Cost-Effectiveness of Whole-Genome vs Whole-Exome Sequencing Among Children With Suspected Genetic Disorders.

Importance: The diagnosis of rare diseases and other genetic conditions can be daunting due to vague or poorly defined clinical features that are not recognized even by experienced clinicians. Next-generation sequencing technologies, such as whole-genome sequencing (WGS) and whole-exome sequencing (WES), have greatly enhanced the diagnosis of genetic diseases by expanding the ability to sequence a large part of the genome, rendering a cost-effectiveness comparison between them necessary. Objective: To assess the cost-effectiveness of WGS compared with WES and conventional testing in children with suspected genetic disorders. Design, Setting, and Participants: In this economic evaluation, a bayesian Markov model was implemented from January 1 to June 30, 2023. The model was developed using data from a cohort of 870 pediatric patients with suspected genetic disorders who were enrolled and underwent testing in the Ospedale Pediatrico Bambino Gesù, Rome, Italy, from January 1, 2015, to December 31, 2022. The robustness of the model was assessed through probabilistic sensitivity analysis and value of information analysis. Main Outcomes and Measures: Overall costs, number of definitive diagnoses, and incremental cost-effectiveness ratios per diagnosis were measured. The cost-effectiveness analyses involved 4 comparisons: first-tier WGS with standard of care; first-tier WGS with first-tier WES; first-tier WGS with second-tier WES; and first-tier WGS with second-tier WGS. Results: The ages of the 870 participants ranged from 0 to 18 years (539 [62%] girls). The results of the analysis suggested that adopting WGS as a first-tier strategy would be cost-effective compared with all other explored options. For all threshold levels above €29 800 (US $32 408) per diagnosis that were tested up to €50 000 (US $54 375) per diagnosis, first-line WGS vs second-line WES strategy (ie, 54.6%) had the highest probability of being cost-effective, followed by first-line vs second-line WGS (ie, 54.3%), first-line WGS vs the standard of care alternative (ie, 53.2%), and first-line WGS vs first-line WES (ie, 51.1%). Based on sensitivity analyses, these estimates remained robust to assumptions and parameter uncertainty. Conclusions and Relevance: The findings of this economic evaluation encourage the development of policy changes at various levels (ie, macro, meso, and micro) of international health systems to ensure an efficient adoption of WGS in clinical practice and its equitable access.

Bayesian cost-effectiveness analysis of Whole genome sequencing versus Whole exome sequencing in a pediatric population with suspected genetic disorders.

Genetic diseases are medical conditions caused by sequence or structural changes in an individual's genome. Whole exome sequencing (WES) and whole genome sequencing (WGS) are increasingly used for diagnosing suspected genetic conditions in children to reduce the diagnostic delay and accelerating the implementation of appropriate treatments. While more information is becoming available on clinical efficacy and economic sustainability of WES, the broad implementation of WGS is still hindered by higher complexity and economic issues. The aim of this study is to estimate the cost-effectiveness of WGS versus WES and standard testing for pediatric patients with suspected genetic disorders. A Bayesian decision tree model was set up. Model parameters were retrieved both from hospital administrative datasets and scientific literature. The analysis considered a lifetime time frame and adopted the perspective of the Italian National Health Service (NHS). Bayesian inference was performed using the Markov Chain Monte Carlo simulation method. Uncertainty was explored through a probabilistic sensitivity analysis (PSA) and a value of information analysis (VOI). The present analysis showed that implementing first-line WGS would be a cost-effective strategy, against the majority of the other tested alternatives at a threshold of €30,000-50,000, for diagnosing outpatient pediatric patients with suspected genetic disorders. According to the sensitivity analyses, the findings were robust to most assumption and parameter uncertainty. Lessons learnt from this modeling study reinforces the adoption of first-line WGS, as a cost-effective strategy, depending on actual difficulties for the NHS to properly allocate limited resources.

Mobility restrictions and alcohol use during lockdown: "A still and dry pandemic for the many"?

