Reported Challenges in Health Technology Assessment of Complex Health Technologies

ObjectivesWith complex health technologies entering the market, methods for health technology assessment (HTA) may require changes. This study aimed to identify challenges in HTA of complex health technologies.MethodsA survey was sent to European HTA organizations participating in European Network for HTA (EUnetHTA). The survey contained open questions and used predefined potentially complex health technologies and 7 case studies to identify types of complex health technologies and challenges faced during HTA. The survey was validated, tested for reliability by an expert panel, and pilot tested before dissemination.ResultsA total of 22 HTA organizations completed the survey (67%). Advanced therapeutic medicinal products (ATMPs) and histology-independent therapies were considered most challenging based on the predefined complex health technologies and case studies. For the case studies, more than half of the reported challenges were “methodological,” equal in relative effectiveness assessments as in cost-effectiveness assessments. Through the open questions, we found that most of these challenges actually rooted in data unavailability. Data were reported as “absent,” “insufficient,” “immature,” or “low quality” by 18 of 20 organizations (90%), in particular data on quality of life. Policy and organizational challenges and challenges because of societal or political pressure were reported by 8 (40%) and 4 organizations (20%), respectively. Modeling issues were reported least often (n = 2, 4%).ConclusionsMost challenges in HTA of complex health technologies root in data insufficiencies rather than in the complexity of health technologies itself. As the number of complex technologies grows, the urgency for new methods and policies to guide HTA decision making increases.     

Assessing the Economic Value of Clinical Artificial Intelligence: Challenges and Opportunities

ObjectivesClinical artificial intelligence (AI) is a novel technology, and few economic evaluations have focused on it to date. Before its wider implementation, it is important to highlight the aspects of AI that challenge traditional health technology assessment methods.MethodsWe used an existing broad value framework to assess potential ways AI can provide good value for money. We also developed a rubric of how economic evaluations of AI should vary depending on the case of its use.ResultsWe found that the measurement of core elements of value—health outcomes and cost—are complicated by AI because its generalizability across different populations is often unclear and because its use may necessitate reconfigured clinical processes. Clinicians’ productivity may improve when AI is used. If poorly implemented though, AI may also cause clinicians’ workload to increase. Some AI has been found to exacerbate health disparities. Nevertheless, AI may promote equity by expanding access to medical care and, when properly trained, providing unbiased diagnoses and prognoses. The approach to assessment of AI should vary based on its use case: AI that creates new clinical possibilities can improve outcomes, but regulation and evidence collection may be difficult; AI that extends clinical expertise can reduce disparities and lower costs but may result in overuse; and AI that automates clinicians’ work can improve productivity but may reduce skills.ConclusionsThe potential uses of clinical AI create challenges for health technology assessment methods originally developed for pharmaceuticals and medical devices. Health economists should be prepared to examine data collection and methods used to train AI, as these may impact its future value.     

Development of an EQ-5D Value Set for India Using an Extended Design (DEVINE) Study: The Indian 5-Level Version EQ-5D Value Set

ObjectivesThis study aimed to develop the Indian 5-level version EQ-5D (EQ-5D-5L) value set, which is a key input in health technology assessment for resource allocation in healthcare.MethodsA cross-sectional survey using the EuroQol Group’s Valuation Technology was undertaken in a representative sample of 3548 adult respondents, selected from 5 different states of India using a multistage stratified random sampling technique. The participants were interviewed using a computer-assisted personal interviewing technique. This study adopted a novel extended EuroQol Group’s Valuation Technology design that included 18 blocks of 10 composite time trade-off (c-TTO) tasks, comprising 150 unique health states, and 36 blocks of 7 discrete choice experiment (DCE) tasks, comprising 252 DCE pairs. Different models were explored for their predictive performance. Hybrid modeling approach using both c-TTO and DCE data was used to estimate the value set.ResultsA total of 2409 interviews were included in the analysis. The hybrid heteroscedastic model with censoring at ?1 combining c-TTO and DCE data yielded the most consistent results and was used for the generation of the value set. The predicted values for all 3125 health states ranged from ?0.923 to 1. The preference values were most affected by the pain/discomfort dimension.ConclusionsThis is the largest EQ-5D-5L valuation study conducted so far in the world. The Indian EQ-5D-5L value set will promote the effective conduct of health technology assessment studies in India, thereby generating credible evidence for efficient resource use in healthcare.     

