Comorbidity and household income as mediators of gender inequalities in dementia risk: a real-world data population study

BACKGROUND

Low household income (HI), comorbidities and female sex are associated with an increased risk of dementia. The aim of this study was to measure the mediating effect of comorbidity and HI on the excess risk due to gender in relation to the incidence and prevalence of dementia in the general population.

METHODS

A retrospective and observational study using real-world data analysed all people over 60 who were registered with the Basque Health Service in Gipuzkoa. The study measured HI level, the Charlson comorbidity index (CCI), age and sex. The prevalence and incidence of dementia were analysed using logistic regression and Poisson regression models, respectively, adjusted by HI, sex, comorbidity and age. We estimated the combined mediation effect of HI and comorbidity on the prevalence of dementia associated with gender.

RESULTS

Of the 221,777 individuals, 3.85% (8,549) had a diagnosis of dementia as of 31 December 2021. Classification by the CCI showed a gradient with 2.90% in CCI 0-1, 10.60% in CCI 2-3 and 18.01% in CCI > 3. Both low HI and gender were associated with a higher crude prevalence of dementia. However, in the CCI-adjusted model, women had an increased risk of dementia, while HI was no longer statistically significant. The incidence analysis produced similar results, although HI was not significant in any model. The CCI was significantly higher for men and for people with low HI. The mediation was statistically significant, and the CCI and HI explained 79% of the gender effect.

CONCLUSIONS

Comorbidity and low HI act as mediators in the increased risk of dementia associated with female sex. Given the difference in the prevalence of comorbidities by HI, individual interventions to control comorbidities could not only prevent dementia but also reduce inequalities, as the risk is greater in the most disadvantaged population.

Using Age-Specific Rates for Parametric Survival Function Estimation in Simulation Models

PURPOSE

To describe a procedure for incorporating parametric functions into individual-level simulation models to sample time to event when age-specific rates are available but not the individual data.

METHODS

Using age-specific event rates, regression analysis was used to parametrize parametric survival distributions (Weibull, Gompertz, log-normal, and log-logistic), select the best fit using the R2 statistic, and apply the corresponding formula to assign random times to events in simulation models. We used stroke rates in the Spanish population to illustrate our procedure.

RESULTS

The 3 selected survival functions (Gompertz, Weibull, and log-normal) had a good fit to the data up to 85 y of age. We selected Gompertz distribution as the best-fitting distribution due to its goodness of fit.

CONCLUSIONS

Our work provides a simple procedure for incorporating parametric risk functions into simulation models without individual-level data.

HIGHLIGHTS

We describe the procedure for sampling times to event for individual-level simulation models as a function of age from parametric survival functions when age-specific rates are available but not the individual dataWe used linear regression to estimate age-specific hazard functions, obtaining estimates of parameter uncertainty.Our approach allows incorporating parameter (second-order) uncertainty in individual-level simulation models needed for probabilistic sensitivity analysis in the absence of individual-level survival data.

Cost-Effectiveness Analysis of Vaccines for COVID-19 According to Sex, Comorbidity and Socioeconomic Status: A Population Study

BACKGROUND AND OBJECTIVE

Coronavirus disease 2019 (COVID-19) vaccines are extremely effective in preventing severe disease, but their real-world cost effectiveness is still an open question. We present an analysis of the cost-effectiveness and economic impact of the initial phase of the COVID-19 vaccination rollout in the Basque Country, Spain.

METHODS

To calculate costs and quality-adjusted life years for the entire population of the Basque Country, dynamic modelling and a real-world data analysis were combined. Data on COVID-19 infection outcomes (cases, hospitalisations, intensive care unit admissions and deaths) and population characteristics (age, sex, socioeconomic status and comorbidity) during the initial phase of the vaccination rollout, from January to June of 2021, were retrieved from the Basque Health Service database. The outcomes in the alternative scenario (without vaccination) were estimated with the dynamic model used to guide public health authority policies, from February to December 2020. Individual comorbidity-adjusted life expectancy and costs were estimated.

RESULTS

By averting severe disease-related outcomes, COVID-19 vaccination resulted in monetary savings of €26.44 million for the first semester of 2021. The incremental cost-effectiveness ratio was €707/quality-adjusted life year considering official vaccine prices and dominant real prices. While the analysis by comorbidity showed that vaccines were considerably more cost effective in individuals with pre-existing health conditions, this benefit was lower in the low socioeconomic status group.

CONCLUSIONS

The incremental cost-effectiveness ratio of the vaccination programme justified the policy of prioritising high-comorbidity patients. The initial phase of COVID-19 vaccination was dominant from the perspective of the healthcare payer.

Cost-utility analysis of the UPRIGHT intervention promoting resilience in adolescents

BACKGROUND

As mental health in adulthood is related to mental status during adolescence, school-based interventions have been proposed to improve resilience. The objective of this study was to build a simulation model representing the natural history of mental disorders in childhood, adolescence and youth to estimate the cost-effectiveness of the UPRIGHT school-based intervention in promoting resilience and mental health in adolescence.

