Life Cycle Health Research Articles

Preliminary discussion on the whole life-cycle management of wisdom teeth health

The impaction rate of wisdom teeth is increasingly high, leading to more and more serious clinical problems. For a long time, the primary approach to managing wisdom teeth has been direct extraction, with a notable lack of systematic and diversified treatment methods. This article introduces, for the first time, the concept of whole life-cycle health management for wisdom teeth and suggests that the window for wisdom teeth life-cycle health management should be moved forward to the tooth germ stage. For tooth germs of wisdom teeth with severe risks, timely and necessary intervention should be administered. For normally erupting wisdom teeth, efforts should be made to maintain their health so they can function over the long term. For impacted wisdom teeth that have not caused related clinical symptoms, careful observation and cautious extraction should be considered. If necessary, techniques such as orthodontics and autotransplantation can be used to functionalize them. For impacted wisdom teeth that have caused clinical symptoms, functional oral surgical principles should be applied to reduce surgical trauma and prevent intraoperative and postoperative complications using advanced clinical techniques.

An operationalization framework for lifecycle health technology assessment: a Health Technology Assessment International Global Policy Forum Task Force report.

Operationalization guidance is needed to support health technology assessment (HTA) bodies considering implementing lifecycle HTA (LC-HTA) approaches. The 2022 Health Technology Assessment International (HTAi) Global Policy Forum (GPF) established a Task Force to develop a position paper on LC-HTA. In its first paper, the Task Force established a definition and framework for LC-HTA in order to tailor it to specific decision problems. This second paper focused on the provision of practical operational guidance to implement LC-HTA. Detailed descriptions of the three LC-HTA operational steps are provided (defining the decision problem, sequencing of HTA activities, and developing optimization criteria) and accompanied by worked examples and an operationalization checklist with 20 different questions for HTA bodies to consider when developing an LC-HTA approach. The questions were designed to be applicable across different types of HTA and scenarios, and require adaptation to local jurisdictions, remits, and context.

Status Quo and Prospects of Research on Precision Nursing of Life-Cycle Health and Disease

With the changing lifestyle and spectrum of diseases among Chinese people, the life-cycle approach to health has been given national strategic importance. Over the past decade, global nursing researchers have gradually started to pay more attention to the research related to precision nursing at different stages of the life cycle. Researchers have applied multi-omics to explore the pathogenesis and novel biomarkers of relevant symptoms in tumor patients or patients with chronic diseases in order to manage symptoms with better precision. However, systematic theories of precision nursing of life-cycle health and disease have not yet been developed, and the research field and its implications still need to be continuously expanded and innovated. In the nursing discipline, the advantages of interdisciplinary integration should be given full play and the precise and effective resolution of life-cycle health problems should be taken as its goal. Through accurately defining key quantitative objective indicators of nursing care, the nursing discipline will be able to achieve early identification of life-cycle health problems, clarify the occurrence and patterns of change in life-cycle health problems, and gain a better understanding of the regulatory mechanisms. Precise and effective nursing-related technologies and products of non-medication and non-surgery nature should be developed to achieve better precision in nursing interventions, thereby effectively promoting recovery from diseases and improving the overall health of the people.

The Construction of an Intrauterine Diagnosis and Treatment System and Comprehensive Lifecycle Health Service of Congenital Heart Disease: Xinhua Hospital Model

