disease 2019 (COVID-19) in Catalonia, Spain.DESIGNCross-sectional study.SETTINGData collected from the Catalan Health Surveillance System (CatSalut) in Catalonia, a region of Spain.PARTICIPANTSUsing data collected between 1 March and 1 June 2020, we conducted the following comparative analyses: people infected by SARS-CoV-2 (328 892) vs Catalonia’s entire population (7 699 568); COVID-19 cases who required hospitalisation (37 638) vs cases who did not require hospitalisation (291 254); and COVID-19 cases who died during the study period vs cases who did not die during the study period (12 287).MAIN OUTCOME MEASURESThree clinical outcomes related to COVID-19 (infection, hospitalisation, or death). We analysed sociodemographic and environment variables (such as residing in a nursing home) and the presence of previous comorbidities.RESULTSA total of 328 892 cases were considered to be infected with SARS-CoV-2 (4.27% of total population). The main risk factors for the diagnostic were: female gender (risk ratio [RR] =1.49; 95% confidence interval [95% CI] =1.48-1.50), age (4564 years old; RR=1.02; 95% CI=1.01-1.03), high comorbidity burden (GMA index) (RR=3.03; 95% CI=2.97-3.09), reside in a nursing home (RR=11.82; 95% CI=11.66-11.99), and smoking (RR=1.06; 95% CI=1.05-1.07). During the study period, there were 37 638 (11.4 %) hospitalisations due to COVID-19, and the risk factors were: male gender (RR=1.45; 95% CI=1.43-1.48), age > 65 (RR=2.38; 95% CI=2.28-2.48), very low individual income (RR=1.03; 95% CI=0.97-1.08), and high burden of comorbidities (GMA index) (RR=5.15; 95% CI=4.89-5.42). The individual comorbidities with higher burden were obesity (RR=1.23; 95% CI=1.20-1.25), chronic obstructive pulmonary disease (RR=1.19; 95% CI=1.15-1.22), heart failure (RR=1.19; 95% CI=1.16-1.22), diabetes mellitus (RR=1.07; 95% CI=1.04-1.10), and neuropsychiatric comorbidities (RR=1.06; 95% CI=1.03-1.10). A total of 12 287 deaths (3.73%) were attributed to COVID-19, and the main risk factors were: male gender (RR=1.73; 95% CI=1.67-1.81), age > 65 (RR=37.45; 95% CI=29.23-47.93), residing in a nursing home (RR=9.22; 95% CI=8.81-9.65), and high burden of comorbidities (GMA index) (RR=5.25; 95% CI=4.60-6.00). The individual comorbidities with higher burden were: heart failure (RR=1.21; 95% CI=1.16-1.22), chronic kidney disease (RR=1.17; 95% CI=1.13-1.22), and diabetes mellitus (RR=1.10; 95% CI=1.06-1.14). These results did not change significantly when we considered only PCR-positive patients.CONCLUSIONSFemale gender, age between 45 to 64 years old, high burden of comorbidities, and factors related to environment (nursing home) play a relevant role in SARS-CoV-2 infection and transmission. In addition, we found risk factors for hospitalisation and death due to COVID-19 that had not been described to date, including comorbidity burden, neuro-psychiatric disorders, and very low individual income. This study supports interventions for transmission control beyond stratify-and-shield strategies focused only on protecting those at risk of death. Future COVID-19 studies should examine the role of gender, the burden of comorbidities, and socioeconomic status in disease transmission, and should determine its relationship to workplaces, especially healthcare centres and nursing homes.

Background Planning population care in a specific health care setting requires deep knowledge of the clinical characteristics of the target care recipients, which tend to be country specific. Our area virtually lacks any descriptive, far-reaching publications about institutionalized older people (IOP). We aimed to investigate the demographic and clinical characteristics of institutionalized older people (IOP) ≥65 years old and compare them with those of the rest of the population of the same age.Methods Retrospective analysis (total cohort approach) of clinical and resource-use characteristics of IOP and non-IOP older than 65 years in Catalonia (North-East Spain). Variables analysed included age and sex, diagnoses, morbidity burden—using Adjusted Morbidity Groups (GMA, Grupos de Morbilidad Ajustada)—, mortality, use of resources, and medications taken. All data were obtained from the administrative database of the local healthcare system.Results This study included 93,038, 78,458, 68,545 and 67,456 IOP from 2011, 2013, 2015 and 2017, respectively. In this interval, an increase in median age (83 vs. 87 years), in women (68.64% vs. 72.11%) and in annual mortality (11.74% vs. 20.46%) was observed. Compared with non-IOP (pConclusions There is a growing gap between the clinical and demographic characteristics of age-matched IOP and non-IOP, which overlaps with a higher mortality rate of IOP. The profile of resources utilization of IOP compared with non-IOP strongly suggests a deficiency of preventive actions and stresses the need to rethink the care model for IOP from a social and health care perspective.

