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.     

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.     

Percutaneous renal mass biopsy: historical perspective,current status,and future considerations

Introduction: Percutaneous renal mass biopsy has evolved over the last decade with improvements on previous pitfalls including low tissue yield, high non-diagnostic rates, and complications. As understanding of tumor biology and natural history of renal cortical neoplasms has improved, percutaneous renal mass biopsy is poised to have an expanding role in an area characterized by individualized management and refined risk stratification.

Areas covered: This review summarizes the evolution of renal mass biopsy to its current state with respect to outcomes, indications, and clinical guidelines.

Expert opinion: With improved understanding of differential biological potential of renal cortical neoplasms combined with technical improvements in diagnostic yield and accuracy, utilization of renal mass biopsy is becoming an important adjunct to patient care in a broad range of clinical scenarios, including active surveillance, thermal ablation, and use of primary systemic therapy in localized and advanced settings.     

Research hotspots and effectiveness of repetitive transcranial magnetic stimulation in stroke rehabilitation

Repetitive transcranial magnetic stimulation, as a relatively new type of rehabilitation treatment, is a painless and non-invasive method for altering brain excitability. Repetitive transcranial magnetic stimulation has been widely used in the neurorehabilitation of stroke patients. Here, we used CiteSpace software to visually analyze 315 studies concerning repetitive transcranial magnetic stimulation for stroke rehabilitation from 1999 to 2019, indexed by Web of Science, to clarify the research hotspots in different periods and characterize the gradual process of discovery in this field. We found that four main points were generally accepted:(1) repetitive transcranial magnetic stimulation has a positive effect on motor function recovery in patients with subcortical stroke;(2) it may be more advantageous for stroke patients to receive low-frequency repetitive transcranial magnetic stimulation in the unaffected hemispheres than to receive high-frequency repetitive transcranial magnetic stimulation in affected hemisphere;(3) low-frequency repetitive transcranial magnetic stimulation has become a potential therapeutic tool for patients with non-fluent aphasia after chronic stroke for neurological rehabilitation and language recovery; and(4) there are some limitations to these classic clinical studies, such as small sample size and low test efficiency. Our assessment indicates that prospective, multi-center, large-sample, randomized controlled clinical trials are still needed to further verify the effectiveness of various repetitive transcranial magnetic stimulation programs for the rehabilitation of stroke patients.     

人工智能在耳鼻咽喉头颈外科的运用及展望

通过对大数据深度学习,近年人工智能技术已逐渐渗透到医学各个领域,实现一定程度应用。虽然耳鼻咽喉头颈外科专业近几年发表相关文献数量急剧增长,但大部分临床医生对于人工智能的研究还比较陌生。介绍人工智能的基本原理,列举、分析其在耳鼻喉科的主要研究情况,探讨目前人工智能技术实际应用的局限,展望未来人工智能技术在耳鼻喉科可能的应用。     

基于数据挖掘的国医大师刘祖贻治疗脑梗死恢复期方药规律研究

目的挖掘分析国医大师刘祖贻治疗脑梗死恢复期的处方用药规律,总结其学术思想。方法收集整理刘祖贻治疗脑梗死恢复期的病案处方,录入中医传承辅助平台软件中构建数据库,再使用该软件相关功能进行数据挖掘,分析处方中的组方用药规律。结果①共得处方147首,涉及药物179味,累计使用频次2 164次。②使用频次在20次及以上的药物,共有22味,其中前10味高频药物为黄芪、丹参、山楂、葛根、枸杞子、地龙、制何首乌、川芎、石菖蒲、淫羊藿。③黄芪用量从15 g至120 g均可见,最常用剂量为30 g,常用剂量范围主要集中于30～60 g。④药物功效分类排名靠前的为补虚药、活血化瘀药、平肝息风药等。⑤高频药组前5位为丹参-黄芪、黄芪-山楂、葛根-黄芪、葛根-丹参、丹参-山楂;关联度较高的药组有地龙-黄芪、葛根-地龙-黄芪、丹参-地龙-黄芪等。⑥通过聚类分析算法提取出核心组合12个,进而演化出潜在新方6首,如"白芍、威灵仙、桂枝、鸡血藤、白芥子""全蝎、菊花、蜈蚣、刺蒺藜"等。结论国医大师刘祖贻治疗脑梗死恢复期的用药以益气温阳、填精益髓、活血通络、息风化痰为主,重用黄芪,方以自拟芪仙通络方加减,体现出"气阳主用""脑髓阳生阴长"等学术思想。