With the growing influence of slow population growth and population aging, China has established the birth policy and issued a series of documents to promote maternal and fetal health and improve the birth rate. With the increase in prevalence of birth defects, timely diagnosis and intervention in utero provide possibilities to reduce unnecessary abortions and offer better prognosis. Congenital heart disease (CHD), as one of the most common congenital birth defects, is the leading cause of mortality in patients aged <5 years, and brings a heavy burden to both the affected families and society. Fetuses with CHD are associated with an increased risk of pregnancy-related complications and premature birth, and children with CHD typically face growth and developmental problems even after the correction of malformation. Therefore, management including diagnosis, treatment, and rehabilitation throughout the fetal period into childhood and even adulthood is essential for children with CHD. Based on the rapid advances in intrauterine and perinatal medicine and an in-depth collaboration among obstetrics and pediatrics, a novel diagnosis and treatment system has been established for the management of CHD in the past 2 decades in Shanghai Xinhua Hospital. This Intrauterine Diagnosis and Treatment System and Comprehensive Lifecycle Health Service of Congenital Heart Disease model provides prenatal diagnosis, intrauterine intervention, delivery room service and neonatal therapies, and postintrauterine rehabilitation for children with CHD. We have developed a four-dimensional spatiotemporal image correlation echocardiography and a three-dimensional cardiac virtual endoscopy system for the intrauterine diagnosis of CHD, dramatically raising the diagnostic utility. Our innovative and independent newborn-intervention technique has effectively reduced the re-intervention rate in patients with pulmonary atresia with intact ventricular septum and critical pulmonary stenosis. In 2018, Xinhua Hospital independently performed the case of fetal aortic valvuloplasty in Asia through a multidepartment collaborative effort. All children treated in this system achieved biventricular circulation and a better long-term postoperative outcome. We also have conducted postoperative rehabilitation therapy to promote the development and health of children with CHD. The practice of Xinhua model has reduced unnecessary abortion of CHD fetuses, reduced the mortality rate associated with critical CHD, and improved the mid- and long-term prognosis in CHD, which is essential to promote the fertility level and children’s health. Furthermore, translational medicine platform and the birth cohort Early Life Plan was constructed to explore the origins of major developmental diseases and establish an early intervention model in CHD. This practice of assessment of the intrauterine system has been expanded to other congenital defects in Xinhua Hospital, and sequential treatment of more than 2,000 cases has been completed to date. Based on practice in intrauterine management of CHD and other diseases, the concept of Intrauterine Pediatrics was proposed as a first to emphasize early prevention and intervention of childhood diseases and promote a comprehensive lifecycle service for children. The development and evolution of this system requires further attention not only from researchers but also from the government and global medical communities.

Disease- and Drug-Related Knowledge Extraction for Health Management from Online Health Communities Based on BERT-BiGRU-ATT.

Knowledge extraction from rich text in online health communities can supplement and improve the existing knowledge base, supporting evidence-based medicine and clinical decision making. The extracted time series health management data of users can help users with similar conditions when managing their health. By annotating four relationships, this study constructed a deep learning model, BERT-BiGRU-ATT, to extract disease-medication relationships. A Chinese-pretrained BERT model was used to generate word embeddings for the question-and-answer data from online health communities in China. In addition, the bidirectional gated recurrent unit, combined with an attention mechanism, was employed to capture sequence context features and then to classify text related to diseases and drugs using a softmax classifier and to obtain the time series data provided by users. By using various word embedding training experiments and comparisons with classical models, the superiority of our model in relation to extraction was verified. Based on the knowledge extraction, the evolution of a user's disease progression was analyzed according to the time series data provided by users to further analyze the evolution of the user's disease progression. BERT word embedding, GRU, and attention mechanisms in our research play major roles in knowledge extraction. The knowledge extraction results obtained are expected to supplement and improve the existing knowledge base, assist doctors' diagnosis, and help users with dynamic lifecycle health management, such as user disease treatment management. In future studies, a co-reference resolution can be introduced to further improve the effect of extracting the relationships among diseases, drugs, and drug effects.

Central adiposity increases the odds for plasma folate deficiency among Chinese women of reproductive age.

