Background Reducing health inequalities on the basis of social factors has been a key driver in the development of Public Health policies. Health-related quality of life is a global indicator useful to assess health inequalities within a society. The objective of this study was to identify inequalities on health by analysing the interactive effects of gender, age, educational level, social class, body mass index and chronic diseases on health-related quality of life in a Spanish population sample. Methods We used data from the Spanish National Health Survey 2011–2012. Health-related quality of life was measured by the EQ-5D-5L instrument applying the Spanish value set. Probability of being in perfect health was ascertained by logistic regression models including gender, age, educational level, body mass index and social class and the corresponding terms of interaction. A two-part model combining logistic regression analysis and generalized linear models was applied to calculate the adjusted utility loss associated with chronic conditions (disutility values). Results The sample used for analysis contained 18,450 individuals. The mean age was 50 years, 51.3% were women, 55% were overweight or obese and 46.7% had low social status. The mean utility was 0.94 in men and 0.89 in women. Elderly women, obese people, those of low social class and those with chronic conditions had significant lower utility values. Within the regression analysis, interaction assessment revealed that the detrimental effect of obesity disappeared in higher social classes. Utility values for all chronic conditions considered were lower in women than in men and were on a gradient within social class, the lowest for individuals declaring stroke. The greatest decrease on health-related quality of life was determined by declaration of stroke (17.6%) or mental diseases (18.6%). Conclusions The interactive effects of gender, age, educational level, social class, body mass index and chronic diseases on health-related quality of life in the Spanish population revealed important inequalities in health. Social class acted as a modulator of the stigma associated with obesity. Chronic conditions producing loss of autonomy had the greatest impact on reduction of health-related quality of life. This is the first study using the Spanish EQ-5D-5L value set to estimate utilities. Electronic supplementary material The online version of this article (10.1186/s12955-019-1134-9) contains supplementary material, which is available to authorized users.
BackgroundThe Basque Colorectal Cancer Screening Programme began in 2009 and the implementation has been complete since 2013. Faecal immunological testing was used for screening in individuals between 50 and 69 years old. Colorectal Cancer in Basque country is characterized by unusual epidemiological features given that Colorectal Cancer incidence is similar to other European countries while adenoma prevalence is higher. The object of our study was to economically evaluate the programme via cost-effectiveness and budget impact analyses with microsimulation models.MethodsWe applied the Microsimulation Screening Analysis (MISCAN)-Colon model to predict trends in Colorectal Cancer incidence and mortality and to quantify the short- and long-term effects and costs of the Basque Colorectal Cancer Screening Programme. The model was calibrated to the Basque demographics in 2008 and age-specific Colorectal Cancer incidence data in the Basque Cancer Registry from 2005 to 2008 before the screening begun. The model was also calibrated to the high adenoma prevalence observed for the Basque population in a previously published study. The multi-cohort approach used in the model included all the cohorts in the programme during 30 years of implementation, with lifetime follow-up. Unit costs were obtained from the Basque Health Service and both cost-effectiveness analysis and budget impact analysis were carried out.ResultsThe goodness-of-fit of the model adaptation to observed programme data was evidence of validation. In the cost-effectiveness analysis, the savings from treatment were larger than the added costs due to screening. Thus, the Basque programme was dominant compared to no screening, as life expectancy increased by 29.3 days per person. The savings in the budget analysis appeared 10 years after the complete implementation of the programme. The average annual budget was €73.4 million from year 2023 onwards.ConclusionsThis economic evaluation showed a screening intervention with a major health gain that also produced net savings when a long follow-up was used to capture the late economic benefit. The number of colonoscopies required was high but remain within the capacity of the Basque Health Service. So far in Europe, no other population Colorectal Cancer screening programme has been evaluated by budget impact analysis.Electronic supplementary materialThe online version of this article (10.1186/s12885-018-4362-1) contains supplementary material, which is available to authorized users.