Epidemiological studies on heart failure (HF) using large health care databases are becoming increasingly frequent, as they represent an invaluable opportunity to characterize the importance and risk factors of HF from a population perspective. Nevertheless, because of its complex diagnosis and natural history, the heterogeneous use of the relevant terminology in routine clinical practice, and the limitations of some disease coding systems, HF can be a challenging condition to assess using large health care databases as the main source of information. In this narrative review, we discuss some of the challenges that researchers may face, with a special focus on the identification and validation of chronic HF cases and acute HF decompensations. For each of these challenges, we present some potential solutions inspired by the literature and/or based on our research experience, aimed at increasing the internal validity of research and at informing its interpretation. We also discuss future directions on the field, presenting constructive recommendations aimed at facilitating the conduct of valid epidemiological studies on HF in the coming years.

ResumenSe ha desarrollado un agrupador de morbilidad adaptado a nuestro entorno sanitario que permite clasificar a la población en 6 grupos de morbilidad, divididos a su vez en 5 niveles de complejidad, más un grupo de población sana; de este modo la población queda agrupada en 31 categorías mutuamente excluyentes.Se presentan resultados de la estratificación en Cataluña.Los grupos de morbilidad ajustados (GMA) son un agrupador de morbilidad comparable a otros existentes en el mercado, pero desarrollado con los datos de nuestro sistema sanitario. Permite generar una adecuada estratificación poblacional y es capaz de identificar a poblaciones diana. Muestra buenos resultados explicativos en indicadores de uso de recursos sanitarios.El Ministerio de Sanidad está impulsando la implantación del agrupador en el Sistema Nacional de Salud.AbstractThe Adjusted Morbidity Groups (GMA) is a new morbidity measurement developed and adapted to the Spanish healthcare System. It enables the population to be classified into 6 morbidity groups, and in turn divided into 5 levels of complexity, along with one healthy population group. Consequently, the population is divided into 31 mutually exclusive categories.The results of the stratification in Catalonia are presented. GMA is a method for grouping morbidity that is comparable to others in the field, but has been developed with data from the Spanish health system. It can be used to stratify the population and to identify target populations. It has good explanatory and predictive results in the use of health resources indicators.The Spanish Ministry of Health is promoting the introduction of the GMA into the National Health System.

Miguel Cainzos-Achirica was funded by a research grant frorn the Spanish Society of Cardiology.

Objectives To assess the impact of hip fracture (HF) on health care expenditures and resource use. Design Observational, retrospective study. An administrative registry was used to obtain sociodemographic, clinical, and expenditure data of patients treated in centers all over Catalonia (North-East Spain). Setting and participants Male and female patients aged 65 years or older admitted to a Catalonian hospital due to hip fracture (HF) between January 1 2012, and December 31, 2016. Measures The study data set included the expenditure and frequency of using nonemergency transport, rehabilitation, skilled nursing facility, specialist visits, admissions to the emergency department, hospitalization, pharmacy, and primary care. The patient status at each time point included living at home, staying in hospital, staying in a skilled nursing facility, institutionalized in a nursing home, and death. Results The record included 38,628 patients (74.4% female) with a mean [standard deviation (SD)] age of 84.9 (7.07) years. The average expenditure per patient during the first year after hospital admission was €11,721.06, the index hospitalization being the leading expenditure (€4740.29). Expenditures related to hospitalization and skilled nursing facility remained higher than preinjury throughout the 3 years following HF. Three years after the index admission, 44.9% of patients had died, 39.7% were living in their homes, 14.2% were in a nursing home, 0.9% were in a skilled nursing facility, and 0.3% were in hospital. The expenditure of hospitalizations, primary care, and visits to the emergency department increased few months before the HF. Conclusions In patients hospitalized for HF, the expenditure per patient decreases after hospital discharge but the use of healthcare resources is not restored to preinjury values. The increase of expenditures associated with primary care services, hospitalization, and emergency department services during the few months preceding hospital admission suggests a decline of health status in these patients.