Unexpected mobility disruptions during lockdown during the first wave of COVID-19 became 'tipping points' with the potential to alter pre-pandemic routines sensitive to socialisation. This paper investigates the impact of lockdown exposure on alcohol consumption. We document two findings using information from the Google Mobility Report and longitudinal data from the Understanding Society survey (UKHLS) in the United Kingdom. First, we find a sharp reduction in both actual mobility and alcohol use (consistent with a "still and dry pandemic for the many" hypothesis). However, we document an increase in alcohol use among heavy drinkers, implying a split behavioural response to COVID-19 mobility restrictions based on alcohol use prior to the pandemic. Second, using the predictions of the prevalence-response elasticity theory, we find that the pandemic's reduction in social contacts is responsible for a 2.8 percentage point reduction in drinking among men.

The social value of a SARS-CoV-2 vaccine: Willingness to pay estimates from four western countries.

SARS-CoV-2 vaccines give rise to positive externalities on population health, society and the economy in addition to protecting the health of vaccinated individuals. Hence, the social value of such a vaccine exceeds its market value. This paper estimates the willingness to pay (WTP) for a hypothetical SARS-CoV-2 vaccine (or shadow prices), in four countries, namely the United States (US), the United Kingdom, Spain and Italy during the first wave of the pandemic when COVID-19 vaccines were in development but not yet approved. WTP estimates are elicited using a payment card method to avoid "yea saying" biases, and we study the effect of protest responses, sample selection bias, as well as the influence of trust in government and risk exposure when estimating the WTP. Our estimates suggest evidence of an average value of a hypothetical vaccine of 100-200 US dollars once adjusted for purchasing power parity. Estimates are robust to a number of checks.

Too Healthy to Fall Sick? Longevity Expectations and Protective Health Behaviours during the First Wave of COVID-19.

Longevity expectations (LE) are subjective assessments of future health status that can influence a number of individual health protective decisions. This is especially true during a pandemic such as COVID-19, as the risk of ill health depends more than ever on such protective decisions. This paper examines the causal effect of LE on some protective health behaviors and a number of decisions regarding forgoing health care using individual differences in LE. We use data from the Survey of Health Ageing and Retirement in Europe, and we draw on an instrumental variable strategy exploiting individual level information on parental age at death. Consistent with the too healthy to be sick hypothesis, we find that individuals, exhibiting higher expected longevity, are more likely to engage in protective behaviours, and are less likely to forgo medical treatment. We estimate that a one standard deviation increase in LE increases the probability to comply always with social distancing by 0.6%, to meet people less often by 0.4% and decreases the probability to forgo any medical treatment by 0.6%. Our estimates vary depending on supply side restrictions influencing the availability of health care, as well as individual characteristics such as their gender and the presence of pre-existing health conditions.

Operations management solutions to improve ED patient flows: evidence from the Italian NHS.

BACKGROUND: Overcrowding occurs when the identified need for emergency services outweighs the available resources in the emergency department (ED). Literature shows that ED overcrowding impacts the overall quality of the entire hospital production system, as confirmed by the recent COVID-19 pandemic. This study aims to identify the most relevant variables that cause ED overcrowding using the input-process-output model with the aim of providing managers and policy makers with useful hints for how to effectively redesign ED operations. METHODS: A mixed-method approach is used, blending qualitative inquiry with quantitative investigation in order to: i) identifying and operationalizing the main components of the model that can be addressed by hospital operation management teams and ii) testing and measuring how these components can influence ED LOS. RESULTS: With a dashboard of indicators developed following the input-process-output model, the analysis identifies the most significant variables that have an impact on ED overcrowding: the type (age and complexity) and volume of patients (input), the actual ED structural capacity (in terms of both people and technology) and the ED physician-to-nurse ratio (process), and the hospital discharging process (output). CONCLUSIONS: The present paper represents an original contribution regarding two different aspects. First, this study combines different research methodologies with the aim of capturing relevant information that by relying on just one research method, may otherwise be missed. Second, this study adopts a hospitalwide approach, adding to our understanding of ED overcrowding, which has thus far focused mainly on single aspects of ED operations.

