Hasil untuk "Insurance"

Jiayi Guo, Panyi Dong, Zhiyu Quan

When working with real-world insurance data, practitioners often encounter challenges during the data preparation stage that can undermine the statistical validity and reliability of downstream modeling. This study illustrates that conventional data preparation procedures such as random train-test partitioning, often yield unreliable and unstable results when confronted with highly imbalanced insurance loss data. To mitigate these limitations, we propose a novel data preparation framework leveraging two recent statistical advancements: support points for representative data splitting to ensure distributional consistency across partitions, and the Chatterjee correlation coefficient for initial, non-parametric feature screening to capture feature relevance and dependence structure. We further integrate these theoretical advances into a unified, efficient framework that also incorporates missing-data handling, and embed this framework within our custom InsurAutoML pipeline. The performance of the proposed approach is evaluated using both simulated datasets and datasets often cited in the academic literature. Our findings definitively demonstrate that incorporating statistically rigorous data preparation methods not only significantly enhances model robustness and interpretability but also substantially reduces computational resource requirements across diverse insurance loss modeling tasks. This work provides a crucial methodological upgrade for achieving reliable results in high stakes insurance applications.

Xi Xin, Giles Hooker, Fei Huang

Proxy-based race inference is increasingly used to conduct fairness assessments when protected-class data are unavailable or legally restricted -- most prominently in U.S. fair-lending enforcement, and now explicitly contemplated in emerging insurance regulation, including Colorado's draft SB21-169 testing framework and New York's Insurance Circular Letter No. 7. Despite this growing regulatory relevance, little is known about how standard regression-based discrimination analyses behave when race is measured with error through proxies such as Bayesian Improved Surname Geocoding (BISG) or Bayesian Improved First Name and Surname Geocoding (BIFSG). This paper studies the consequences of using proxy-imputed race as a categorical regressor in regression-based fairness assessments. Treating proxy race as a categorical covariate subject to misclassification, we show that proxy-based coefficients become weighted mixtures of true group effects, systematically shrinking estimated disparities toward the majority group -- even when overall classification accuracy is high. Empirically, using a linked North Carolina voter-insurance dataset with self-reported race and ZIP-level auto insurance premiums, we demonstrate two mechanisms through which it distorts inference: (i) the intrinsic mixing of group effects implied by misclassification, and (ii) structured errors that vary with ZIP-level racial composition and socioeconomic conditions and remain correlated with pricing residuals after controls. As a result, regression-based disparity estimates can be attenuated or amplified relative to analogous analyses based on self-reported race. Our findings caution against treating proxy race as a plug-in substitute in regulatory testing and highlight design implications for proxy-based audit frameworks in insurance and other high-stakes domains.

Lin Zhu, Wenyue Lu, Zhiqing Elaine Liu et al.

IntroductionAsian Americans are disproportionately affected by chronic hepatitis B (CHB), which is caused by infection with hepatitis B virus (HBV). While adherence to antiviral medication is an effective practical approach to managing CHB and preventing liver cancer, medication adherence rates among Chinese and Vietnamese Americans with CHB, two vulnerable yet understudied populations, remain largely unknown.MethodsWe designed and implemented a randomized controlled clinical trial to investigate the potential improvement of long-term adherence to HBV medication in Asian American populations. Eligible Asian American HBV patients were recruited from the Greater Philadelphia and New York City. HBV medication adherence was assessed using the 8-Item Morisky Medication Adherence Scale. We conducted ordinary least squares (OLS) regression to examine the intervention effects on medication adherence among 129 Chinese and Vietnamese Americans taking CHB medication.ResultsAmong 129 participants (91 Chinese and 38 Vietnamese), about three-quarters (74.4%) reported limited English proficiency. Almost one out of 10 (9.3%) did not have any health insurance. OLS regression results indicated that the intervention had a significant impact on improving medication adherence at 12-month follow-up assessment (coefficient = 0.56, p = 0.04). In addition, we found that depression score at baseline was negatively associated with medication adherence at 12-month follow-up assessment (coefficient = −0.10, p = 0.003), with other covariates held constant.DiscussionThe findings show that a community-based culturally appropriate intervention significantly improved adherence to medication among Chinese and Vietnamese Americans with CHB in a 12-month period. Providing mental health support to CHB patients in this population may play an important role in improving medication adherence.Clinical trial registration[https://clinicaltrials.gov/study], identifier [NCT04082338].

