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.

Community-based participatory research to engage disadvantaged communities: Levels of engagement reached and how to increase it. A systematic review.

Community-based participatory research (CBPR) is one of the most used community engagement frameworks to promote health changes in vulnerable populations. The more a community is engaged, the more a program can impact the social determinants of health. The present study aims to measure the level of engagement reached in randomized controlled trials (RCTs) using CBPR in disadvantaged populations, and to find out the CBPR components that better correlate with a higher level of engagement. A systematic review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Embase, Web of Science, MEDLINE, Cochrane and Scopus databases were queried. Engagement level was assessed using the revised version of IAP2 spectrum, ranging from "inform" to "shared leadership" . Fifty-one RCTs were included, belonging to 36 engagement programs. Fourteen CBPR reached the highest level of engagement. According to the multivariate logistic regression, a pre-existing community intervention was associated with a higher engagement level (OR = 10.08; p<0.05). The variable "institutional funding" was perfectly correlated with a higher level of engagement. No correlation was found with income status or type of preventive programs. A history of collaboration seems to influence the effectiveness in involving communities burdened with social inequities, so starting new partnerships remains a public health priority to invest on. A strong potentiality of CBPR was described in engaging disadvantaged communities, addressing social determinants of health. The key findings described above should be taken into account when planning a community engagement intervention, to build up an effective collaborative field between researchers and population.

Strengthening and promoting digital health practice: results from a Global Digital Health Partnership's survey.

Background and objective: The capacity to promote and disseminate the best evidence-based practices in terms of digital health innovations and technologies represents an important goal for countries and governments. To support the digital health maturity across countries the Global Digital Health Partnership (GDHP) was established in 2019. The mission of the GDHP is to facilitate global collaboration and knowledge-sharing in the design of digital health services, through the administration of surveys and white papers. Objective: The scope of this study is to critically analyze and discuss results from the Evidence and Evaluation GDHP Work Stream's survey, understand how governments and countries intend to address main obstacles to the digital health implementation, identify their strategies for a communication of effective digital health services, and promote the sharing of international based best practices on digital health. Methods: This survey followed a cross-sectional study approach. A multiple-choice questionnaire was designed to gather data. Choices were extracted from research publications retrieved through a rapid review. Results: Out of 29 countries receiving the survey, 10 returned it. On a scale from 1 to 5, eHealth systems/platforms (mean = 3.56) were indicated as the most important tool for centralized infrastructure to collect information on digital health, while primary care (mean = 4.0) represented the most voted item for healthcare services to collect information on digital health. Seven Countries out of 10 identified lack of organization, skepticism of clinicians, and accessibility of the population as a barriers to adopt digital health implementation, resulting to be the most voted items. Finally, the most endorsed priorities in digital health for Countries were the adoption of data-driven approaches (6 Countries), and telehealth (5 Countries). Conclusion: This survey highlighted the main tools and obstacles for countries to promote the implementation of evidence-based digital health innovations. Identifying strategies that would communicate the value of health care information technology to healthcare professionals are particularly imperative. Effective communication programs for clinicians and the general population in addition to improved digital health literacy (both for clinicians and citizens) will be the key for the real implementation of future digital health technologies.

Organizational Aspects of the Implementation and Use of Whole Genome Sequencing and Whole Exome Sequencing in the Pediatric Population in Italy: Results of a Survey.

This study explores the organizational aspects of whole genome sequencing (WGS) implementation for pediatric patients with suspected genetic disorders in Italy, comparing it with whole exome sequencing (WES). Health professionals' opinions were collected through an internet-based survey and analyzed using a qualitative summative content analysis methodology. Among the 16 respondents, most were clinical geneticists performing only WES, while 5 also used WGS. The key differences identified include higher needs for analyzing genome rearrangements following WES, greater data storage and security requirements for WGS, and WGS only being performed in specific research studies. No difference was detected in centralization and decentralization issues. The main cost factors included genetic consultations, library preparation and sequencing, bioinformatic analysis, interpretation and confirmation, data storage, and complementary diagnostic investigations. Both WES and WGS decreased the need for additional diagnostic analyses when not used as last-resort tests. Organizational aspects were similar for WGS and WES, but economic evidence gaps may exist for WGS in clinical settings. As sequencing costs decline, WGS will likely replace WES and traditional genetic testing. Tailored genomic policies and cost-effectiveness analyses are needed for WGS implementation in health systems. WGS shows promise for enhancing genetics knowledge and expediting diagnoses for pediatric patients with genetic disorders.