Use of instrumental variables in electronic health record-driven models.

Precision medicine presents various methodological challenges whose assessment requires the consideration of multiple factors. In particular, the data multitude in the Electronic Health Records poses interoperability issues and requires novel inference strategies. A problem, though apparently a paradox, is that highly specific treatments and a variety of outcomes may hardly match with consistent observations (i.e., large samples). Why is it the case? Owing to the heterogeneity of Electronic Health Records, models for the evaluation of treatment effects need to be selected, and in some cases, the use of instrumental variables might be necessary. We studied the recently defined person-centered treatment effects in cancer and C-section contexts from Electronic Health Record sources and identified as an instrument the distance of patients from hospitals. We present first the rationale for using such instrument and then its model implementation. While for cancer patients consideration of distance turns out to be a penalty, implying a negative effect on the probability of receiving surgery, a positive effect is instead found in C-section due to higher propensity of scheduling delivery. Overall, the estimated person-centered treatment effects reveal a high degree of heterogeneity, whose interpretation remains context-dependent. With regard to the use of instruments in light of our two case studies, our suggestion is that this process requires ad hoc variable selection for both covariates and instruments and additional testing to ensure validity.

Predictive Assessment of Cancer Center Catchment Area from Electronic Health Records.

Healthcare facilities (HF) may identify catchment areas (CA) by selecting criteria that depend on various factors. These refer to hospital activities, geographical definition, patient covariates, and more. The analyses that were traditionally pursued have a limiting factor in the consideration of only static conditions. Instead, some of the CA determinants involve influences occurring at both temporal and spatial scales. The study of CA in the cancer context means choosing between HF, usually divided into general hospitals versus oncological centers (OCs). In the CA context, electronic health records (EHRs) promise to be a valuable source of information, one driving the next-generation patient-driven clinical decision support systems. Among the challenges, digital health requires the re-definition of a role of stochastic modeling to deal with emerging complexities from data heterogeneity. To model CA with cancer EHR, we have chosen a computational framework centered on a logistic model, as a reference, and on a multivariate statistical approach. We also provided a battery of tests for CA assessment. Our results indicate that a more refined CA model's structure yields superior discrimination power between health facilities. The increased significance was also visualized by comparative evaluations with ad hoc geo-localized maps. Notably, a cancer-specific spatial effect can be noticed, especially for breast cancer and through OCs. To mitigate the data distributional influences, bootstrap analysis was performed, and gains in some cancer-specific and spatially concentrated regions were obtained. Finally, when the temporal dynamics are assessed along a 3-year timeframe, negligible differential effects appear between predicted probabilities observed between standard critical values and bootstrapped values. In conclusion, for interpreting CA in terms of both spatial and temporal dynamics, sophisticated models are required. The one here proposed suggests that bootstrap can improve test accuracy. We recommend that evidences from stochastic modeling are merged with visual analytics, as this combination may be exploited by policy-makers in support to quantitative CA assessment.

The Economic Impact of Smoke-Free Policies on Restaurants, Cafés, and Bars: Panel Data Estimates From European Countries.

In this paper, we investigate the extent to which the economic outcomes of restaurants, bars, and cafés have been affected by the introduction of anti-smoking regulations in Europe. We use an unexploited panel database to collect a comprehensive set of information on financial indicators regarding the balance sheets of private and public companies in various economic sectors. The results show that smoke-free policies did not significantly affect the firms' economic performance, irrespective of the balance sheet indicators analyzed. Moreover, the results are robust to various econometric specifications and suggest that the recent enforcement of anti-smoking legislation in Europe has improved public health without a corresponding negative impact on revenues and employment in the hospitality industry.

Investigating the poverty-obesity paradox in Europe.