METHODS

We built a discrete event simulation model fed with real-world data (cumulative incidence disaggregated into eight clusters) from the Basque Health Service database (609,381 individuals) to calculate utilities (quality-adjusted life years [QALYs]) and costs for the general population in two scenarios (base case and intervention). The model translated changes in the wellbeing of adolescents into different risks of mental illnesses for a time horizon of 30 years.

RESULTS

The number of cases of anxiety was estimated to fall by 5,125 or 9,592 and those of depression by 1,269 and 2,165 if the effect of the intervention lasted 2 or 5 years respectively. From a healthcare system perspective, the intervention was cost-effective for all cases considered with incremental cost-utility ratios always lower than €10,000/QALY and dominant for some subgroups. The intervention was always dominant when including indirect and non-medical costs (societal perspective).

CONCLUSIONS

Although the primary analysis of the trial did not did not detect significant differences, the UPRIGHT intervention promoting positive mental health was dominant in the economic evaluation from the societal perspective. Promoting resilience was more cost-effective in the most deprived group. Despite a lack of information about the spillover effect in some sectors, the economic evaluation framework developed principally for pharmacoeconomics can be applied to interventions to promote resilience in adolescents. As prevention of mental health disorders is even more necessary in the post-coronavirus disease-19 era, such evaluation is essential to assess whether investment in mental health promotion would be good value for money by avoiding costs for healthcare providers and other stakeholders.

Excess healthcare costs of mental disorders in children, adolescents and young adults in the Basque population registry adjusted for socioeconomic status and sex

BACKGROUND

Mental illnesses account for a considerable proportion of the global burden of disease. Economic evaluation of public policies and interventions aimed at mental health is crucial to inform decisions and improve the provision of healthcare services, but experts highlight that nowadays the cost implications of mental illness are not properly quantified. The objective was to measure the costs of excess use of all healthcare services by 1- to 30-year-olds in the Basque population as a function of whether or not they had a mental disorder diagnosis.

METHODS

A real-world data study was used to identify diagnoses of mental disorders and to measure resource use in the Basque Health Service Registry in 2018. Diagnoses were aggregated into eight diagnostic clusters: anxiety, attention deficit hyperactivity disorder, conduct disorders, mood disorders, substance use, psychosis and personality disorders, eating disorders, and self-harm. We calculated the costs incurred by each individual by multiplying the resource use by the unit costs. Annual costs for each cluster were compared with those for individuals with no diagnosed mental disorders through entropy balancing and two-part models which adjusted for socioeconomic status (SES).

RESULTS

Of the 609,381 individuals included, 96,671 (15.9%) had ≥ 1 mental disorder diagnosis. The annual cost per person was two-fold higher in the group diagnosed with mental disorders (€699.7) than that with no diagnoses (€274.6). For all clusters, annual excess costs associated with mental disorders were significant. The adjustment also evidenced a social gradient in healthcare costs, individuals with lower SES consuming more resources than those with medium and higher SES across all clusters. Nonetheless, the effect of being diagnosed with a mental disorder had a greater impact on the mean and excess costs than SES.

CONCLUSIONS

Results were consistent in showing that young people with mental disorders place a greater burden on healthcare services. Excess costs were higher for severe mental disorders like self-harm and psychoses, and lower SES individuals incurred, overall, more than twice the costs per person with no diagnoses. A socioeconomic gradient was notable, excess costs being higher in low SES individuals than those with a high-to-medium SES. Differences by sex were also statistically significant but their sizes were smaller than those related to SES.

Assessment of the Effectiveness, Socio-Economic Impact and Implementation of a Digital Solution for Patients with Advanced Chronic Diseases: The ADLIFE Study Protocol

Due to population ageing and medical advances, people with advanced chronic diseases (ACD) live longer. Such patients are even more likely to face either temporary or permanent reduced functional reserve, which typically further increases their healthcare resource use and the burden of care on their caregiver(s). Accordingly, these patients and their caregiver(s) may benefit from integrated supportive care provided via digitally supported interventions. This approach may either maintain or improve their quality of life, increase their independence, and optimize the healthcare resource use from early stages. ADLIFE is an EU-funded project, aiming to improve the quality of life of older people with ACD by providing integrated personalized care via a digitally enabled toolbox. Indeed, the ADLIFE toolbox is a digital solution which provides patients, caregivers, and health professionals with digitally enabled, integrated, and personalized care, supporting clinical decisions, and encouraging independence and self-management. Here we present the protocol of the ADLIFE study, which is designed to provide robust scientific evidence on the assessment of the effectiveness, socio-economic, implementation, and technology acceptance aspects of the ADLIFE intervention compared to the current standard of care (SoC) when applied in real-life settings of seven different pilot sites across six countries. A quasi-experimental trial following a multicenter, non-randomized, non-concurrent, unblinded, and controlled design will be implemented. Patients in the intervention group will receive the ADLIFE intervention, while patients in the control group will receive SoC. The assessment of the ADLIFE intervention will be conducted using a mixed-methods approach.