Whole genome sequencing diagnostic yield for paediatric patients with suspected genetic disorders: systematic review, meta-analysis, and GRADE assessment.

BACKGROUND: About 80% of the roughly 7,000 known rare diseases are single gene disorders, about 85% of which are ultra-rare, affecting less than one in one million individuals. NGS technologies, in particular whole genome sequencing (WGS) in paediatric patients suffering from severe disorders of likely genetic origin improve the diagnostic yield allowing targeted, effective care and management. The aim of this study is to perform a systematic review and meta-analysis to assess the effectiveness of WGS, with respect to whole exome sequencing (WES) and/or usual care, for the diagnosis of suspected genetic disorders among the paediatric population. METHODS: A systematic review of the literature was conducted querying relevant electronic databases, including MEDLINE, EMBASE, ISI Web of Science, and Scopus from January 2010 to June 2022. A random-effect meta-analysis was run to inspect the diagnostic yield of different techniques. A network meta-analysis was also performed to directly assess the comparison between WGS and WES. RESULTS: Of the 4,927 initially retrieved articles, thirty-nine met the inclusion criteria. Overall results highlighted a significantly higher pooled diagnostic yield for WGS, 38.6% (95% CI: [32.6 - 45.0]), in respect to WES, 37.8% (95% CI: [32.9 - 42.9]) and usual care, 7.8% (95% CI: [4.4 - 13.2]). The meta-regression output suggested a higher diagnostic yield of the WGS compared to WES after controlling for the type of disease (monogenic vs non-monogenic), with a tendency to better diagnostic performances for Mendelian diseases. The network meta-analysis showed a higher diagnostic yield for WGS compared to WES (OR = 1.54, 95%CI: [1.11 - 2.12]). CONCLUSIONS: Although whole genome sequencing for the paediatric population with suspected genetic disorders provided an accurate and early genetic diagnosis in a high proportion of cases, further research is needed for evaluating costs, effectiveness, and cost-effectiveness of WGS and achieving an informed decision-making process. TRIAL REGISTRATION: This systematic review has not been registered.

Potentiality of algorithms and artificial intelligence adoption to improve medication management in primary care: a systematic review.

OBJECTIVES: The aim of this study is to investigate the effect of artificial intelligence (AI) and/or algorithms on drug management in primary care settings comparing AI and/or algorithms with standard clinical practice. Second, we evaluated what is the most frequently reported type of medication error and the most used AI machine type. METHODS: A systematic review of literature was conducted querying PubMed, Cochrane and ISI Web of Science until November 2021. The search strategy and the study selection were conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses and the Population, Intervention, Comparator, Outcome framework. Specifically, the Population chosen was general population of all ages (ie, including paediatric patients) in primary care settings (ie, home setting, ambulatory and nursery homes); the Intervention considered was the analysis AI and/or algorithms (ie, intelligent programs or software) application in primary care for reducing medications errors, the Comparator was the general practice and, lastly, the Outcome was the reduction of preventable medication errors (eg, overprescribing, inappropriate medication, drug interaction, risk of injury, dosing errors or in an increase in adherence to therapy). The methodological quality of included studies was appraised adopting the Quality Assessment of Controlled Intervention Studies of the National Institute of Health for randomised controlled trials. RESULTS: Studies reported in different ways the effective reduction of medication error. Ten out of 14 included studies, corresponding to 71% of articles, reported a reduction of medication errors, supporting the hypothesis that AI is an important tool for patient safety. CONCLUSION: This study highlights how a proper application of AI in primary care is possible, since it provides an important tool to support the physician with drug management in non-hospital environments.

Medical Residents' Behaviours toward Compulsory COVID-19 Vaccination in a Tertiary Hospital in Italy.

