Aetna (United States)

This paper focuses on quantifying the application boundaries of AI in financial transactions, identifying the cross-institutional risk spillover and transmission patterns, and constructing a multi-dimensional governance framework. Based on a dataset of 986 daily observations from 123 product accounts with a total asset value of 360 billion yuan from 2020 to 2024, combined with in-depth interviews with 15 leading asset management (AM) AI executives and comparative case studies, we develop a two-dimensional “scene-fit-risk tolerance” boundary quantification model and an “AI-securities firm-bank-asset management” risk transmission chain model. We propose the “3% boundary rule” and a three-tier governance framework of “technology-process-regulation.” Empirically validated by a century-old insurance asset management company, this framework reduced the AI transaction risk loss rate from 0.85% to 0.18% while maintaining a 35% improvement in transaction efficiency. It effectively addresses the core pain points of large-scale asset management institutions, such as blind AI application, concealed risk transmission, and an incomplete governance system, providing a solution with both theoretical support and practical value for the industry.

A vibration assessment was conducted to support the design of a ski resort in Utah, USA, with special consideration given to a gondola lift terminal planned near residential condos. The vibration generated from the terminal could propagate through the connected substructure, and an assessment was required to progress the structural and acoustic design. Vibration was measured at a similar gondola lift terminal to inform predictions using a Finite Element model. Structure-borne noise from the gondola system was also measured at a terminal building, and these measurements were used to support a separate empirical analysis. The study utilized a combination of approaches to guide design decisions and meet criteria for human comfort.

This paper discusses the administrative aspects of molecular diagnostics in oncology, including US Food and Drug Administration (FDA) oversight, the regulatory approval process, clinical, and operational workflows, and payment models. Comprehensive molecular testing is important to deliver optimal oncology care and improve patient outcomes. Despite the potential benefits of testing, utilization remains low. The FDA regulatory approval process is reviewed for in vitro diagnostic products, which includes classification into three regulatory classes on the basis of risk. Companion diagnostic devices are used to guide treatment decisions. The clinical and operational challenges associated with molecular testing in oncology are also discussed, including the rapidly evolving landscape of precision oncology, the wide range of biomarker testing options, and complexities of test ordering, interpretation, and result delivery. There is a need for a multifaceted support approach involving education, technology enhancements, and workflow support to overcome these challenges. In terms of payment models, coverage policies between Medicare and commercial payers are compared with differences in coverage criteria, with Medicare focusing on FDA approval or clearance, whereas commercial payers consider additional factors such as National Comprehensive Cancer Network and ASCO guidelines. Commercial payers tend to cover smaller panels on the basis of guideline-recommended biomarkers, whereas coverage for broad tumor profiling is limited. Several strategies can increase the utilization of molecular testing, including integrating test results into electronic medical record platforms, standardizing billing practices, increasing clinical trials, and primary literature supporting the use of molecular testing, educating physicians, and using tumor boards for result interpretation and treatment discussions.

Background: Healthcare 4.0 has transformed supply chain management in the healthcare sector, but there is a lack of comprehensive frameworks to evaluate the impact of Healthcare 4.0 technologies on sector operations, particularly in developing countries. Methods: This study introduces a multi-criteria framework that synergically combines the techno-economic implications of Healthcare 4.0 technologies to improve healthcare supply chain management. The proposed approach innovatively integrates fuzzy VIKOR and Entropy methods to handle data vagueness and uncertainty, using data collected from healthcare supply chain specialists in Lagos, Nigeria. Results: The developed framework identifies the most and least critical technical and economic parameters for Healthcare 4.0 implementation in healthcare supply chain management. It also determines the suitability of different Healthcare 4.0 technologies for supply chain management in the healthcare sector. Conclusions: The main innovation of this study lies in the development of a comprehensive and context-specific framework for evaluating Healthcare 4.0 technologies in healthcare supply chains. The framework offers a new perspective on technology evaluation and provides practical insights for decision-makers. The findings contribute to advancing knowledge and practice in this field, promoting the proper adoption of Healthcare 4.0 technologies in healthcare, particularly in developing countries.