Descriptive and predictive analysis identify centenarians' characteristics from the Basque population

Background

Centenarians exhibit extreme longevity and have been postulated, by some researchers, as a model for healthy aging. The identification of the characteristics of centenarians might be useful to understand the process of human aging.

Methods

In this retrospective study, we took advantage of demographic, clinical, biological, and functional data of deceased individuals between 2014 and 2020 in Guipúzcoa (Basque Country, Spain) taken from the Basque Health Service electronic health records data lake. Fifty characteristics derived from demographic, clinical, pharmaceutical, biological, and functional data were studied in the descriptive analysis and compared through differences in means tests. Twenty-seven of them were used to build machine learning models in the predictive analysis and their relevance for classifying centenarians was assessed.

Results

Most centenarians were women and lived in nursing homes. Importantly, they developed fewer diseases, took fewer drugs, and required fewer medical attendances. They also showed better biological profiles, exhibiting lower levels of glucose, hemoglobin, glycosylated hemoglobin, and triglycerides in blood analysis compared with non-centenarians. In addition, machine learning analyses revealed the main characteristics of the profiles associated with centenarians' status as being women, having fewer consultations, having fewer diagnoses of neoplasms, and having lower levels of hemoglobin.

Conclusions

Our results revealed the main characteristics linked to centenarians in the Basque Country using Computational Biology programs. These results expand the knowledge on the characterization of the centenarian population and hence of human longevity.

Incidence of mental disorders in the general population aged 1-30 years disaggregated by gender and socioeconomic status

PURPOSE

The objective of this study was to estimate the incidence and age of onset of mental disorders diagnosed by gender and socioeconomic status (SES) in children, adolescents, and young adults up to 30 years of age in the whole population of the Basque Country (Spain).

METHODS

All mental health diagnoses documented in Basque Health Service records from 1 January 2003 to 31 December 2018, were classified into eight clusters: anxiety, attention deficit hyperactivity disorder (ADHD), conduct disorders, depression, psychosis/personality disorders, substance use, eating disorders, and self-harm. We calculated incidence and cumulative incidence for each cluster, disaggregated by gender, and socioeconomic status (SES). Poisson regression analyses were performed.

RESULTS

Overall, 9,486,853 person-years of observation were available for the 609,281 individuals included. ADHD and conduct disorders were diagnosed in the first decade, anxiety and depression disorders in the second and third decades, and psychosis/personality and substance use in the third. The cumulative incidence at 18 years of age for any type of disorder was 15.5%. The group with low SES had a statistically significantly higher incidence of all eight clusters. The incidence of ADHD, conduct disorders, depression, psychosis/personality disorders, and substance use was higher in males and that of anxiety, eating disorders and self-harm was higher in females.

CONCLUSIONS

The incidence of mental disorders is high among children, adolescents, and young adults in the Basque Country underlining the need for preventive interventions. Marked differences by gender and SES highlight mental health inequalities, especially for depression and psychosis in low SES males.

Budget impact analysis of the use of Souvenaid in patients with prodromal Alzheimer’s Disease in Spain

Introduction

The effectiveness, safety, and cost-effectiveness of the use of Souvenaid for Alzheimer’s disease (AD) have been previously evidenced. To complete the economic analysis, there is a need to assess whether society can afford it. The objective of this study was to carry out a budget impact analysis of the use of Souvenaid in Spain under the conditions of the LipiDidiet clinical trial from a societal perspective.

Methods

We built a population model that took into account all the cohorts of individuals with AD, their individual progression, and the potential impact of Souvenaid treatment on their trajectories. Patient progression data were obtained from mixed models. The target population was estimated based on the population forecast for 2020–2035 and the incidence of dementia. Individual progression to dementia measured by the Clinical Dementia Rating-Sum of Boxes was reproduced using mixed models. Besides the costs of treatment and diagnosis, direct costs of medical and non-medical care and indirect costs were included.

Results

The epidemiological indicators and the distribution of life expectancy by stages validated the model. From the third year (2022), the differences in the cost of dementia offset the incremental cost of diagnosis and treatment. The costs of dependency reached €500 million/year while those of the intervention were limited to €40 million.

Conclusions

Souvenaid, with modest effectiveness in delaying dementia associated with AD, achieved a positive economic balance between costs and savings. Its use in the treatment of prodromal AD would imply an initial cost that would be ongoing, but this would be offset by savings in the care system for dependency associated with dementia from the third year. These results were based on adopting a societal perspective taking into account the effect of treatment on the use of health, social, and family resources.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13195-022-01111-7.