ObjectiveTo explore the association between adiposity and plasma folate deficiency odds among women of reproductive age in China.MethodsA cross-sectional survey on nutritional status among women of reproductive aged 18–30 years in 2005–2006 in China was conducted. General adiposity was defined as body mass index (BMI) ≥24 kg/m2, and central adiposity was defined as waist circumference >80 cm. A plasma folate concentration <10.5 nmol/L (measured through microbiological assay) was defined as plasma folate deficiency. Odds ratios (ORs) and 95% confidence intervals (CIs) for plasma folate deficiency were calculated using a logistic regression model, with adjustment for potential confounders.ResultsA total of 3,076 women of reproductive age were included in the final analysis. Compared to women with normal BMI and WC, women with both general and central adiposity had the highest odds for plasma folate deficiency (OR = 3.107, 95% CI: 1.819–5.307). Women with exclusively central adiposity had excess odds for plasma folate deficiency (WC > 80 cm, BMI <24 kg/m2; OR = 2.448, 95% CI: 1.144–5.241), which was higher than women with exclusively general adiposity (BMI ≥ 24 kg/m2, WC ≤ 80 cm; OR = 1.709, 95% CI: 1.259–2.319). The combined use of BMI and WC can detect more women (11.7%) at higher plasma folate deficiency odds than either used alone.ConclusionsWomen with central adiposity in normal weight have higher odds for plasma folate deficiency than those with general obesity only. Early screening for central adiposity among women of reproductive age would be meaningful to prevent folate deficiency and improve life-cycle health.

Real-world cost effectiveness of first-line pembrolizumab for advanced melanoma: A population-based study by the Canadian Real-world Evidence Value for Cancer Drugs (CanREValue) Collaboration.

17 Background: Randomized controlled trials (RCTs) demonstrate large survival benefits with anti-PD-1 checkpoint inhibitors compared to anti-CTLA4 therapy for advanced melanoma. However, it remains unclear if patients in routine practice derive a similar survival benefit or if real-world health utilization differs from trials. Outcomes are needed to inform life-cycle health technology reassessment (HTA) with real-world cost-effectiveness analysis. Methods: This study compared patients with advanced melanoma treated with publicly funded first-line ipilimumab (September 2012 - December 2014) or pembrolizumab (June 2016 - March 2018) in Ontario, Canada. These periods were chosen to reflect distinct eras of access to treatment. Linked administrative databases were used to identify cases, covariates, health-utilization and all-cause death. Inverse probability of treatment weighting (IPTW) with stabilizing weights was used to adjust for covariates (including: age, sex, melanoma site, rurality, income, comorbidity, stage at diagnosis, cancer history, prior brain metastasis treatment). Using a three-year time horizon, individual patient-level censoring-adjusted costs in 2019 Canadian dollars with a 1.5% annual discount rate were determined from the public payer’s perspective. The outcome was quality-adjusted life-years (QALY) measured at the individual patient level. Health utilities were based on accepted Canadian values from the initial HTA. The incremental cost-effectiveness ratio (ICER) was determined with bootstrap confidence intervals (CI). Results: Ninety patients treated with first-line ipilimumab, and 300 with pembrolizumab were identified. Those receiving pembrolizumab were older (median 70 vs.63 years), more likely to have multiple comorbidities (12% vs. 8%), and no prior brain radiation (83% vs. 74%). Covariates were balanced after weighting. Pembrolizumab was associated with improved OS (43.1% vs. 22.1% with ipilimumab at 3 years, IPTW adjusted hazard ratio: 0.52, 95% CI: 0.39-0.70; p &lt; 0.001). Mean costs for pembrolizumab and ipilimumab were $212,706 (95% CI 196,122 - 229,290) and $158,352 ($143,218 - 173,484), and mean survival 1.20 QALY (95%CI 1.11 – 1.29) and 0.66 QALY (0.52 – 0.80) respectively. The ICER was $101,183/QALY (65,375 – 139,298). The probability of cost-effectiveness was 0%, 48% and 99% at willingness-to-pay thresholds of $50k, $100k and $150k respectively. Conclusions: In real-world patients, first-line pembrolizumab for advanced melanoma was associated with improved OS compared to ipilimumab. The real-world cost-effectiveness estimate of $101,183/QALY is similar to the model-based cost-effectiveness estimates ($114,389/QALY to $151,369/QALY) used in the initial health technology assessment recommendation prior to reimbursement.

