Effects of state reinsurance programs on health insurance exchange premiums and insurer participation

Objective

The aim of the study was to estimate the effect of the state-based reinsurance programs through the section 1332 State Innovation Waivers on health insurance marketplace premiums and insurer participation.

Data Source

2015 to 2022 Robert Wood Johnson Foundation Health Insurance Exchange Compare Datasets.

Study Design

An event study difference-in-differences (DD) model separately for each year of implementation and a synthetic control method (SCM) are used to estimate year-by-year effects following program implementation.

Data Collection/Extraction Methods

Not applicable.

Principal Findings

Reinsurance programs were associated with a decline in premiums in the first year of implementation by 10%–13%, 5%–19%, and 11%–17% for bronze, silver, and gold plans (p < 0.05). There is a trend of sustained declines especially for states that implemented their programs in 2019 and 2020. The SCM analyses suggest some effect heterogeneity across states but also premium declines across most states. There is no evidence that reinsurance programs affected insurer participation.

Conclusion

State-based reinsurance programs have the potential to improve the affordability of health insurance coverage. However, reinsurance programs do not appear to have had an effect on insurer participation, highlighting the need for policy makers to consider complementary strategies to encourage insurer participation.     

物理治疗翻转课堂教学应用效果的系统综述

目的 系统评价翻转课堂教学模式在物理治疗学教学中的应用效果。方法 计算机检索CENTRAL、MEDLINE、EMBASE、CINAHL Plus、Academic Search Premier、Teacher Reference Center、ERIC以及Education Research,纳入翻转课堂教学模式应用于物理治疗学教学的原始研究。检索时限为建库至2021年6月。由2名研究人员独立完成文献筛选、数据提取、质量评价,对翻转课堂教学模式对比传统教学模式在物理治疗学教学中的效果进行综述。结果与结论 共检索文献1 307篇,最终纳入7篇,包括至少770名学生。发表时间集中在2013年至2019年,研究对象为物理治疗学专业学生,主要结局指标为考试成绩。翻转课堂教学模式总体说来可提高学生的笔试成绩,增强高阶思维能力,得到了学生和教师的积极评价。     

Bayesian consensus clustering for multivariate longitudinal data

In clinical and epidemiological studies, there is a growing interest in studying the heterogeneity among patients based on longitudinal characteristics to identify subtypes of the study population. Compared to clustering a single longitudinal marker, simultaneously clustering multiple longitudinal markers allow additional information to be incorporated into the clustering process, which reveals co-existing longitudinal patterns and generates deeper biological insight. In the current study, we propose a Bayesian consensus clustering (BCC) model for multivariate longitudinal data. Instead of arriving at a single overall clustering, the proposed model allows each marker to follow marker-specific local clustering and these local clusterings are aggregated to find a global (consensus) clustering. To estimate the posterior distribution of model parameters, a Gibbs sampling algorithm is proposed. We apply our proposed model to the primary biliary cirrhosis study to identify patient subtypes that may be associated with their prognosis. We also perform simulation studies to compare the clustering performance between the proposed model and existing models under several scenarios. The results demonstrate that the proposed BCC model serves as a useful tool for clustering multivariate longitudinal data.     

Priorities for content for a short-course on postoperative care relevant for low- and middle-income countries: an e-Delphi process with training facilitators

Most surgical and anaesthetic mortality and morbidity occurs postoperatively, disproportionately affecting low- and middle-income countries. Various short courses have been developed to improve patient outcomes in low- and middle-income countries, but none specifically to address postoperative care and complications. We aimed to identify key features of a proposed short-course addressing this topic using a Delphi process with low- and middle-income country anaesthesia providers trained as short-course facilitators. An initial questionnaire was co-developed from literature review and exploratory workshops to include 108 potential course features. Features included content; teaching method; appropriate participants; and appropriate faculty. Over three Delphi rounds (panellists numbered 86, 64 and 35 in successive cycles), panellists indicated which features they considered most important. Responses were analysed by geographical regions: Africa, the Americas, south-east Asia and Western Pacific. Ultimately, panellists identified 60, 40 and 54 core features for the proposed course in each region, respectively. There were high levels of consensus within regions on what constituted core course content, but not between regions. All panellists preferred the small group workshop teaching method irrespective of region. All regions considered anaesthetists to be key facilitators, while all agreed that both anaesthetists and operating theatre nurses were key participants. The African and Americas regional panels recommended more multidisciplinary healthcare professionals for participant roles. Faculty from high-income countries were not considered high priority. Our study highlights variability between geographical regions as to which course features were perceived as most locally relevant, supporting regional adaptation of short-course design rather than a one-size-fits-all model.     