Changes in Social and Clinical Determinants of COVID-19 Outcomes Achieved by the Vaccination Program: A Nationwide Cohort Study

BACKGROUND

The objective of this study was to assess changes in social and clinical determinants of COVID-19 outcomes associated with the first year of COVID-19 vaccination rollout in the Basque population.

METHODS

A retrospective study was performed using the complete database of the Basque Health Service (n = 2,343,858). We analyzed data on age, sex, socioeconomic status, the Charlson comorbidity index (CCI), hospitalization and intensive care unit (ICU) admission, and COVID-19 infection by Cox regression models and Kaplan-Meier curves.

RESULTS

Women had a higher hazard ratio (HR) of infection (1.1) and a much lower rate of hospitalization (0.7). With older age, the risk of infection fell, but the risks of hospitalization and ICU admission increased. The higher the CCI, the higher the risks of infection and hospitalization. The risk of infection was higher in high-income individuals in all periods (HR = 1.2-1.4) while their risk of hospitalization was lower in the post-vaccination period (HR = 0.451).

CONCLUSION

Despite the lifting of many control measures during the second half of 2021, restoring human mobility patterns, the situation could not be defined as syndemic, clinical determinants seeming to have more influence than social ones on COVID-19 outcomes, both before and after vaccination program implementation.

Estimation of the epidemiology of dementia and associated neuropsychiatric symptoms by applying machine learning to real-world data

INTRODUCTION

Incidence rates of dementia-related neuropsychiatric symptoms (NPS) are not known and this hampers the assessment of their population burden. The objective of this study was to obtain an approximate estimate of the population incidence and prevalence of both dementia and NPS.

METHODS

Given the dynamic nature of the population with dementia, a retrospective study was conducted within the database of the Basque Health Service (real-world data) at the beginning and end of 2019. Validated random forest models were used to identify separately depressive and psychotic clusters according to their presence in the electronic health records of all patients diagnosed with dementia.

RESULTS

Among the 631,949 individuals over 60 years registered, 28,563 were diagnosed with dementia, of whom 15,828 (55.4%) showed psychotic symptoms and 19,461 (68.1%) depressive symptoms. The incidence of dementia in 2019 was 6.8/1000 person-years. Most incident cases of depressive (72.3%) and psychotic (51.9%) NPS occurred in cases of incident dementia. The risk of depressive-type NPS grows with years since dementia diagnosis, living in a nursing home, and female sex, but falls with older age. In the psychotic cluster model, the effects of male sex, and older age are inverted, both increasing the probability of this type of symptoms.

CONCLUSIONS

The stigmatization factor conditions the social and attitudinal environment, delaying the diagnosis of dementia, preventing patients from receiving adequate care and exacerbating families' suffering. This study evidences the synergy between big data and real-world data for psychiatric epidemiological research.

Development and Validation of a Discrete Event Simulation Model to Evaluate the Cardiovascular Impact of Population Policies for Obesity

Introduction

Our aim was to describe the development and validation of an obesity model representing the cardiovascular risks associated with different body mass index (BMI) categories, through simulation, designed to evaluate the epidemiological and economic impact of population policies for obesity.

Methods

A discrete event simulation model was built in R considering the risk of cardiovascular events (heart failure, stroke, coronary heart disease, and diabetes) associated with BMI categories in the Spanish population. The main parameters included in the model were estimated from Spanish hospital discharge records and the Spanish Health Survey and allowed both first-order and second-order (probabilistic sensitivity analysis) uncertainty to be programmed into the model. The simulation yielded the incidence and prevalence of cardiovascular events as validation outputs. To illustrate the capacity of the model, we estimated the reduction in cardiovascular events and cost-utility (incremental cost/incremental quality-adjusted life-years [QALYs]) of a hypothetical intervention that fully eliminated the cardiovascular risks associated with obesity and overweight.

Results

The Validation Status of Health-Economic decision models (AdViSHE) tool was applied. Internal validation plots showed adequate goodness of fit for the Spanish population. External validation was achieved by comparing the simulated and real incidence by age group for stroke, acute myocardial infarction, and heart failure. The intervention reduced the population hazard ratios of stroke, acute myocardial infarction, and heart failure to 0.81, 0.74, and 0.78, respectively, and added 0.74 QALYs to the whole population.

Conclusions

This obesity simulation model evidenced good properties for estimating the long-term epidemiological and economic impact of policies to tackle obesity in Spain. The conceptual model could be implemented for other counties using country-specific input data.

Stratified cost-utility analysis of total hip arthroplasty in displaced femoral neck fracture

OBJECTIVE

To conduct a stratified cost-utility analysis of total versus partial hip arthroplasty as a function of clinical subtype.