Quantifying the life-cycle health impacts of a cobalt-containing lithium-ion battery

PurposeLithium-ion batteries (LIBs) have been criticized for contributing to negative social impacts along their life cycles, especially child labor and harsh working conditions during cobalt extraction. This study focuses on human health impacts — arguably the most fundamental of all social impacts. The aim is to quantify the potential life-cycle health impacts of an LIB cell of the type nickel-manganese-cobalt (NMC 811) in terms of disability-adjusted life years (DALY), as well as to identify hotspots and ways to reduce the health impacts.MethodsA cradle-to-gate attributional life-cycle assessment study is conducted with the functional unit of one LIB cell and human health as the sole endpoint considered. The studied LIB is produced in a large-scale “gigafactory” in Sweden, the cobalt sulfate for the cathode is produced in China, and the cobalt raw material is sourced from the Democratic Republic of the Congo (DRC). Potential health impacts from both emissions and occupational accidents are quantified in terms of DALY, making this an impact pathway (or type II) study with regard to social impact assessment. Two scenarios for fatality rates in the artisanal cobalt mining in the DRC are considered: a high scenario at 2000 fatalities/year and a low scenario at 65 fatalities/year.ResultsApplying the high fatality rate, occupational accidents in the artisanal cobalt mining in the DRC contribute notably to the total life-cycle health impacts of the LIB cell (13%). However, emissions from production of nickel sulfate (used in the cathode) and of copper foil (the anode current collector) contribute even more (30% and 20%, respectively). These contributions are sensitive to the selected time horizon of the life-cycle assessment, with longer or shorter time horizons leading to considerably increased or decreased health impacts, respectively.ConclusionsIn order to reduce the health impacts of the studied LIB, it is recommended to (i) investigate the feasibility of replacing the copper foil with another material able to provide anode current collector functionality, (ii) reduce emissions from metal extraction (particularly nickel and copper), (iii) increase the recycled content of metals supplied to the LIB manufacturing, and (iv) improve the occupational standards in artisanal mining in the DRC, in particular by reducing fatal accidents.

Life-cycle health technology assessment for precision oncology.

e18704 Background: Rapid advances in precision oncology challenge timely and sustainable reimbursement decisions. Life-cycle health technology assessment (LC-HTA) can enable conditional patient access to promising precision oncology innovations alongside evidence development. Our objective was to create a life-cycle evaluative framework, called PRecision oncology Evidence Development in Cancer Treatment (PREDiCT). Methods: Through an iterative, health system and stakeholder-informed approach, we designed our LC-HTA framework. Elements supporting data and evidence generation were subsequently implemented within British Columbia, Canada’s provincial cancer control system. Our development, refinement, and pilot implementation process included a structured literature review, multi-disciplinary international expert consultation, a formal gap assessment, and a series of pan-Canadian inter-disciplinary stakeholder workshops to refine framework elements. Results: We engaged n = 15 pan-Canadian and international stakeholders to co-develop the LC-HTA framework. Defining framework components include: (a) managed access that defines the time horizon and pricing conditions of real-world healthcare system trialing; (b) collection of core data elements required to enable economic evaluation of precision oncology using real world data; (c) externally leveraged real world data and evidence generation to determine comparative effectiveness, cost-effectiveness, and the value of conducting additional research; and (d) data interpretation updating decisions, including investment, continued evaluation, or disinvestment from managed access. Key to the success of early framework implementation is the expansion of infrastructure to enable routine collection and linkage of genomic sequencing and cancer treatment data, patient quality of life and clinical outcomes, as well as health resource use spanning the diagnostic, treatment, and follow up trajectory. Conclusions: Sustainable integration of precision oncology requires the design and implementation of learning healthcare systems (LHS) that integrate genomic data with other health information. LC-HTA moves beyond static estimates of clinical and cost-effectiveness to continuously generate evidence that reduces evidentiary uncertainty and supports life-cycle decisions. We are embarking on a PREDiCT pilot to implement the framework in real-time to demonstrate the ability of real-world data to support life cycle evaluation.