ardiac rehabilitation (CR) is a well-established program for secondary prevention of cardiovascular disease.CR is a multimodal intervention that includes education, medication adherence promotion, risk factor management, nutritional counseling, psychosocial support, and structured exercise for patients with myocardial infarction, heart failure, stable angina, or following cardiac surgeries or catheter-based valve replacement procedures (eg, transcatheter aortic valve replacement).Patients who complete CR have lower mortality and hospitalizations as well as improved functional status and quality of life. 1 Additionally, CR is generally considered cost-effective based on current studies. 2 Given these benefits, CR is given a class 1A recommendation by the American Heart Association, the American College of Cardiology, and the European Society of Cardiology.However, a significant gap remains in CR participation rates; among Medicare beneficiaries in 2017, only 8% of patients were able to complete the recommended number of CR sessions. 3Furthermore, there are significant disparities in referral and participation that occur based on race, sex, and socioeconomic status. 4 Barriers to patient participation include transportation issues, work responsibilities, and financial and time constraints.To address these issues, the American Association of Cardiovascular and Pulmonary Rehabilitation, American Heart Association, and American College of Cardiology and national quality improvement initiatives, notably the Million Hearts initiative and the Agency for Healthcare Research and Quality TAKEheart initiative, have endorsed home-based CR and hybrid delivery models to improve access to CR. 5,6 Herein, we offer our perspective on current and future models of CR, and how technology may enable innovative models of CR to enhance health equity.

A parede celular do fungo é responsável pela proteção, forma e comunicação intracelular. Essas variedades funcionais, estão relacionadas à sua composição tendo como principais componentes glicanas e quitinas que podem ser variáveis de acordo com a espécie e gênero do fungo. O gênero Trichoderma está entre os mais estudados atualmente, devido a sua importância para a agricultura por ser efetivo contra patógenos de plantas. Neste estudo foram utilizados os isolados de Trichoderma, Trichoderma harzianum selvagem, Trichoderma harzianum mutante (Δepl1), Trichoderma asperellum e Trichoderma reesei e os fitopatógenos Sclerotinia sclerotiorum, Rhizoctonia solani e Fusarium oxysporum. O perfil de açúcares presentes na parede dos isolados de Trichoderma foi determinado por cromatografia líquida de alta eficiência (CLAE) revelando que estes apresentaram o mesmo perfil de mesmo perfil de glicose, oriunda de glucanas, e oligossacarídeos de quitobiose como pentacetil e diacetil bem como a N-acetilglicosamina presentes na estrutura de quitinas. Durante a interação com os fitopatógenos todos os isolados de Trichoderma apresentaram elevação de glucanas e quitinas. A atividade de glucanases e quitinases na interação de isolados de Trichoderma com os fitopatógenos mostrou que, durante a interação com os fitopatógenos, os isolados de Trichoderma apresentaram respostas diferentes dessas enzimas e que Trichoderma asperellum foi o que apresentou melhor atividade das enzimas avaliadas. Este trabalho mostrou a dinâmica existente de glucanas, quitinas e das enzimas degradadoras da parede celular de fitopatógenos, glucanases e quitinases, e que, essas alterações estão intimamente relacionadas com a composição da parede celular de fitopatógenos definindo-os bons candidatos como agentes no biocontrole.

Identifying hospitalizations for serious infections among patients dispensed biologic therapies within healthcare databases is important for post-marketing surveillance of these drugs. We determined the positive predictive value (PPV) of an ICD-10-CM-based diagnostic coding algorithm to identify hospitalization for serious infection among patients dispensed biologic therapy within the FDA's Sentinel Distributed Database. We identified health plan members who met the following algorithm criteria: (1) hospital ICD-10-CM discharge diagnosis of serious infection between July 1, 2016 and August 31, 2018; (2) either outpatient/emergency department infection diagnosis or outpatient antimicrobial treatment within 7 days prior to hospitalization; (3) inflammatory bowel disease, psoriasis, or rheumatological diagnosis within 1 year prior to hospitalization, and (4) were dispensed outpatient biologic therapy within 90 days prior to admission. Medical records were reviewed by infectious disease clinicians to adjudicate hospitalizations for serious infection. The PPV (95% confidence interval [CI]) for confirmed events was determined after further weighting by the prevalence of the type of serious infection in the database. Among 223 selected health plan members who met the algorithm, 209 (93.7% [95% CI, 90.1%-96.9%]) were confirmed to have a hospitalization for serious infection. After weighting by the prevalence of the type of serious infection, the PPV of the ICD-10-CM algorithm identifying a hospitalization for serious infection was 80.2% (95% CI, 75.3%-84.7%). The ICD-10-CM-based algorithm for hospitalization for serious infection among patients dispensed biologic therapies within the Sentinel Distributed Database had 80% PPV for confirmed events and could be considered for use within pharmacoepidemiologic studies.