METHOD

All cases of this type of intervention were analysed between 2010 and 2016 in the Basque Health Service, gathering data on clinical outcomes and resource use to calculate the cost and utility in quality-adjusted life years (QALYs) at individual level. The statistical analysis included applying the propensity score to balance the groups, and seemingly unrelated regression models to calculate the incremental cost-utility ratio and plot the cost-effectiveness plane. The interaction between age group and American Society of Anesthesiologists (ASA) risk class was assessed in the multivariate analysis.

RESULTS

The study identified 5867 patients diagnosed with femoral neck fracture, of whom 1307 and 4560 were treated with total and partial hip arthroplasty, respectively. In the cost-utility analysis based on the seemingly unrelated regression, total hip arthroplasty was found to have a higher cost and higher utility (2465€ and 0.42 QALYs). Considering a willingness-to-pay threshold of €22,000 per QALY, total hip arthroplasty was cost-effective in the under-80-year-old subgroup. Among patients above this age, hemiarthroplasty was cost-effective in ASA class I-II patients and dominant in ASA class III-IV patients.

CONCLUSIONS

Subgroup analysis supports current daily clinical practice in displaced femoral neck fractures, namely, using partial replacement in most patients and reserving total replacement for younger patients.

Estimation of the epidemiology of dementia and associated neuropsychiatric symptoms by applying machine learning to real-world data

INTRODUCTION

Incidence rates of dementia-related neuropsychiatric symptoms (NPS) are not known and this hampers the assessment of their population burden. The objective of this study was to obtain an approximate estimate of the population incidence and prevalence of both dementia and NPS.

METHODS

Given the dynamic nature of the population with dementia, a retrospective study was conducted within the database of the Basque Health Service (real-world data) at the beginning and end of 2019. Validated random forest models were used to identify separately depressive and psychotic clusters according to their presence in the electronic health records of all patients diagnosed with dementia.

RESULTS

Among the 631,949 individuals over 60 years registered, 28,563 were diagnosed with dementia, of whom 15,828 (55.4%) showed psychotic symptoms and 19,461 (68.1%) depressive symptoms. The incidence of dementia in 2019 was 6.8/1000 person-years. Most incident cases of depressive (72.3%) and psychotic (51.9%) NPS occurred in cases of incident dementia. The risk of depressive-type NPS grows with years since dementia diagnosis, living in a nursing home, and female sex, but falls with older age. In the psychotic cluster model, the effects of male sex, and older age are inverted, both increasing the probability of this type of symptoms.

CONCLUSIONS

The stigmatization factor conditions the social and attitudinal environment, delaying the diagnosis of dementia, preventing patients from receiving adequate care and exacerbating families' suffering. This study evidences the synergy between big data and real-world data for psychiatric epidemiological research.

Health care costs of breast, prostate, colorectal and lung cancer care by clinical stage and cost component

OBJECTIVE

To measure 3-year care costs of breast, prostate, colorectal and lung cancers disaggregated by site and clinical stage.

METHOD

A retrospective observational design was employed to investigate care costs of cases recorded in the Registry of the Basque Country between 2010 and 2015. Data gathered included TNM stage and demographic, clinical and resource use variables. Total costs per patient with stage IV disease were calculated by combining generalized linear models with parametric survival analysis. Unit costs were obtained from the analytical accounting system of the Basque Health Service.

RESULTS

The sample comprised 23,782 cancer cases (7801 colorectal, 5530 breast, 4802 prostate and 5649 lung cancer). The mean 3-year costs per patient with stage I to III disease were €11,323, €13,727, €8,651 and €12,023 for colorectal, breast, prostate and lung cancer, respectively. The most important cost components were surgery and chemotherapy. Total survival-adjusted costs until death for patients with stage IV disease (€27,568, €26,296, €16,151 and €15,931 for breast, colorectal, lung and prostate cancer, respectively) were higher than the 3-year costs for those with earlier-stage disease.

CONCLUSIONS

This study quantitatively shows the pattern of changes in the economic burden of cancer throughout its natural history and the great magnitude of this burden for the health system. The use of indicators based on real-world data from each regional health service would allow cancer care in each region to be tailored to local population needs.

Dynamic evaluation of the comparative effectiveness of an integrated program for heart failure care

RATIONALE, AIMS AND OBJECTIVES

An integrated care program for heart failure (HF) was developed in the Basque Country in 2013. The objective of this research was to evaluate its effectiveness through the number of hospital admissions in three integrated healthcare organizations (IHOs), taking into account the longitudinal nature of the disease and the intensity of the implementation.

METHODS

A retrospective observational study was carried out, based on data entered in administrative and clinical databases between 2014 and 2018 for a total population of 230 000. In addition to conventional statistical analyses, Andersen-Gill models for recurrent events were used, incorporating dynamic variables that allowed assessment of the intervention's intensity before each hospitalization.