Survival and disease burden trend analysis of occupational pneumoconiosis from 1963 to 2020 in Shizuishan City

Objective: To understand the survival status and its influencing factors of occupational pneumoconiosis patients in Shizuishan City, and to analyze the disease burden of occupational pneumoconiosis and its trend, so as to provide scientific basis for formulating comprehensive prevention and treatment measures of occupational pneumoconiosis. Methods: A retrospective survey was conducted during July to December 2020 to explore the survival status of occupational pneumoconiosis patients who had been reported from 1963 to 2020 in Shizuishan City. The Kaplan-Meier method and Life-table method were used for survival analysis, and Cox proportional hazards regression model was used to analyze the influencing factors of survival time. The disability adjusted life years (DALY) was applied to analyze the disease burden of occupational pneumoconiosis and its temporal trend. Results: From 1963 to 2020, a total of 3263 cases of occupational pneumoconiosis were reported in Shizuishan City, of which 1467 died, so that the fatality rate was 44.96%. The median survival time was 26.71 years, average age of death was (70.55±10.92) years old. There were significant differences in the survival rates of occupational pneumoconiosis patients among different types, diagnosis age, exposure time, industry, initial diagnosis stage and whether upgraded (P<0.05) . As the survival time increased, the survival rate of patients decreased gradually. When the survival time was ≥50 years, the cumulative survival rate of patients was 4.20%. Cox regression analysis suggested that the type of pneumoconiosis, industry, diagnosis age, exposure time, initial diagnosis stage and whether upgraded were the influencing factors for the survival time of patients with occupational pneumoconiosis (P<0.05) . The total DALY attributable to occupational pneumoconiosis from 1963 to 2020 in Shizuishan City was 48026.65 person years, of which the years of life lost (YLL) was 15155.39 person years, and the average YLL was 10.33 years/person, and the years lost due to disability (YLD) was 32871.26 person years, and the average YLD was 10.07 years/person. The DALY attributed to coal worker's pneumoconiosis and silicosis were 39408.51 person years and 6565.02 person years, respectively, and they accounted for 82.06% and 13.67% of the total disease burden in Shizuishan City, respectively. The DALY caused by occupational pneumoconiosis in the age group of 40-49 years old and the first diagnosis of stage I occupational pneumoconiosis were higher, which were 20899.71 and 36231.97 person years, respectively. The average YLL and average YLD showed a volatility downtrend over time. Conclusion: The disease burden of occupational pneumoconiosis cannot be ignored in Shizuishan City, and timely targeted measures should be taken for key populations and key industries. It is recommended that life-cycle health management and hierarchical medical should be taken to improve the life quality of patients and prolong their lifes.

A Conceptual Framework for Life-Cycle Health Technology Assessment

ObjectivesHealth technology assessment (HTA) uses evidence appraisal and synthesis with economic evaluation to inform adoption decisions. Standard HTA processes sometimes struggle to (1) support decisions that involve significant uncertainty and (2) encourage continued generation of and adaptation to new evidence. We propose the life-cycle (LC)-HTA framework, addressing these challenges by providing additional tools to decision makers and improving outcomes for all stakeholders. MethodsUnder the LC-HTA framework, HTA processes align to LC management. LC-HTA introduces changes in HTA methods to minimize analytic time while optimizing decision certainty. Where decision uncertainty exists, we recommend risk-based pricing and research-oriented managed access (ROMA). Contractual procurement agreements define the terms of reassessment and provide additional decision options to HTA agencies. LC-HTA extends value-of-information methods to inform ROMA agreements, leveraging routine, administrative data, and registries to reduce uncertainty. ResultsLC-HTA enables the adoption of high-value high-risk innovations while improving health system sustainability through risk-sharing and reducing uncertainty. Responsiveness to evolving evidence is improved through contractually embedded decision rules to simplify reassessment. ROMA allows conditional adoption to obtain additional information, with confidence that the net value of that adoption decision is positive. ConclusionsThe LC-HTA framework improves outcomes for patients, sponsors, and payers. Patients benefit through earlier access to new technologies. Payers increase the value of the technologies they invest in and gain mechanisms to review investments. Sponsors benefit through greater certainty in outcomes related to their investment, swifter access to markets, and greater opportunities to demonstrate value.