Alokesh Manna, Aditya Vikram Sett, Dipak K. Dey et al.

Prediction uncertainty quantification is a key research topic in recent years scientific and business problems. In insurance industries (\cite{parodi2023pricing}), assessing the range of possible claim costs for individual drivers improves premium pricing accuracy. It also enables insurers to manage risk more effectively by accounting for uncertainty in accident likelihood and severity. In the presence of covariates, a variety of regression-type models are often used for modeling insurance claims, ranging from relatively simple generalized linear models (GLMs) to regularized GLMs to gradient boosting models (GBMs). Conformal predictive inference has arisen as a popular distribution-free approach for quantifying predictive uncertainty under relatively weak assumptions of exchangeability, and has been well studied under the classic linear regression setting. In this work, we propose new non-conformity measures for GLMs and GBMs with GLM-type loss. Using regularized Tweedie GLM regression and LightGBM with Tweedie loss, we demonstrate conformal prediction performance with these non-conformity measures in insurance claims data. Our simulation results favor the use of locally weighted Pearson residuals for LightGBM over other methods considered, as the resulting intervals maintained the nominal coverage with the smallest average width.

Alexey V. Lychagin, Andrey A. Gritsyuk, Mikhail P. Elizarov et al.

<b>Background</b>: Lower limb malalignment is a hallmark of knee osteoarthritis, with surgical correction techniques evolving from traditional mechanical alignment (MA) to kinematic alignment (KA) approaches. Restrictive kinematic alignment (rKA) represents a hybrid strategy combining principles from both techniques. This study evaluated short-term functional outcomes following robotic-assisted total knee arthroplasty (RoTKA), comparing MA versus rKA alignment strategies. <b>Methods</b>: This prospective, randomized, single-center study enrolled 96 patients with grade 3–4 idiopathic knee osteoarthritis (Kellgren–Lawrence classification). Patients were randomized to MA (<i>n</i> = 49, mean age 67 ± 9 years) or rKA (<i>n</i> = 47, mean age 66 ± 7 years) groups. Preoperative hip–knee–ankle (HKA) angles were 172.6° ± 1.1° and 172.9° ± 0.9° for MA and rKA groups, respectively. Outcomes were assessed using Visual Analog Scale (VAS) pain scores, range of motion (ROM), Knee Society Score (KSS), Oxford Knee Score (OKS) (primary outcome), SF-36, and Forgotten Joint Score (FJS-12). <b>Results</b>: Postoperative HKA angles were 179.5° ± 1.2° (MA) and 176.0° ± 1.5° (rKA). At 14 days postoperatively, knee ROM increased by 20.5% in the MA group and 25.7% in the rKA group, with a statistically significant 5.2% intergroup difference, indicating faster postoperative recovery (<i>p</i> = 0.008). VAS pain scores decreased by 7% in the rKA group while increasing by 13% in the MA group (<i>p</i> < 0.001). At one-year follow-up, FJS-12 scores were significantly higher in the rKA group (94.8 ± 3.2 vs. 91.9 ± 2.2, <i>p</i> < 0.001). No significant differences were observed in KSS, OKS, or SF-36 score between groups. <b>Conclusions</b>: Restrictive kinematic alignment demonstrated superior early postoperative outcomes compared to mechanical alignment in RoTKA, with significantly reduced pain and improved ROM. While one-year functional outcomes were comparable between techniques, rKA may offer advantages in the immediate postoperative period, supporting its consideration as a viable alignment strategy in robotic-assisted knee arthroplasty.

Amanda Terry, Chelsea Arnold, Zackery White et al.