Diagnostics and Treatments of COVID-19: A Living Systematic Review of Economic Evaluations

ObjectivesAs healthcare systems continue to respond to the COVID-19 pandemic, cost-effectiveness evidence will be needed to identify which tests and treatments for COVID-19 offer value for money. We sought to review economic evaluations of diagnostic tests and treatments for COVID-19, critically appraising the methodological approaches used and reporting cost-effectiveness estimates, using a “living” systematic review approach.MethodsKey databases (including MEDLINE, EconLit, Embase) were last searched on July 12, 2021. Gray literature and model repositories were also searched. Only full economic evaluations published in English were included. Studies were quality assessed and data were extracted into standard tables. Results were narratively summarized. The review was completed by 2 reviewers independently, with disagreements resolved through discussion with a senior reviewer.ResultsOverall, 3540 records were identified, with 13 meeting the inclusion criteria. After quality assessment, 6 were excluded because of very severe limitations. Of the 7 studies included, 5 were cost-utility analyses and 2 were cost-effectiveness analyses. All were model-based analyses. A total of 5 evaluated treatments (dexamethasone, remdesivir, hypothetical) and 2 evaluated hypothetical testing strategies. Cost-effectiveness estimates were sensitive to the treatment effect on survival and hospitalization, testing speed and accuracy, disease severity, and price.ConclusionsPresently, there are few economic evaluations for COVID-19 tests and treatments. They suggest treatments that confer a survival benefit and fast diagnostic tests may be cost effective. Nevertheless, studies are subject to major evidence gaps and take inconsistent analytical approaches. The evidence may improve for planned updates of this “living” review.     

电子鼻技术应用于白及及其近似饮片快速辨识的可行性分析

目的：探讨电子鼻技术应用于白及及其近似饮片快速辨识的可行性。方法：收集134批白及及其近似饮片（白及45批、天麻30批、玉竹30批、黄花白及29批）作为待测样品,使用PEN3型电子鼻采集样品嗅觉感官数据作为自变量X,基于2020年版《中华人民共和国药典》和地方标准的鉴别结果,以及各饮片高效液相色谱法（HPLC）指纹图谱和原始采购信息,获得辨识模型的标杆数据Y,分别采用主成分分析-判别分析（PCA-DA）、偏最小二乘法-判别分析（PLS-DA）、最小二乘法-支持向量机（LS-SVM）及K-最近邻（KNN）4种化学计量学方法建立45批白及与89批非白及的二分类辨识模型和上述4种饮片的四分类辨识模型Y=F(X)。结果：经留一法交互验证,在二分类辨识中,上述4种模型分类正判率分别为97.01%、97.01%、98.51%和97.01%;在四分类辨识中,这4种模型分类正判率分别为97.76%、89.55%、98.51%和97.01%。二分类和四分类辨识模型的最高正判率均可达到98.51%,且均以LS-SVM算法为最优,最优核函数分别选择径向基核函数和线性核函数。最优模型判别结果良好,没有未分类样...     

Chronic Intake of Energy Drinks and Their Sugar Free Substitution Similarly Promotes Metabolic Syndrome

Energy drinks containing significant quantities of caffeine, taurine and sugar are increasingly consumed, particularly by adolescents and young adults. The putative effects of chronic ingestion of either standard energy drink, Mother^TM (ED), or its sugar-free formulation (sfED) on metabolic syndrome were determined in wild-type C57BL/6J mice, in comparison to a soft drink, Coca-Cola (SD), a Western-styled diet enriched in saturated fatty acids (SFA), and a combination of SFA + ED. Following 13 weeks of intervention, mice treated with ED were hyperglycaemic and hypertriglyceridaemic, indicating higher triglyceride glucose index, which was similar to the mice maintained on SD. Surprisingly, the mice maintained on sfED also showed signs of insulin resistance with hyperglycaemia, hypertriglyceridaemia, and greater triglyceride glucose index, comparable to the ED group mice. In addition, the ED mice had greater adiposity primarily due to the increase in white adipose tissue, although the body weight was comparable to the control mice receiving only water. The mice maintained on SFA diet exhibited significantly greater weight gain, body fat, cholesterol and insulin, whilst blood glucose and triglyceride concentrations remained comparable to the control mice. Collectively, these data suggest that the consumption of both standard and sugar-free forms of energy drinks induces metabolic syndrome, particularly insulin resistance.     

Athletes’ and Coaches’ Perceptions of Nutritional Advice: Eating More Food for Health and Performance

Background: Low energy availability results in physiological adaptations which contribute to unfavourable health outcomes. Little information exists on perceptions of nutritional advice to eat more food to maintain health and enhance performance. The aim of this study was to explore athletes’ and coaches’ perceptions towards advice to athletes to eat larger than their current quantities of food and to explore how nutritionists could deliver this advice. Methods: Semi-structured interviews (~20 min in length) were conducted using online communication technology, audio-recorded, and transcribed verbatim. The interview explored perceptions of the nutritional advice provided, its role in health and performance, and the challenges to eating larger amounts of food. Data were analysed using NVIVO 1.2 using an inductive thematic approach. Results: Nine elite athletes (female = 6; males = 3) and nine high-performance coaches (female = 3; male = 6) completed the semi-structured interviews. Athletes reported improved training consistency, fewer injuries and illnesses, and improved resilience when consuming adequate energy and nutrients to meet their needs. Lack of time and meal preparation difficulties were the main challenges faced to fuelling. Conclusions: Although education about under-fuelling is important, motivating, enabling, and supporting athletes to change behaviour is pivotal to increasing athlete self-awareness and to make long-term nutritional changes.     