Life-cycle health monitoring of composite structures using piezoelectric sensor network

The vacuum-assisted resin infusion (VARI) technique provides considerable advantages in manufacturing large-scale composite structures. An accurate and consecutive structural health monitoring system is urgently required to determine the initial quality and assess the structural integrity of a composite structure. In this paper, a real-time active smart diagnostic system (SDS) based on piezoelectric sensor network is proposed to monitor the whole life-cycle of composite structures. Experiments were conducted on carbon fiber reinforced plastic specimens with different thicknesses to investigate the monitoring capability of piezoelectric lead-zirconate-titanate (PZT) sensors used in the SDS approach. The PZT sensor networks inserted inside the composite structures during the VARI process are used to monitor not only the curing parameters, but also the health status of composite structures when they are in service after curing. To monitor the curing process only, the sensor network can also be installed on the bottom of the mould. Experimental results demonstrate that both 3D resin flow and degree of cure in the VARI process can be effectively monitored by the PZT sensor network. Meanwhile, the embedded PZT sensor network has the potential to identify the different stages in the curing process. It is obvious that the piezoelectric sensor network will provide important technical support for composite materials with the structure and function integrated.

Mining Early Life Risk and Resiliency Factors and Their Influences in Human Populations from PubMed: A Machine Learning Approach to Discover DOHaD Evidence.

The Developmental Origins of Health and Disease (DOHaD) framework aims to understand how early life exposures shape lifecycle health. To date, no comprehensive list of these exposures and their interactions has been developed, which limits our ability to predict trajectories of risk and resiliency in humans. To address this gap, we developed a model that uses text-mining, machine learning, and natural language processing approaches to automate search, data extraction, and content analysis from DOHaD-related research articles available in PubMed. Our first model captured 2469 articles, which were subsequently categorised into topics based on word frequencies within the titles and abstracts. A manual screening validated 848 of these as relevant, which were used to develop a revised model that finally captured 2098 articles that largely fell under the most prominently researched domains related to our specific DOHaD focus. The articles were clustered according to latent topic extraction, and 23 experts in the field independently labelled the perceived topics. Consensus analysis on this labelling yielded mostly from fair to substantial agreement, which demonstrates that automated models can be developed to successfully retrieve and classify research literature, as a first step to gather evidence related to DOHaD risk and resilience factors that influence later life human health.

Real-world cost-effectiveness of pertuzumab (P) with trastuzumab + chemo (T+Chemo) in patients (pts) with metastatic breast cancer (MBC): A population-based retrospective cohort study by the Canadian Real-world Evidence for Value in Cancer Drugs (CanREValue) collaboration.