Abstract Background In August 2020, Sarasota Memorial Health Care System (Sarasota Memorial) invested in Unite Us, a closed-loop referral platform, to address obstetric (OB) patients’ non-medical needs. The platform was used to electronically refer patients delivering at Sarasota Memorial who screened positive for these needs to a local network of community-based organizations. Methods A pre-post intervention study with a quasi-experimental, 1:1 matched design was used to measure the impact of implementing a technology-enabled care coordination platform on postpartum health care utilization. Deliveries were matched on patient and birth characteristics including age, race and ethnicity, marital status, insurance type, maternal comorbidities, and birth-specific factors. The impact of the Unite Us platform was assessed using conditional logistic regression, and results were stratified by insurance type, delivery method, low birthweight, preterm delivery, marriage status, infection complications, mental health diagnoses, and race/ethnicity. Results The study consisted of 1,996 deliveries with a live birth, 998 of which were to patients referred for community care through Unite Us from August 27, 2020 to January 31, 2023. These were matched with 998 deliveries with a live birth prior to Unite Us implementation, from January 1, 2019 to August 26, 2020. Matches were predominantly Medicare or Medicaid insured (65.0%), White, Non-Hispanic (56.6%) or Hispanic (28.2%), and never married (62.6%). When stratified by insurance type, patients who were enrolled in Medicaid/Medicare insurance at delivery were 59% less likely (OR: 0.41; 95% CI: 0.17 to 0.99) to be readmitted to the hospital within thirty days of discharge and were 55% less likely (OR: 0.45; 95% CI: 0.21 to 0.99) to have any OB-related inpatient admission within six months of discharge when compared to those who received usual care before Unite Us’ implementation. Conclusions Using the Unite Us platform as a digital tool to advance care coordination, the OB Service line within Sarasota Memorial observed statistically significant reductions in postpartum healthcare utilization in Medicaid/Medicare beneficiaries indicating that addressing non-medical, health-related needs may improve postpartum outcomes and reduce costs. These referral data are also used to facilitate community discussions on ways to build a more supportive network to improve maternal and child health outcomes.

Harsh Vivek Harkare, Marina Antillón, Axel J. Schmidt et al.

  BACKGROUND: This study was conducted as part of the Swiss National Programme to Stop HIV, Hepatitis B Virus, Hepatitis C Virus and Sexually Transmitted Infections (NAPS), which aims to reduce the spread of sexually transmitted infections in Switzerland. The goal was to identify the most effective and cost-efficient screening strategies to lower the incidence of human immunodeficiency virus (HIV), hepatitis C virus (HCV), syphilis, Neisseria gonorrhoeae and Chlamydia trachomatis by improving access to screening. METHODS: A Markov model was developed to assess the impact of various screening strategies among key populations over two years, including men who have sex with men (MSM), female sex workers (FSW) and people who inject drugs (PWID). The model further stratifies individuals based on partner number (MSM) and injection-equipment sharing (PWID). Comprehensive cost estimates for screening and treatment were derived from insurance data, literature and expert opinions. The effectiveness of screening interventions was evaluated by measuring reductions in disease incidence and cost savings, comparing the costs of screening to those of acute and chronic care for prevented infections. RESULTS: Increased screening frequency among key populations led to a reduction in incidence for all five infections studied. The largest effect was seen in people who inject drugs who share injecting equipment, where HCV incidence fell by up to 76% with four annual screens. However, only screening for HIV, HCV and syphilis proved to be cost-saving. Screening for Chlamydia trachomatis and Neisseria gonorrhoeae consistently incurred net costs due to the high screening costs and relatively low treatment costs. CONCLUSION: Targeted expansion of screening among key populations can reduce the incidence of HIV, HCV and syphilis in Switzerland, with regular screening offering potential cost savings to insurers under specific coverage and treatment scenarios.

Leona Hoffmann, Lorenza Gilardi, Tobias Antoni et al.

Abstract COVID-19 had a devastating impact on humanity. We investigated how residential air pollution (ozone (O3), nitrogen dioxide (NO2), fine particulate matter (PM2.5)) and meteorological factors (temperature (Temp), precipitation (Prec)) are associated with COVID-19 incidence in Baden-Württemberg (BW), Germany. We utilized data from the Copernicus Atmosphere Monitoring Service and the Copernicus Climate Change Service to model environmental exposure from 2020 to 2022 in postal code areas in BW. Health insurance data on SARS-CoV-2 infections were provided from the health insurance AOK BW on a quarterly level covering approximately 12 million person-years. We examined the spatiotemporal variability with a generalized additive model including various stressors, demographic factors, and area-wide data, offering a comprehensive analysis of the environmental stressor- COVI-10 incidence associations. In 2022, during the prevalence of the Omicron variant, the number of COVID-19 cases tripled compared to 2020. During the pre-Omicron period, COVID-19 incidence showed a positive association with PM2.5 (relative risk [RR] 2.41; 95% confidence interval [CI] (2.31, 2.52)), a negative association with Temp (RR 0.39 (0.32, 0.48)), and no clear or slight associations with O3, Prec, and NO2. During the Omicron period, there were either no clear or slight negative associations with Temp (RR 0.92 (0.74, 1.30)), PM2·5 (RR 0.70 (0.64, 0.79)), NO2, and Prec and a negative association with O3 (RR 0.46 (0.40, 0.53)). The analysis found clear links between environmental stressors and COVID-19 incidence, which strongly differed between pre-Omicron and Omicron periods. Consideration of environmental stressor concentration could be relevant in the management of the pandemic.