RESULTS

A total of 6768 patients were analysed. Age (hazard ratio [HR] = 1.016; 95% confidence interval [CI] 1.011-1.022), the Charlson index (HR = 1.067, 95% CI 1.047-1.087), and the number of previous hospitalizations (HR = 1.632, 95% CI 1.557-1.712) were risk factors for readmission. Differences between IHOs were also statistically significant. Greater intervention intensity was associated with a lower hospitalization rate (HR = 0.995, 95% CI 0.990-1.000). As indicated by the interaction between intervention intensity and IHO, differences between IHOs disappeared when intensity rose. No inequities in hospitalization were found as a function of deprivation index or sex. Nonetheless, inequity in the implementation of the program by sex was clear, women with HF receiving less intense intervention than men with the same level of comorbidity and age.

CONCLUSIONS

The extent of program implementation measured by intervention intensity is a main driver of the effectiveness of an educational and monitoring program for HF. The evaluation of HF program effectiveness on readmissions must take into account the entire natural history of the disease. Implementation intensity explains differences between IHOs.

Economic evaluation of supplementing the diet with Souvenaid in patients with prodromal Alzheimer's disease

Background

The LipiDiDiet trial showed that Souvenaid, a medical food, might delay progression to dementia in prodromal Alzheimer’s disease (AD). The objective of this study was to assess the cost-utility of Souvenaid compared to placebo in patients with prodromal AD under the conditions applied in that trial.

Methods

A discrete event simulation model was developed based on the LipiDiDiet trial and a literature review to assess the cost-utility of Souvenaid from a societal perspective considering direct and indirect costs. For both intervention and control groups, patient trajectories in terms of functional decline on the Clinical Dementia Rating Sum of Boxes (CDR-SB) scale in LipiDiDiet were reproduced statistically with mixed models by assigning time until events to simulated patients. From the societal perspective, four scenarios were analysed by combining different options for treatment duration and diagnostic test cost. Univariate sensitivity analysis assessed parameter uncertainties.

Results

Validation results at year 2 of disease progression fit with CDR-SB progression in LipiDiDiet. The incremental cost-utility ratio (ICUR) in the baseline case was €22,743/quality-adjusted life year (QALY). All scenarios rendered an ICUR lower than €25,000/QALY (the societal threshold). Moreover, the treatment option was cost-saving and increased health benefits when diagnostic costs were not considered and treatment was only administered during the prodromal stage.

Conclusions

Treating prodromal AD with Souvenaid is a cost-effective intervention in all scenarios analysed. The LipiDiDiet trial showed a modest improvement in disease course but as the social costs of AD are very high, the intervention was efficient. Assessing small benefits at specific stages of AD is relevant because it is reasonable to expect that no effective, safe and affordable disease-modifying therapies will become available in the short to medium term.

Impact of an organised population screening programme for colorectal cancer: Measurement after first and second rounds

OBJECTIVE

The first and second rounds of the Basque programme for organised colorectal cancer screening were implemented between 2009 and 2014. Our objective was to measure the changes in incidence, tumour, node, metastasis staging distribution and tumour, node, metastasis-adjusted survival of patients with colorectal cancer from 2003 to 2014.

METHOD

Colorectal cancer cases with screening (patients <70 years old) and without screening (patients ≥70 years old) were compared during three four-year periods: 2003-2006, 2007-2010 and 2011-2014 (fully implemented phase). Cox regression, five-year relative survival and cancer probability of death were calculated for each four-year period, age group and tumour, node, metastasis stage. Adjusted incidence rates were analysed by joinpoint regression.

RESULTS

In an analysis of 23,301 cases of colorectal cancer, the incidence in patients younger than 70 years in 2013 showed a 17% annual decrease. The survival hazard ratios for stages I, II and III for 2003-2006 and 2007-2010 were compared to those for 2011-2014. From the first to the third period, diagnosis in the early stages (I and II) rose from 45.1% to 50.9% in the younger patient group and remained stable in the older group (49.6% and 49.4%). Additionally, the five-year relative survival rate increased significantly from 0.67 to 0.82 in those patients younger than 70 years, whereas in patients 70 years or older the rate did not change significantly (0.61 and 0.65).

CONCLUSION

The screening reduced incidence and improved survival by anticipating the diagnosis and by reducing mortality for each tumour, node, metastasis stage in the target population. The effect on survival could also be due to lead-time bias.

Validation of Random Forest Machine Learning Models to Predict Dementia-Related Neuropsychiatric Symptoms in Real-World Data

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.

Harnessing Deep-Hole Drilling to Fabricate Air-Structured Polymer Optical Fibres

The performance of a precisely controlled drilling technique is critical in the fabrication process of microstructured polymer optical fibres. For the creation of a holey preform, adequate drilling bits with large length-to-diameter ratios provide the ability of machining preforms with complex structures and large lengths in a relatively short time. In this work, we analysed different drilling bits and techniques that can be employed for the creation of such preforms, and key parameters characterising the quality of the drilled holes, such as surface rugosity, diameter deviation, coaxiality and cylindricity were measured. For this purpose, based on theoretical simulations, four rings of air holes arranged in a hexagonal pattern were drilled in the preforms with different drill bits, and the experimental results for the above mentioned parameters have been presented. Additionally, optical power distribution of the fabricated microstructured polymer optical fibres was theoretically calculated and experimentally measured.