Background Dementia-related neuropsychiatric symptoms (NPS) are the main determinant of family stress and institutionalization of patients. This study aimed to identify inequalities by gender and socioeconomic status in the management of NPS in patients diagnosed with dementia. Methods An observational study was carried out to study all the cases of dementia in the corporate database of the Basque Health Service (29,864 patients). The prescription of antipsychotics and antidepressants and admission to a nursing home were used to establish the presence of NPS. The socioeconomic status of individuals was classified by a deprivation index. Logistic regressions were used to identify drivers for drug prescriptions and institutionalization. Results NPS are poorly recorded in the clinical databases (12%). Neuropsychiatric symptoms were severe enough in two thirds of patients with dementia to be treated with psychoactive medication. Institutionalization showed an increase from those who did not receive medication to those who had been prescribed antidepressants (OR: 1.546), antipsychotics (OR: 2.075) or both (OR: 2.741). The resulting inequalities were the increased prescription of antidepressant drugs in women and more nursing-home admissions for women who were the least socioeconomically deprived and men who were the most deprived. Conclusions In large clinical databases, psychoactive drugs prescriptions can be useful to underscore the considerable burden of dementia-related NPS. Specific tools are needed to monitor social and health care programs targeted to dementia-related NPS from a population perspective. Programs aimed at reducing the family burden of care of dementia patients at home become the key elements in reducing inequalities in these patients’ care. Socioeconomic status is the most important driver of inequality, and gender inequality may simply be hidden within the social environment. Integrated programs boosting the continuity of care are an objective for which compliance could be measured according to the NPS coding in the electronic health record.
Our results show the complexity and rapid progression of end-stage liver disease associated with HCV infection. The considerable loss of life expectancy associated with the development of decompensated cirrhosis in patients with chronic HCV infection in the absence of viral clearance through treatment is acutely evident.
Vaccines have measurable efficacies, obtained first from vaccine trials. However, vaccine efficacy is not a static measure upon licensing, and the long term population studies are very important to evaluate vaccine performance and impact. COVID-19 vaccines were developed in record time and although the extent of sterilizing immunity is still under evaluation, the currently licensed vaccines are extremely effective against severe disease, with vaccine efficacy significantly higher after the full immunization schedule. We investigate the impact of vaccines which have different efficacies after first dose and after the second dose administration schedule, eventually considering different efficacies against severe disease as opposed to overall infection. As a proof of concept, we model the vaccine performance of hospitalization reduction at the momentary scenario of the Basque Country, Spain, with population in a mixed vaccination setting, giving insights into the population coverage needed to achieve herd immunity in the current vaccination context.
Background: Neuropsychiatric symptoms (NPS) are the leading cause of the social burden of dementia but their role is underestimated. Objective: The objective of the study was to validate predictive models to separately identify psychotic and depressive symptoms in patients diagnosed with dementia using clinical databases representing the whole population to inform decision-makers. Methods: First, we searched the electronic health records of 4,003 patients with dementia to identify NPS. Second, machine learning (random forest) algorithms were applied to build separate predictive models for psychotic and depressive symptom clusters in the training set (N = 3,003). Third, calibration and discrimination were assessed in the test set (N = 1,000) to assess the performance of the models. Results: Neuropsychiatric symptoms were noted in the electronic health record of 58% of patients. The area under the receiver operating curve reached 0.80 for the psychotic cluster model and 0.74 for the depressive cluster model. The Kappa index and accuracy also showed better discrimination in the psychotic model. Calibration plots indicated that both types of model had less predictive accuracy when the probability of neuropsychiatric symptoms was <25%. The most important variables in the psychotic cluster model were use of risperidone, level of sedation, use of quetiapine and haloperidol and the number of antipsychotics prescribed. In the depressive cluster model, the most important variables were number of antidepressants prescribed, escitalopram use, level of sedation, and age. Conclusion: Given their relatively good performance, the predictive models can be used to estimate prevalence of NPS in population databases.
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