Khay-Seng Soh, Cheng-Li Lin, Wei-Ming Lee et al.

<b>Background:</b> Pneumoconiosis is associated with chronic pulmonary and systemic complications, yet its relationship with pleural empyema remains insufficiently defined. This study evaluated the risk of pleural empyema among individuals with pneumoconiosis using a nationwide population-based cohort. <b>Methods:</b> Using Taiwan’s National Health Insurance database, we identified 14,441 patients with newly diagnosed pneumoconiosis and 57,764 matched controls by age, sex, and index year. Pleural empyema was ascertained using ICD-based definitions. Cox proportional hazards models, stratified and cluster-adjusted to account for matched design, were used to estimate hazard ratios (HRs). Competing-risk models, propensity score matching, E-value estimation, and mediation analysis were performed to evaluate robustness and residual confounding. <b>Results:</b> During follow-up, the incidence of pleural empyema was significantly higher in the pneumoconiosis cohort than in controls (2.33 vs. 1.02 per 1000 person-years). Pneumoconiosis was associated with an increased risk of pleural empyema (adjusted HR = 1.79, 95% CI: 1.47–2.18), consistent across subgroup analyses and competing-risk models. The strongest associations were observed among younger individuals and those without comorbidities. Sensitivity analyses, including 1:1 propensity score matching, yielded similar effect estimates. The E-value suggested that only a strong unmeasured confounder could fully explain the observed association. <b>Conclusions:</b> Patients with pneumoconiosis face a substantially elevated risk of developing pleural empyema, independent of demographic factors, comorbidities, corticosteroid use, and healthcare utilization. Intensified monitoring for pleural complications in pneumoconiosis patients who develop respiratory infections may lead to earlier diagnosis and a reduction in the negative outcomes associated with pleural empyema.

Wan-Ju Liao, Hsi-Yu Lai, Liang-Yi Lin et al.

Aims: Frailty, a common and clinically significant condition in older adults with heart failure (HF), is often overlooked in emergency department (ED) settings. This study aims to evaluate the impact of frailty on clinical outcomes in older adults directly discharged from the ED due to HF. Methods and results: This retrospective cohort study used data from Taiwan's National Health Insurance (NHI) database, identifying older adults (≥65 years) discharged from the ED due to HF between 2017 and 2021. Frailty was assessed using a 38-item multimorbidity frailty index (mFI) derived from ICD-10-CM codes, stratifying patients into fit, mild-to-moderately frail, and severely frail. Outcomes included all-cause mortality, all-cause readmissions, and HF-related readmissions. Cox regression and Fine and Gray models estimated the impact of frailty on these outcomes. Among 42,989 older HF patients (mean age 80.7 ± 8.2 years, 55.5 % female), 57.8 % were frail (46.4 % mild-to-moderately frail and 11.4 % severely frail). Six-month mortality rates were 12.0 % in fit, 16.0 % in mild-to-moderately frail, and 19.4 % in severely frail patients. Readmission rates showed similar patterns. The severely frail group had higher risks of mortality (aHR 1.44, 95 % CI 1.33–1.55), all-cause readmissions (sHR 1.69, 95 % CI 1.62–1.76), and HF-related readmissions (sHR 1.59, 95 % CI 1.48–1.71). Conclusion: Frailty is prevalent among older adults directly discharged from the ED due to HF and significantly elevates risks of mortality and readmissions. These findings highlight the need for frailty assessment in ED settings for older HF patients to optimize care planning, and improve outcomes.