人工智能在中医药领域的应用进展及现状思考

人工智能（Artificial Intelligence，AI）的蓬勃兴起为现代社会带来了前所未有的机遇，中医药是中华民族传承千年的文化瑰宝。随着人工智能技术不断在中医药领域的科技创新中崭露头角，二者的融合不断加深，人工智能在中医药领域的发展前景、争议挑战也引发了诸多思考。本文将从人工智能在中医药领域的应用入手，对人工智能辅助中医诊断、智能决策与数据挖掘、健康管理及中草药现代化研究等方面，就近年来国内外研究进展进行总结与分析，以期为AI视域下实现中医药现代化、智能化赋能。     

基于文本挖掘和生物医学数据库的新型冠状病毒肺炎药物发现

目的 基于文本挖掘技术和生物医学数据库对新型冠状病毒肺炎（COVID-19）相关文献进行数据挖掘分析，探究COVID-19及其主要症状发热、咳嗽、呼吸障碍相关基因靶点，筛选潜在有效的化学药和中药。方法 使用GenCLiP 3网站获取COVID-19和其主要症状咳嗽、发热、呼吸障碍共4个关键词的共有靶点，在METASCAPE数据库中对其进行基因本体（GO）和通路富集分析，再利用String数据库和Cytoscape软件构建共有靶点的蛋白质相互作用网络，筛选获得核心基因，运用DGIdb数据库、SymMap数据库针对核心基因进行中西医治疗药物预测。结果 获得COVID-19及其主要症状共有基因靶点28个，其中有IL2、IL1B、CCL2等核心基因16个，使用DGIdb数据库筛选获得与16个关键靶点相互作用的化学药包括沙利度胺、来氟米特、环孢素等28种，中药包括虎杖、黄芪、芦荟等70味。结论 COVID-19及其主要症状的病理机制可能和CD4、KNG1、VEGFA等28个共有基因相关，可能通过介导TNF、IL-17等信号通路参与COVID-19病理过程。潜在有效药物可能通过作用相关靶点通路起到治疗COVID-19的作用。     

《医疗质量管理办法》中医疗质量概念及相关问题探讨

采用文献复习和实证研究经验的方法对《医疗质量管理办法》中涉及的医疗质量概念及相关问题进行探讨。《医疗质量管理办法》中的医疗质量的定义存在重大缺失,没有涉及医疗服务的结果,特别是患者安全。医疗质量的定义应与国际相关权威机构保持一致,应高度重视医疗服务的结果,特别是患者安全。     

A Pilot First-in-Human Study of Embrace,a Polyethylene Glycol-Based Liquid Embolic Agent,in the Embolization of Malignant and Benign Hypervascular Tumors