科技期刊出版运营需求调研与分析

【目的】 了解科技期刊从业人员和科研工作者对科技期刊出版技术、运营、传播的需求,探究可行的技术应用、工具开发和平台建设策略。【方法】 2020年11月,通过问卷星向科技期刊从业人员和科研工作者进行问卷调查;问卷涉及参与问卷调查人员对当今互联网技术发展、科技期刊运营模式、学术成果传播途径的了解和需求。【结果】 从402份面向科技期刊从业人员以及138份面向科研工作者的有效问卷中总结得出,参与问卷调查人员对互联网技术的应用、运营手段的丰富和传播途径的扩展有实际需求。【结论】 结合目前国际出版领域领先的出版技术与运营和传播实践,向科技期刊及相关公司机构提出技术应用、运营平台建设和传播体系搭建的相关可行性建议。     

The Australian Obesity Management Algorithm: A simple tool to guide the management of obesity in primary care

Obesity is a complex and multifactorial chronic disease with genetic, environmental, physiological and behavioural determinants that requires long-term care. Obesity is associated with a broad range of complications including type 2 diabetes, cardiovascular disease, dyslipidaemia, metabolic associated fatty liver disease, reproductive hormonal abnormalities, sleep apnoea, depression, osteoarthritis and certain cancers. An algorithm has been developed (with PubMed and Medline searched for all relevant articles from 1 Jan 2000–1 Oct 2021) to (i) assist primary care physicians in treatment decisions for non-pregnant adults with obesity, and (ii) provide a practical clinical tool to guide the implementation of existing guidelines (summarised in Appendix 1) for the treatment of obesity in the Australian primary care setting.Main recommendations and changes in managementTreatment pathways should be determined by a person’s anthropometry (body mass index (BMI) and waist circumference (WC)) and the presence and severity of obesity-related complications. A target of 10–15% weight loss is recommended for people with BMI 30–40 kg/m² or abdominal obesity (WC > 88 cm in females, WC > 102 cm in males) without complications. The treatment focus should be supervised lifestyle interventions that may include a reduced or low energy diet, very low energy diet (VLED) or pharmacotherapy. For people with BMI 30–40 kg/m² or abdominal obesity and complications, or those with BMI > 40 kg/m² a weight loss target of 10–15% body weight is recommended, and management should include intensive interventions such as VLED, pharmacotherapy or bariatric surgery, which may be required in combination. A weight loss target of > 15% is recommended for those with BMI > 40 kg/m² and complications and they should be referred to specialist care. Their treatment should include a VLED with or without pharmacotherapy and bariatric surgery.     

Metabolic rate and substrate oxidation of young males with obesity at the different sleep stages

ObjectiveInsufficient and poor-quality sleep among young adults is closely related to obesity and may impact metabolic processes. The mobilization and use of endogenous substrates during sleep, especially fat oxidation, is essential for energy metabolism. This study investigated whether there are differences in sleep structure, metabolic rate, substrate oxidation, and the respiratory quotient (RQ) between young males with normal weight and obesity according to sleep stages and overnight sleep.MethodsFifteen young males with normal weight and fifteen with obesity posited electrodes of polysomnography (PSG) and slept in the metabolic chamber for estimation of sleep structure, sleep metabolic rate (SMR), carbohydrate oxidation (CHOO), fat oxidation (FATO), and RQ. Fat-free mass (FFM) was measured by bioelectrical impedance analysis.ResultsThe sleep period time (p = 0.038) and total sleep time (p = 0.032) were significantly shorter in the obesity group than in the normal-weight group. The obesity group also had a longer sleep latency (p = 0.034) and more sleep-turning events (p = 0.018). CHOO/FFM and the RQ were higher in the obesity group while FATO/FFM was significantly higher in the normal-weight group. FATO/FFM was also higher in the normal-weight group in each sleep stage whereas the RQ was higher in the obesity group (p < 0.05).ConclusionsYoung males with obesity showed lower fat oxidation and more dominant carbohydrate-derived fuel oxidation than normal-weight during sleep and experienced shorter sleep periods and total sleep time.