Fajri Koto

While knowledge evaluation in large language models has predominantly focused on academic subjects like math and physics, these assessments often fail to capture the practical demands of real-world professions. In this paper, we introduce IndoCareer, a dataset comprising 8,834 multiple-choice questions designed to evaluate performance in vocational and professional certification exams across various fields. With a focus on Indonesia, IndoCareer provides rich local contexts, spanning six key sectors: (1) healthcare, (2) insurance and finance, (3) creative and design, (4) tourism and hospitality, (5) education and training, and (6) law. Our comprehensive evaluation of 27 large language models shows that these models struggle particularly in fields with strong local contexts, such as insurance and finance. Additionally, while using the entire dataset, shuffling answer options generally maintains consistent evaluation results across models, but it introduces instability specifically in the insurance and finance sectors.

Zhang Yicheng

The pricing of insurance products has always occupied a central position in the insurance business and has long been an important focus of academic research. With the development of theory, the combination of option theory and game theory provides a new analytical perspective for insurance pricing. Specifically, insurance can be viewed as a kind of option so that the strategies in option game theory can be applied to determine a reasonable premium level. In this context, this study aims to explore in depth how option game theory can be applied to the insurance pricing problem. First, this paper defines insurance as a special form of option and tries to borrow the classical option pricing model, i.e., the Black-Scholes model, to explore the insurance pricing problem in this new perspective. The Black-Scholes model is an important tool in the field of option pricing, through which a reasonable insurance pricing approach can be derived. Secondly, this paper further introduces the concept of game theory and constructs a basic framework of games in insurance pricing. In this framework, the interaction between insurance companies and policyholders is regarded as a game process, and the decision-making behavior of both parties directly affects the price formation of insurance. Game theory provides a new theoretical basis for understanding the pricing mechanism in the insurance market. Finally, this paper focuses on the potential application of American put options in insurance pricing based on option game theory.

Kerstin Wolk, Kerstin Wolk, Maximilian Schielein et al.

BackgroundChronic inflammatory skin diseases (CISDs) are among the most common diseases in the Western world. Current estimates of medical care for CISDs are primarily based on surveys among patients in medical care facilities and on health insurance data.AimSurvey-based examination to what extent CISD patients in health-aware environment consider their skin disease to be controlled.MethodsThe survey of CISD patients was carried out in 2022 among the employees of a pharmaceutical company located in Germany and Switzerland. Software-based, anonymous, self-reported questionnaires were used.ResultsThe number of employees, who answered the questionnaire, was 905. Of these, 222 participants (24.5%) reported having at least one CISD. 28.7% of participants with CISD described their disease as being hardly or not controlled. Regarding the nature of disease, more than one third of participants suffering from hidradenitis suppurativa (HS) or psoriasis fell into the hardly/not controlled category. In contrast, the largest proportion of participants with chronic spontaneous urticaria (43%) or atopic dermatitis (42%) considered their CISD to be completely or well controlled. Only 35.5% of CISD sufferers stated that they were currently under medical care for their skin condition. Being under medical care, however, had no influence on the extent CISD sufferers considered their skin disease to be controlled. The number of active CISD episodes but not the total number of symptomatic days per year was negatively associated with poor disease control (p = 0.042 and p = 0.856, respectively). Poor disease control had a negative effect on the personal and professional lives of those affected, as deduced from its positive association with the extent of daily activity impairment and presenteeism (p = 0.005 and p = 0.005, respectively). Moreover, 41.4 and 20.7% of participants with hardly/not controlled disease stated that their CISD had a moderate and severe or very severe impact on their overall lives (p &lt; 0.001), respectively. A severe or very severe impact of their CISD on their overall life was most commonly reported by participants with HS.ConclusionMedical care for CISDs, even in an environment with high socio-economic standard and high health-awareness, still appears to be limited and has a negative impact on individuals and society.

Dave Gwun, Brennan Snow, Emery Potter et al.

Abstract Background Many studies have described barriers to gender-affirming surgery (GAS) in Canada; however, few have explored why these barriers persist. To address this knowledge gap, we sought to describe documents related to public health insurance (Medicare) for GAS to identify the types of procedures covered, variations in coverage across provinces and territories, and changes in policy over time. Methods We conducted a descriptive cross-sectional study using an environmental scan approach. We queried 23 government websites, the Google search engine, and an online legal database between July 2022 and April 2024 to gather gray literature documents related to GAS and Medicare. Variables from relevant documents were compiled to create a present, at-glance overview of GAS Medicare coverage for all provinces and territories and a timeline of policy changes across Canada.  Results Eight provinces and three territories had documents or websites related to GAS Medicare coverage (85%). We identified 15 GAS procedures that were covered variably across Canada. Yukon (n = 14) covered the most types of GAS, while Quebec and Saskatchewan covered the least (n = 6). Mastectomy and genital surgeries were covered across Canada, but other GAS were rarely covered. Five provinces and territories provided coverage for travel-related costs. Our GAS Medicare timeline showed differential expansion of GAS coverage in Canada over the last 25 years. Conclusions  We provide previously unreported information regarding GAS Medicare coverage in Canada. We hope our findings will help patients and healthcare providers navigate a complicated public healthcare system. We also highlight barriers within GAS Medicare documents and make recommendations to alleviate those barriers.