1048 Background: Addition of P to T+chemo for MBC pts has been shown to improve overall survival (OS) in a pivotal randomized trial (hazard ratio [HR] = 0.66, 95% CI: 0.52, 0.84) (Baselga et al., NEJM 2012). In Canada, the manufacturer submission to the health technology assessment agency estimated that P produced 0.64 life years gained (LYG) with an incremental cost-effectiveness ratio (ICER) of $187,376/LYG over 10 years (CADTH-pCODR, 2013). This retrospective cohort analysis aims to determine the comparative real-world population-based effectiveness and cost-effectiveness of P among MBC pts in Ontario, Canada. Methods: MBC pts were identified from the Ontario Cancer Registry and linked to the New Drug Funding Program database to identify receipt of treatment between 1/1/2008 and 3/31/2018. Cases received P-T-chemo after universal public funding of P (Nov 2013) and controls received T-chemo before. Demographic (age, socioeconomic, rurality) and clinical (comorbidities, prior adjuvant treatments, prior breast cancer surgery, prior radiation, stage at diagnosis, ER/PR status) characteristics were identified from linked admin databases balanced between cases and controls using propensity score matching. Kaplan-Meier methods and Cox regressions accounting for matched pairs were used to estimate median OS and HR. 5-year mean total costs from the public health system perspective were estimated from admin claims databases using established direct statistical methods and adjusted for censoring of both cost and effectiveness using inverse probability weighting. ICERs and 95% bootstrapped CIs were calculated, along with incremental net benefit (INB) at various willingness-to-pay values using net benefit regression. Results: We identified 1,823 MBC pts with 912 cases and 911 controls (mean age = 55 years), of which 579 pairs were matched. Cases had improved OS (HR = 0.66; 95% CI: 0.57, 0.78), with median 3.4 years, compared to controls median OS of 2.1. P provided an additional 0.63 (95% CI: 0.48 – 0.84) LYG at an incremental cost of $196,622 (95% CI: $180,774, $219,172), with a mean ICER = $312,147/LYG (95% CI: $260,752, $375,492). At threshold of $100,000/LYG, the INB was -$133,632 (95% CI: -$151,525, -$115,739) with &lt; 1% probability of being cost-effective. Key drivers of incremental cost increase between groups included drug and cancer clinic costs. Conclusions: The addition of P to T-chemo for MBC increased survival but at significant costs. The ICER based on direct real-world data was higher than the initial economic model due to higher total costs for pts receiving P. This study demonstrated feasibility to derive ICER from person-level real-world data to inform cancer drug life-cycle health technology reassessment.

Optimal Long-Term Health Insurance Contracts: Characterization, Computation, and Welfare Effects

Reclassification risk is a major concern in health insurance where contracts are typically one year in length but health shocks often persist for much longer. While most health systems with private insurers emphasize short-run contracts paired with substantial pricing regulations to reduce reclassification risk, long-term contracts with one-sided insurer commitment have significant potential to reduce reclassification risk without the negative side effects of price regulation, such as adverse selection. In this paper, we theoretically characterize optimal long-term insurance contracts with one-sided commitment, extending prior models of this form in several key directions that are important for studying health insurance markets. We leverage this characterization to provide a simple algorithm for computing optimal contracts from primitives. We estimate key market fundamentals using data on all under-65 privately insured consumers in Utah and pair these estimates with our model to study comparative statics related to contract design and welfare. We find that the welfare value of a system that effectively implements these long-term contracts depends crucially on (i) the degree of public insurance pre-system health risk (ii) the distribution of expected lifetime income gradients in the population (iii) the stochastic process governing life-cycle health shocks (iv) the extent of consumer switching costs and (v) the degree of consumer myopia.

Is Human Digital Twin possible?

While Digital Twin finds its applications in many fields, mainly in advanced manufacturing, PLM (Product Lifecycle Management), and smart healthcare, attempt of using Digital Twin in full lifecycle management of human being is discussed. The concept of Augmented Digital Twin is put forward as the basis of the concept of Human Digital Twin (HDT), which is the core idea of the paper. With the experiences of Digital Twin application in smart manufacturing, PLM and smart healthcare, and the development of other related technologies such as Data Mining, Data Fusion Analysis, Artificial Intelligence, especially Deep Learning and Human Computer Science, a conclusion can be drawn naturally, that HDT is an enabling way of full lifecycle health management and it is possible to construct Human Digital Twin, particularly from the technology view. Comparison between Digital Twin and Human Digital Twin demonstrates the possibility. The concept, conceptual model and characteristics of HDT are presented for preparation of its construction. How to construct Human Digital Twin is discussed by proposing Human Digital Twin System Architecture and Implementation Approach. Also, it is pointed out that there will be a long way to go because of not only its extreme complexity, but also so many aspects being involved, especially the security and social ethics problem.