This paper investigates the effect of income- and wealth-based poverty on the probability of being obese for the elderly in Europe by analysing data drawn from the Survey of Health, Ageing and Retirement (SHARE) and the English Longitudinal Study of Ageing (ELSA). We use early-life economic conditions and regional circumstances as instruments for poverty later in life to account for endogeneity issues. After controlling for a large set of covariates at the individual, household, regional and country level, the results show that poverty significantly increases the probability of being obese and the Body Mass Index (BMI), for men and women. The results show that, accounting for endogeneity with a bivariate probit model, poor individuals are from 10 to 20% points more likely to be obese than non-poor individuals. The effect on BMI ranges from 0.295 points (2.39 kg) to 0.395 points (2.75 kg). These results are robust to a series of checks and suggest that anti-poverty interventions might have positive side effects in terms of reducing food-related health inequalities.

Immigrant mothers and access to prenatal care: evidence from a regional population study in Italy.

OBJECTIVES: We addressed the question of whether use of adequate prenatal care differs between foreign-born and Italian mothers and estimated the extent to which unobservable characteristics bias results. SETTING: This study is on primary care and especially on adequate access to prenatal healthcare services by immigrant mothers. PARTICIPANTS: Approximately 37,000 mothers of both Italian and foreign nationality were studied. Data were obtained from the Standard Certificate of Live Birth between 2005 and 2010 in Umbria. RESULTS: Estimates from the bivariate probit model indicate that immigrant mothers are three times more likely to make fewer than four prenatal visits (OR=3.35) and 1.66 times more likely to make a late first visit (OR=1.66). The effect is found to be strongest for Asian women. CONCLUSIONS: Standard probit models lead to underestimation of the probability of inadequate use of prenatal care services by immigrant women, whereas bivariate probit models, which allow us to consider immigrant status as an endogenous variable, estimated ORs to be three times larger than those obtained with univariate models.

The effect of smoking habit changes on body weight: Evidence from the UK.

This paper evaluates the causal relationship between smoking and body weight through two waves (2004-2006) of the British Household Panel Survey. We model the effect of changes in smoking habits, such as quitting or reducing, and account for the heterogeneous responses of individuals located at different points of the body mass distribution by quantile regression. We test our results by means of a large set of control groups and investigate their robustness by using the changes-in-changes estimator and accounting for different thresholds to define smoking reductions. Our results reveal the positive effect of quitting smoking on weight changes, which is also found to increase in the highest quantiles, whereas the decision to reduce smoking does not affect body weight.

Immigration policy and birth weight: Positive externalities in Italian law.

A decade ago, the political party of the Italian center-right voted a law restricting immigration. The law became effective in early 2005, when the Italian parliament approved the decree for its application, but one of its articles, granting amnesty for illegal immigrant workers, became immediately effective in July 2002. As a result, 650,000 immigrants were granted the status of foreign nationals in Italy. In this paper, we examine whether the increase in the prevalence of "regular immigrants" has led to an improvement in health outcomes of babies born to migrant women, measured in terms of birth weight. Two hitherto unexploited birth sample surveys published by Italian Institute of Statistics were used for this study. Our estimates show that regularized immigration reduced the probability of low birth weight.

Estimating the Smoking Ban Effects on Smoking Prevalence, Quitting and Cigarette Consumption in a Population Study of Apprentices in Italy.

OBJECTIVES: We evaluated the effects of the Italian 2005 smoking ban in public places on the prevalence of smoking, quitting and cigarette consumption of young workers. DATA AND METHODS: The dataset was obtained from non-computerized registers of medical examinations for a population of workers with apprenticeship contracts residing in the province of Viterbo, Italy, in the period 1996-2007. To estimate the effects of the ban, a segmented regression approach was used, exploiting the discontinuity introduced by the application of the law on apprentices' smoking behavior. RESULTS: It is estimated that the Italian smoking ban generally had no effect on smoking prevalence, quitting ratio, or cigarette consumption of apprentices. However, when the estimates were applied to subpopulations, significant effects were found: -1% in smoking prevalence, +2% in quitting, and -3% in smoking intensity of apprentices with at least a diploma.