Economic Evaluation of an Integrated Health and Social Care Program for Heart Failure Through 2 Different Modeling Techniques

Introduction

An integrated health and social care program for patients with heart failure (HF) was implemented at the Friuli-Venezia Giulia deployment site as part of the SmartCare European project. The objective of this study was to validate 2 different decision modeling techniques used to perform the economic evaluation.

Methods

Data were collected during the SmartCare project which enrolled 108 patients with HF and followed for more than 6 months. The techniques used were Markov and discrete event simulation models. In both cases, a cost-effectiveness analysis and a budget impact analysis were carried out. The former was used to assign priority to the intervention and the latter to assess its sustainability. Analyses were conducted from the perspective of the Regional Health Authority.

Results

Results were similar with both types of model. Cost-effectiveness analysis found no significant differences in quality of life, but the intervention generated significant cost savings, becoming the dominant option. Data extrapolation showed no benefits in terms of mortality or hospital admissions, but budget impact analysis also predicted annual savings, as a significant number of in-hospital days were avoided. In budget analysis, both models predicted early, increasing and cumulative annual savings.

Discussion

The integrated program was dominant as it provided better outcomes and lower total costs, and thus, decision-makers should prioritize it. Besides, the work demonstrates the capacity of decision modeling to become a complementary tool in managing integrated health and social care models.

[The impact of patient identification on an integrated program of palliative care in Basque Country]

Objetivo

Evaluar el proceso y el impacto económico de un programa integrado de cuidados paliativos.

Diseño

Estudio transversal comparativo.

Emplazamiento

Organizaciones Sanitarias Integradas Alto Deba y Goierri Alto-Urola, País Vasco.

Participantes

Pacientes fallecidos (oncológicos y no oncológicos) en 2012 (grupo control) y 2015 (grupo intervención) susceptibles de necesitar cuidados paliativos según la estimación mínima de McNamara.

Intervenciones

Identificación de pacientes con el código de cuidados paliativos en atención primaria, uso de rutas asistenciales conjuntas en atención primaria y hospitalaria e impartición de cursos formativos.

Mediciones principales

Cambio en el perfil de uso de recursos del paciente durante sus últimos 3 meses de vida. Se utilizó el genetic matching para evitar sesgos. Mediante análisis univariante se compararon los grupos y mediante regresiones logísticas y modelos lineales generalizados se analizaron las relaciones entre variables.

Resultados

Se identificaron 1.023 pacientes en 2012 y 1.142 en 2015. En 2015 aumentó al doble la probabilidad de ser identificado como paliativo en pacientes oncológicos (19-33%) y no oncológicos (7-16%). La prescripción de opiáceos subió (25-68%) y el fallecimiento en hospital se mantuvo estable. Los contactos por paciente con atención primaria y hospitalización a domicilio aumentaron, mientras que las hospitalizaciones tradicionales disminuyeron. El coste por paciente aumentó un 26%.

Conclusiones

El modelo integrado incrementó la identificación de la población diana. La relación entre variables mostró que la identificación repercutió positivamente en la prescripción de opiáceos, fallecimiento fuera del hospital y extensión a enfermedades no oncológicas. Aunque también disminuyeron los ingresos, el coste aumentó debido al uso de hospitalización a domicilio.

Incorporating Budget Impact Analysis in the Implementation of Complex Interventions: A Case of an Integrated Intervention for Multimorbid Patients within the CareWell Study

OBJECTIVES

To develop a framework for the management of complex health care interventions within the Deming continuous improvement cycle and to test the framework in the case of an integrated intervention for multimorbid patients in the Basque Country within the CareWell project.

METHODS

Statistical analysis alone, although necessary, may not always represent the practical significance of the intervention. Thus, to ascertain the true economic impact of the intervention, the statistical results can be integrated into the budget impact analysis. The intervention of the case study consisted of a comprehensive approach that integrated new provider roles and new technological infrastructure for multimorbid patients, with the aim of reducing patient decompensations by 10% over 5 years. The study period was 2012 to 2020.

RESULTS

Given the aging of the general population, the conventional scenario predicts an increase of 21% in the health care budget for care of multimorbid patients during the study period. With a successful intervention, this figure should drop to 18%. The statistical analysis, however, showed no significant differences in costs either in primary care or in hospital care between 2012 and 2014. The real costs in 2014 were by far closer to those in the conventional scenario than to the reductions expected in the objective scenario. The present implementation should be reappraised, because the present expenditure did not move closer to the objective budget.

CONCLUSIONS

This work demonstrates the capacity of budget impact analysis to enhance the implementation of complex interventions. Its integration in the context of the continuous improvement cycle is transferable to other contexts in which implementation depth and time are important.