Importance The increased mortality after hip fracture (HF) is caused by multiple factors, and large samples are needed to assess the weight of each factor. To date, few studies have investigated these factors through a total cohort approach, and the complexity of underlying medical conditions has not been considered. Objective To investigate the influence of demographic and clinical characteristics on increased mortality risk in elderly patients with hip fracture (HF). Design Retrospective, total cohort study collecting 4-year data. Setting All hospitals and primary care units owned by, or associated with, Catalonia's local health department (CatSalut) (north-east Spain). Participants All patients aged ≥65 years, admitted to Catalan hospitals from CatSalut because of a HF between 1st January 2012 and 31st December 2015. Exposure Hip fracture. Main outcome measures The main outcome was survival. Measures regarding demographic and clinical characteristics at the moment of hospital admission included age, sex, osteoporosis treatment, previous fractures, type of intervention, nutritional status, and comorbidities. Patients were stratified using the Adjusted Morbidity Groups (GMA) risk assessment tool. Results Of the 30,552 patients included in the study sample, 10,439 (34%) died during follow-up, 6821 (22%) within the first year after hospital admission. Mean (SD) age was 84 (7) years; 75% were female. Baseline factors with greater influence on survival were age (HRs 1.44 [95% CI 1.22–1.70], 2.38 [2.03–2.79], and 4.38 [3.73–5.15] for age groups 70–79, 80–89, and >89, respectively), underweight (HR 1.65 [1.36–2.01]), lack of surgical intervention (HR 2.64 [2.47–2.83]), and very high risk stratum of GMA risk (HR 1.58 [1.45–1.73]). Vitamin D/calcium supplementation and osteoporosis treatment showed a significant but moderate influence on mortality (HRs 0.84 (0.79–0.88) and 0.92 [0.85–0.99], respectively). Conclusions and relevance In elderly patients with HF, age and health status factors at hospital admission have the greatest impact on mortality risk after hospital admission. Our findings encourage a comprehensive intervention aimed at improving underlying medical conditions of HF patients.

Resumen Objetivo Comparar el rendimiento referente a la bondad de ajuste y el poder explicativo de 2 agrupadores de morbilidad en el ámbito de la atención primaria (AP): los grupos de morbilidad ajustados (GMA) y los clinical risk groups (CRG). Diseño Estudio transversal. Emplazamiento Ámbito de la AP del Instituto Catalán de la Salud (ICS), Cataluña, España. Participantes Población asignada a centros de AP del ICS para el año 2014. Mediciones principales Se analizan 3 indicadores de interés, como son el ingreso urgente, el número de visitas y el gasto en farmacia. Se aplica un análisis estratificado por centros ajustando modelos lineales generalizados a partir de las variables edad, sexo y agrupador de morbilidad para explicar cada una de las 3 variables de interés. Las medidas estadísticas para analizar el rendimiento de los distintos modelos aplicados son el índice de Akaike, el índice de Bayes y la seudovariabilidad explicada mediante cambio de deviance. Resultados Los resultados muestran que en el ámbito de la AP del ICS el poder explicativo de los GMA es superior al ofrecido por los CRG, especialmente para el caso de las visitas y el gasto en farmacia. Conclusiones El rendimiento de los GMA en el ámbito de la AP del ICS es superior al mostrado por los CRG.