[Knowledge about sexual health in Italian adolescents girls and women: the need for intergenerational communication]. / Conoscenze sulla salute sessuale di un gruppo di ragazze adolescenti e donne adulte in Italia: il bisogno di comunicazione tra generazioni.

The aim of this study, performed between September to November 2010, was to provide insight into Italian girls' and women's knowledge of sexual health and sexuality, in particular regarding the physiology of human reproduction, contraception, sexuality, cervical cancer screening and abortion. The data used were obtained through face-to-face interviews with two groups of women, performed by a trained interviewer using a structured multiple-choice questionnaire. The first group was composed of young women aged 17 to 20 years, randomly selected from five high-school institutes in the inner-city area of Perugia (Italy), while the second group was made up of women aged 30 to 43 years, recruited amongst women undergoing postpartum checks at a regional hospital. The number of correct answers for each group of questions and the total number of correct answers in the questionnaire were calculated. A Poisson regression model was used to identify the main determinants of answering correctly. Adult women gave a higher rate of correct answers for each topic, except for those related to abortion, contraception, and HPV. Characteristics of adult women associated with a better knowledge about sexuality were: discussing about sexuality with friends or partner, being Italy-born and having an open and relaxed attitude toward sex. For younger women, better knowledge was associated with being Italy-born, having attended affectivity education courses and having an open and relaxed attitude towards sex. Results suggest that no sex education or information source by itself is effective but what is needed is a combination of various information sources, both formal and informal, including parent-adolescent communication.

Socio-demographic determinants and access to prenatal care in Italy.

BACKGROUND: Many governments have made commitments to examine inequalities in healthcare access based on studies assessing the association between several socio-demographic factors and late initiation or fewer prenatal examinations. This study addressed the question of whether socio-demographic determinants were significant in explaining differences in prenatal care in one administrative region of Italy, Umbria. METHODS: Data were obtained from the administrative source of the regional Standard Certificate of Live Births between 2005 and 2010, and were merged with Census data to include a socio-economic deprivation index. Standard and multilevel logistic regression models were used to analyze the magnitude of various individual-level maternal characteristics and socio-demographic indicators, such as nationality, employment status, education with respect to late access to the first examination, and low number of medical visits. RESULTS: The study involved approximately 37,000 women. The heterogeneous effects of socio-demographic variables were documented on the prenatal care indicators analyzed. A multivariate model showed that women born outside Italy had a higher probability of making their first visit later than the 12th week of pregnancy and low numbers of prenatal medical visits; the estimated odds ratio for the analyzed indicators range from 2.25 to 3.05. Inadequate prenatal healthcare use was also observed in younger and pluriparous women and those with low education; in addition, having a job improved the use of services, possibly through transmission of information of negative consequences due to delayed or few prenatal visits. Interestingly, this study found a substantial reduction in the number of pregnant women who do not use prenatal healthcare services properly. CONCLUSIONS: The aim of this research is to provide more accurate knowledge about the inadequate use of prenatal healthcare in Italy. Results highlight the existence of differences in healthcare use during pregnancy, especially for women from less advantaged social classes (i.e., unemployed or poorly educated). Such inequalities should be examined in all areas of public policy and public services, to ensure equal opportunity for their use.

The role of anti-smoking legislation on cigarette and alcohol consumption habits in Italy.

The short-term effects of public smoking bans on individual smoking and drinking habits were investigated in this paper. In 2005, a smoking ban was introduced in Italy, and we exploited this exogenous variation to measure the effect on both smoking participation and intensity and the indirect effect on alcohol consumption. Using data from the Everyday Life Aspects survey, for the period 2001-2007, we show that the introduction of smoke-free legislation in Italy significantly affected smoking behavior. We also document significant indirect effects on alcohol consumption for the main alcoholic beverage categories. A robustness analysis is also performed, to test the extent to which unobservable variables may bias our estimated parameters. Our results are then used to perform a cost-effectiveness analysis of the anti-smoking legislation in Italy.