Socioeconomic position and type 2 diabetes mellitus in Europe 1999-2009: a panorama of inequalities

The aim of the present review is to synthesis findings from studies on the relationship between socioeconomic position (SEP) and incidence, prevalence and mortality of type 2 diabetes mellitus (T2DM) in Europe between the years 1999 and 2009. A systematic search was carried out in the National Library of Medicine's PubMed database. The search was limited to articles published between January 1999 and December 2009, in English or Spanish. Additional requirements for inclusion were: (i) presentation of empirical results directly related with SEP and the prevalence, incidence or mortality of diabetes, (ii) dealing with T2DM, (iii) carried out in Europe, and (iv) mainly focused only on diabetes. Of the 19 articles found, twelve studied the relationship between SEP and the prevalence of T2DM, two dealt with diabetes incidence, three with mortality and two studied both inequalities in mortality and prevalence. People with more deprived SEP have greater incidence, more prevalence and higher mortality due to T2DM, although the magnitude and significance of the associations varied from one study to another. Part of these inequalities is explained by SEP differences in the prevalence of the established T2DM risk factors. SEP inequalities in T2DM tended to be greater in women than in men. There is consistent evidence that SEP inequalities in T2DM incidence, prevalence and mortality are present in Europe, especially among women. Improving accessibility of physical activity in terms of both price and availability, access to healthy food, and access to health services, will be key to achieving a reduction of SEP related diabetes inequalities in Europe.

Socio-economic inequalities in the prevalence of Type 2 diabetes, cardiovascular risk factors and chronic diabetic complications in the Basque Country, Spain

AIMS

To establish the relationship between socio-economic status and the prevalence of known Type 2 diabetes, cardiovascular risk factors and chronic diabetic complications.

METHODS

In 2000, a cross-sectional survey was conducted among 61 general practitioners (GPs) who studied 65 651 people older than 24 years. Of those, 2985 known Type 2 diabetic patients were registered. The main outcome measures were: diabetes prevalence, major cardiovascular risk factors, chronic diabetic complications and primary care services utilization in Type 2 diabetic patients. Socio-economic status was based on area-based socio-economic measures.

RESULTS

The prevalence of known Type 2 diabetes was higher in patients of lower socio-economic status (OR: 2.17, 95% CI: 1.77-2.28), especially among women (OR: 2.28, 95% CI: 1.91-2.73). In Type 2 diabetes patients, obesity, sedentary lifestyle, and abnormal levels of low-density lipoprotein (LDL) cholesterol and HbA(1c) were more prevalent among those from lower socio-economic status. Macroangiopathy was inversely associated with socio-economic status after adjustment for clinical and demographic variables. Patients of lower socio-economic status more frequently visited primary care services than those of higher status.

CONCLUSIONS

This study shows an association between deprivation and Type 2 diabetes prevalence, cardiovascular risk factors and chronic diabetic complications in Type 2 diabetes patients. Despite a greater use of health services by less wealthy patients, they showed worse glycaemic control and more chronic complications. Besides clinical variables, socio-economic status and environmental information need to be considered in the assessment of risk profile of diabetic patients by health professionals and by health service planners.

Human papillomavirus and cervical intraepithelial neoplasia grade III/carcinoma in situ: a case-control study in Spain and Colombia

A case-control study of 525 cases of cervical intraepithelial neoplasia grade III (CIN III) and 512 controls was conducted in Spain and Colombia between 1985 and 1988 to assess the role of human papillomavirus (HPV) in the etiology of CIN III. HPV DNA in cytological scrapes from the cervix was assessed by Virapap and by polymerase chain reaction (PCR) based on the L1 consensus primers. A subsample of 268 specimens was also tested for HPV DNA using Southern hybridization. In Spain, the PCR-based prevalences of HPV DNA were 70.7% among cases and 4.7% among controls. Odds ratio (OR) and 95% confidence interval (numbers in parentheses) for HPV DNA were 56.9 (24.8-130.6). In Columbia HPV DNA was detected by PCR in 63.2% of the cases and in 10.5% of the controls. The OR was 15.5 (8.2-29.4). The estimated fractions of CIN III attributable to HPV were 72.4% in Spain and 60.3% in Colombia. HPV 16 was the predominant viral type and showed the strongest association with CIN III; in Spain the OR was 295.5 (44.8-1946.4) and in Colombia the OR was 27.1 (10.6-69.5). HPV DNA of unknown type was frequent in HPV-positive cases (18.3% in Spain and 38.0% in Colombia) and controls (66.7% in Spain and 47.4% in Colombia). The comparison of results from Virapap and PCR indicated that PCR is the method of choice for epidemiological studies. These data strongly support the hypothesis of the viral origin of CIN III, the common etiology of CIN III and invasive cervical cancer, and the causal nature of the association between HPV and CIN III.