Diabetes health management strategy based on internet plus graded diagnosis and treatment strategy

Type 2 diabetes (T2D) is a widespread chronic disease with high rates of morbidity and mortality worldwide. Managing risk factors can effectively prevent acute and chronic complications, improve quality of life, and reduce mortality. Therefore, implementation of a diabetes health management strategy is urgently needed. Emerging medical technologies have strengthened communication between patients and clinicians. The establishment and improvement of the graded diagnosis and treatment system has promoted the prevention, treatment, and management of diabetes. A total of 300 patients diagnosed with T2D in the Health Management Center at the Affiliated Hospital of Nantong University were randomly divided into two groups: an internet plus graded diagnosis and treatment strategy group, and a control group. After 6 months, the physiological parameters, management indices, and complications were compared between the groups. Physiological indicators, such as body mass index (BMI), waist circumference, triglycerides, low-density lipoprotein, systolic and diastolic blood pressure, and blood glucose were significantly alleviated in the Internet plus graded diagnosis and treatment strategy group. Management indicators (such as blood glucose monitoring compliance rate, diet control compliance rate, and exercise compliance rate) also improved substantially. The incidence of hypoglycemia was notably increased compared to the control group. The new health management strategy for diabetes can improve lifestyle, ameliorate physiological indicators, reduce the complication rate, and form a virtuous cycle. This provides a positive impact on the entire life-cycle health management of diabetes, and is worthy of further promotion.

Early life risk and resiliency factors and their influences on developmental outcomes and disease pathways: a rapid evidence review of systematic reviews and meta-analyses.

The Developmental Origins of Health and Disease (DOHaD) framework aims to understand how environmental exposures in early life shape lifecycle health. Our understanding and the ability to prevent poor health outcomes and enrich for resiliency remain limited, in part, because exposure-outcome relationships are complex and poorly defined. We, therefore, aimed to determine the major DOHaD risk and resilience factors. A systematic approach with a 3-level screening process was used to conduct our Rapid Evidence Review following the established guidelines. Scientific databases using DOHaD-related keywords were searched to capture articles between January 1, 2009 and April 19, 2019. A final total of 56 systematic reviews/meta-analyses were obtained. Studies were categorized into domains based on primary exposures and outcomes investigated. Primary summary statistics and extracted data from the studies are presented in Graphical Overview for Evidence Reviews diagrams. There was substantial heterogeneity within and between studies. While global trends showed an increase in DOHaD publications over the last decade, the majority of data reported were from high-income countries. Articles were categorized under six exposure domains: Early Life Nutrition, Maternal/Paternal Health, Maternal/Paternal Psychological Exposure, Toxicants/Environment, Social Determinants, and Others. Studies examining social determinants of health and paternal influences were underrepresented. Only 23% of the articles explored resiliency factors. We synthesized major evidence on relationships between early life exposures and developmental and health outcomes, identifying risk and resiliency factors that influence later life health. Our findings provide insight into important trends and gaps in knowledge within many exposures and outcome domains.

Early Childhood Education and Life-Cycle Health

This paper forecasts the life-cycle treatment effects on health of a high-quality early childhood program. Our predictions combine microsimulation using non-experimental data with experimental data from a midlife long-term follow-up. The follow-up incorporated a full epidemiological exam. The program mainly benefits males and significantly reduces the prevalence of heart disease, stroke, cancer, and mortality across the life-cycle. For men, we estimate an average reduction of 3.8 disability-adjusted years (DALYs). The reduction in DALYs is relatively small for women. The gain in quality-adjusted life years (QALYs) is almost enough to offset all of the costs associated with program implementation for males and half of program costs for women.

Intelligent fault diagnosis system based on big data

In view of the actual problems existing in life-cycle health monitoring and diagnosis of large complex equipment, the machine-learning algorithm is applied to data mining of the equipment operation big data, the expert knowledge base is established, the diagnosis rules related to the fault are obtained, the intelligent online monitoring and remote diagnosis of the equipment health condition are realised. The system uses uncertain fault prediction method and hybrid intelligent algorithm to discover the hierarchical association between operation feature big data and operation faults, the feature extraction of operation faults, and the intelligent diagnosis of operation faults. It effectively improved the sensitivity, robustness, and accuracy of monitoring and diagnosis. In the cloud service platform based on the Internet of things, the system realises the intelligent fault prediction and diagnosis, establishes a proactive maintenance system, improves the production efficiency, and ensures the production safety.