PurposeTo investigate the safety and efficacy of an aqueous polyethylene glycol-based liquid embolic agent, Embrace Hydrogel Embolic System (HES), in the treatment of benign and malignant hypervascular tumors.Materials and MethodsA prospective, single-arm, multicenter study included 8 patients, 5 males and 3 females, with a median age of 58.5 years (30–85 years), who underwent embolization in 8 tumors between October 2019 and May 2020. Technical success was defined as successful delivery of HES to the index vessel, with disappearance of >90% of the targeted vascular enhancement or, for portal vein embolization, occlusion of the portal branches to the liver segments for future resection. The volume of HES administered, ease of use (5 point Likert scale), administration time, and adverse events (AEs) were recorded. Evaluation was performed at 7, 30, and 90 days via clinical assessment and blood testing, and follow-up imaging was performed at 30 days.ResultsEight patients were enrolled, and 10 embolizations were performed in 8 lesions. Tumors included hepatocellular carcinoma (n = 4), renal angiomyolipoma (n = 3), and intrahepatic cholangiocarcinoma (n = 1). Technical success was 100%, and the average ease of use was 3.3 ± 1.0 SD. The HES delivery time was 1–28 minutes (median, 16.5 minutes), and the HES volume injected was 0.4–4.0 mL (median, 1.3 mL). All patients reached 30-day follow-up with imaging, and 6 patients reached 90-day follow-up. There were 3 serious AEs in 2 patients that were unrelated to the embolic agent.ConclusionHES resulted in a 100% embolization technical success rate. The product ease of use was acceptable, and no target vessel recanalization was noted on follow-up imaging at 30 days.     

流动人口基层医疗卫生机构首诊现状及影响因素分析

目的:了解流动人口基层首诊现状及其影响因素,为推进流动人口分级诊疗提供实证参考依据。方法:基于2017年全国流动人口动态监测调查数据中82734名最近1次患病(负伤)流动人口数据,利用SPSS 25.0统计软件分析其基层首诊情况及影响因素。结果:82734名最近1次患病(负伤)流动人口中首选到基层医疗卫生机构就诊15936人,基层首诊率仅为19.3%;二分类logistic回归分析结果显示:年龄≥65岁、农业户口、流动时间0~5年、患慢性病、至少参加1项医疗保险,居住地到最近医疗服务机构所需时间≤15 min的流动人口患病后更愿意选择到基层首诊。学历大专及以上、家庭月均收入>10000元、市跨县、东北地区、不愿意落户、自评健康状况为不健康的流动人口患病后更不愿意选择到基层首诊。结论:流动人口患病(负伤)后选择到基层首诊率较低,年龄、受教育程度、户口类型、家庭月均总收入、流动时间、流动范围、流入地区域、落户意愿、自评健康状况、是否患慢性病、有无参加医疗保险、居住地到最近医疗服务机构所需时间是影响流动人口患病(负伤)后选择到基层首诊的主要因素。     

基于真实世界数据探讨中医药治疗糖尿病肾病用药规律的研究＊

目的 基于临床信息系统分析总结真实世界的数据，采用数据挖掘的方法探讨中医药治疗糖尿病肾病的用药规律。方法 收集2018年1月-2020年12月上海中医药大学附属曙光医院宝山分院健康信息系统确诊的糖尿病肾病的门诊或住院患者的诊疗信息，建立Excel数据库，采用Excel 2010软件统计高频药物的四气、五味、归经及功效；使用SPSS Modeler 18.0软件中的Apriori算法分析关联规则，采用web节点建构药对关联网状图；运用SPSS 25统计软件进行因子分析。结果 本研究最终纳入477例接受中药饮片治疗的DKD患者，在1203条方剂信息中，涉及中药462种；使用频数排名前5位的中药分别是黄芪、黄精、石斛、山茱萸、麦冬；使用频数前5类的中药类别分别是补气药、补阴药、清热燥湿药、活血调经药、息风止痉药；在30味高频药物中，苦、甘、辛药味最为常见；药性寒、温数量接近；归脾经、肝经、肺经、肾经居多；关联规则提示，药物组合中置信度最高的组合为地龙-当归-僵蚕，因子分析共得到5个有效因子，累积贡献率为47.33%。结论 中医药治疗DKD在补益气血阴阳的同时，兼顾对瘀血、湿邪和痰饮的治疗，结合证型，可考虑使用黄芪、黄精、石斛、山茱萸、麦冬、金蝉花等药物的使用，清热燥湿药物如黄连、黄芩、黄柏可适当加入，为使邪有去处，大黄、车前子或可增添疗效。