To maintain safety conditions in the provision of care and assistance, and to protect healthcare workers (HCWs) and patients, the Italian government required compulsory COVID-19 vaccination for HCWs, including medical residents (MRs). The aim of this study was to assess COVID-19 vaccination coverage in MRs in a large tertiary hospital in Italy, before and after the introduction of compulsory vaccination, according to demographic characteristics and specific residency. A database on COVID-19 vaccination status and infection of resident medical doctors was created. Descriptive statistics and logistic regressions were carried out on the data. A total of 1894 MRs were included in the study. Being vaccinated in the same hospital as the residency program was significantly related to the year of residency and being enrolled in a frontline residency. A significant association between compliance with the compulsory primary cycle vaccination and vaccination in the hospital residency was observed. Being enrolled in the second, third, and last years of residency, and in a frontline residency, were predictive of being vaccinated in the residency hospital. Almost 100% of the MRs participating in the study were vaccinated against COVID-19. Compulsory vaccination of HCWs, alongside greater and clearer information about the risks and benefits of vaccination, represents an important booster to ensure public health and to promote quality and safety of care.

Approaches to priority identification in digital health in ten countries of the Global Digital Health Partnership.

Background: To promote shared digital health best practices in a global context, as agreed within the Global Digital Health Partnership (GDHP), one of the most important topics to evaluate is the ability to detect what participating countries believe to be priorities suitable to improve their healthcare systems. No previously published scientific papers investigated these aspects as a cross-country comparison. Objective: The aim of this paper is to present results concerning the priorities identification section of the Evidence and Evaluation survey addressed to GDHP members in 2021, comparing countries' initiatives and perspectives for the future of digital health based on internationally agreed developments. Methods: This survey followed a cross-sectional study approach. An online survey was addressed to the stakeholders of 29 major countries. Results: Ten out of 29 countries answered the survey. The mean global score of 3.54 out of 5, calculated on the whole data set, demonstrates how the global attention to a digital evolution in health is shared by most of the evaluated countries. Conclusion: The resulting insights on the differences between digital health priority identification among different GDHP countries serves as a starting point to coordinate further progress on digital health worldwide and foster evidence-based collaboration.

Assessing the potentiality of algorithms and artificial intelligence adoption to disrupt patient primary care with a safer and faster medication management: a systematic review protocol.

INTRODUCTION: In primary care, almost 75% of outpatient visits by family doctors and general practitioners involve continuation or initiation of drug therapy. Due to the enormous amount of drugs used by outpatients in unmonitored situations, the potential risk of adverse events due to an error in the use or prescription of drugs is much higher than in a hospital setting. Artificial intelligence (AI) application can help healthcare professionals to take charge of patient safety by improving error detection, patient stratification and drug management. The aim is to investigate the impact of AI algorithms on drug management in primary care settings and to compare AI or algorithms with standard clinical practice to define the medication fields where a technological support could lead to better results. METHODS AND ANALYSIS: A systematic review and meta-analysis of literature will be conducted querying PubMed, Cochrane and ISI Web of Science from the inception to December 2021. The primary outcome will be the reduction of medication errors obtained by AI application. The search strategy and the study selection will be conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses and the population, intervention, comparator and outcome framework. Quality of included studies will be appraised adopting the quality assessment tool for observational cohort and cross-sectional studies for non-randomised controlled trials as well as the quality assessment of controlled intervention studies of National Institute of Health for randomised controlled trials. ETHICS AND DISSEMINATION: Formal ethical approval is not required since no human beings are involved. The results will be disseminated widely through peer-reviewed publications.

Cancers: What Are the Costs in Relation to Disability-Adjusted Life Years? A Systematic Review and Meta-Analysis.

Cancers currently represent a leading cause of morbidity and mortality, and precisely estimating their burden is crucial for evidence-based decision-making. This study aimed at understanding the average costs of cancer-related disability-adjusted life years (DALYs) and highlighting possible differences in economic estimates obtained with diverse approaches. We searched four scientific databases to identify all the primary literature simultaneously investigating cancer-related costs and DALYs. In view of the different methodologies, studies were divided into two groups: those estimating costs starting from DALYs, and those independently performing cost and DALY analyses. The latter were pooled to compute costs per disease-related DALY: meta-analytic syntheses were performed for total costs and indirect costs, and in relation to the corresponding gross domestic product (GDP) per capita. The quality of included studies was assessed through the Quality of Health Economic Studies instrument. Seven studies were selected. Total and indirect pooled costs per DALY were, respectively, USD 9150 (95% CI: 5560-15,050) and USD 3890 (95% CI: 2570-5880). Moreover, the cost per cancer-related DALY has been found to be, on average, 32% (95% CI: 24-42%) of the corresponding countries' GDP per capita. Costs calculated a priori from DALYs may lead to results widely different from those obtained after data retrieval and model building. Further research is needed to better estimate the economic burden of cancer in terms of costs and DALYs.