To analyse the distribution of the expenditure according to the healthcare services and characteristics of patients, using the microdata of the Catalan population's use of healthcare services.A fee or an indirect cost has been applied to all healthcare activities financed by CatSalut during 2014, computing the health expenditure made up by each person and adding it all up for the inhabitants of Catalonia (Spain).The sum of the healthcare expenditure made by all the inhabitants of Catalonia represents 97.0% of the CatSalut budget. Half of the population accounts for 3.6% of total healthcare expenditure (71€ per person); 1% of the population spends 23% of the expenditure (22,852€ per person). The highest average expenditure, in both women and men, occurs between the age of 80 and 89. The population with a chronic disease has an average annual expenditure of 413€, with 5 of 2,413€, and 10 of 9,626€. The average cost varies according to pathologies, from 2,854€ in patients with severe depression to 8,097€ in patients with HIV-AIDS.The results are extremely useful for healthcare planning and for the prioritization of health policy interventions in groups with most needs.

ObjectiveTo describe the prevalence and incidence of cardiovascular risk factors, established cardiovascular disease (CVD) and cardiovascular medication use, among immigrant individuals of diverse national origins living in Catalonia (Spain), a region receiving large groups of immigrants from all around the world, and with universal access to healthcare.MethodsWe conducted a population-based analysis including >6 million adult individuals living in Catalonia, using the local administrative healthcare databases. Immigrants were classified in 6 World Bank geographic areas: Latin America/Caribbean, North Africa/Middle East, sub-Saharan Africa, East Asia and South Asia. Prevalence calculations were set as of 31 December 2017.ResultsImmigrant groups were younger than the local population; despite this, the prevalence of CVD risk factors and of established CVD was very high in some immigrant subgroups compared with local individuals. South Asians had the highest prevalence of diabetes, and of hyperlipidemia among adults aged ConclusionsThe high prevalence of risk factors and established CVD among South Asians and sub-Saharan Africans stresses the need for tailored, aggressive health promotion interventions. These are likely to be beneficial in Catalonia, and in countries receiving similar migratory fluxes, as well as in their countries of origin.

Heart failure (HF) is one of the diseases with greater healthcare expenditure. However, little is known about the cost of HF at a population level. Hence, our aim was to study the population-level distribution and predictors of healthcare expenditure in patients with HF.This was a population-based longitudinal study including all prevalent HF cases in Catalonia (Spain) on 31 December 2012 (n = 88 195). We evaluated 1-year healthcare resource use and expenditure using the Health Department (CatSalut) surveillance system that collects detailed information on healthcare usage for the entire population. Mean age was 77.4 (12) years; 55% were women. One-year mortality rate was 14%. All-cause emergency department visits and unplanned hospitalizations were required at least once in 53.4% and 30.8% of patients, respectively. During 2013, a total of €536.2 million were spent in the care of HF patients (7.1% of the total healthcare budget). The main source of expenditure was hospitalization (39% of the total) whereas outpatient care represented 20% of the total expenditure. In the general population, outpatient care and hospitalization were the main expenses. In multivariate analysis, younger age, higher presence of co-morbidities, and a recent HF or all-cause hospitalization were independently associated with higher healthcare expenditure.In Catalonia, a large portion of the annual healthcare budget is devoted to HF patients. Unplanned hospitalization represents the main source of healthcare-related expenditure. The knowledge of how expenditure is distributed in a non-selected HF population might allow health providers to plan the distribution of resources in patients with HF.

To verify the usefulness of the minimum data set (MDS) for acute-care hospitals and emergency resources for the study of road traffic injuries and to describe the use of health resources in Catalonia (Spain).The study population consisted of patients treated in any kind of emergency service and patients admitted for acute hospitalization in Catalonia in 2013. A descriptive analysis was performed by age, gender, time and clinical variables.A total of 48,150 patients were treated in hospital emergency departments, 6,210 were attended in primary care, and 4,912 were admitted to hospital. There was a higher proportion of men (56.2%), mainly aged between 20 and 40 years. Men accounted for 54.9% of patients with minor injuries and 75.1% of those with severe injuries. Contusions are the most common injury (30.2%), followed by sprains (28.7%). Fractures mostly affected persons older than 64 years, internal injuries particularly affected men older than 64 years, and wounds mainly affected persons younger than 18 years and older than 64 years. In the adult population, the severity of the injuries increased with age, leading to longer length of stay and greater complexity. Hospital mortality was 0.2%. Fractures, internal injuries and wounds were more frequent in the group of very serious injuries, and sprains and contusions in the group of minor injuries.MDS records (acute hospitals and emergency resources) provide information that is complementary to other sources of information on traffic accidents, increasing the completeness of the data.