Allison J. Carroll, Delbert G. Robinson, Delbert G. Robinson et al.

IntroductionLong-acting injectable (LAI) antipsychotic medications and clozapine are effective yet underutilized medical therapies in early intervention services. The purpose of this study was to conduct a pre-implementation evaluation of contextual determinants of early intervention programs to implement innovations optimizing LAI antipsychotic and clozapine use within a shared decision-making model.MethodsSemi-structured interviews explored barriers and facilitators to implementing LAI antipsychotics and clozapine in early intervention services. Participants were: prescribers (n = 2), non-prescribing clinicians (n = 5), administrators (n = 3), clients (n = 3), and caregivers (n = 3). Interviews were structured and analyzed using the Consolidated Framework for Implementation Research (CFIR 2.0).ResultsParticipants were supportive of using LAI antipsychotics, despite barriers (e.g., transportation, insurance coverage), while most were unfamiliar with clozapine (Innovation). Critical incidents (e.g., COVID-19) did not interfere with implementation, while barriers included lack of performance measures; stigma affecting willingness to take medication; and clozapine considered to be a “last resort” (Outer Setting). Treatment culture was described as client-centered and collaborative, and most participants indicated LAI antipsychotic use was compatible with clinic workflows, but some were in need of resources (e.g., individuals trained to administer LAI antipsychotics; Inner Setting). Participants on the healthcare team expressed confidence in their roles. Family education and collaborative decision-making were recommended to improve client/family engagement (Individuals). Participants related the importance of tracking medication compliance, addressing client concerns, and providing prescribers with updated guidelines on evidence-based treatment (Implementation Process).DiscussionResults may guide implementation strategy selection for future programs seeking to optimize the use of LAI antipsychotics and clozapine for early-phase schizophrenia, when appropriate.

Min-Taek Lee, Moon Seong Baek, Tae Wan Kim et al.

Abstract Background Previous studies that assessed the risk of cardiovascular outcomes in survivors of coronavirus disease 2019 (COVID-19) were likely limited by lack of generalizability and selection of controls nonrepresentative of a counterfactual situation regarding COVID-19-related hospitalization. This study determined whether COVID-19 hospitalization was associated with incident cardiovascular outcomes compared to non-COVID-19 pneumonia hospitalization. Methods Nationwide population-based study conducted using the Korean National Health Insurance Service database. A cohort of 132,784 inpatients with COVID-19 (October 8, 2020–September 30, 2021) and a cohort of 31,173 inpatients with non-COVID-19 pneumonia (January 1–December 31, 2019) were included. The primary outcome was the major adverse cardiovascular event (MACE; a composite of myocardial infarction and stroke). Hazard ratios (HRs) with 95% confidence intervals (CIs) of all outcomes of interest were estimated between inverse probability of treatment-weighted patients with COVID-19 and non-COVID-19 pneumonia. Results After weighting, the COVID-19 and non-COVID-19 pneumonia groups included 125,810 (mean [SD] age, 47.2 [17.6] years; men, 49.3%) and 28,492 patients (mean [SD] age, 48.6 [18.4] years; men, 47.2%), respectively. COVID-19 hospitalization was not associated with an increased risk of the MACE (HR, 0.84; 95% CI 0.69–1.03). However, the MACE (HR, 7.30; 95% CI 3.29–16.21), dysrhythmia (HR, 1.88; 95% CI 1.04–3.42), acute myocarditis (HR, 11.33; 95% CI 2.97–43.20), myocardial infarction (HR, 6.78; 95% CI 3.03–15.15), congestive heart failure (HR, 1.95; 95% CI 1.37–2.77), and thrombotic disease (HR, 8.26; 95% CI 4.06–16.83) risks were significantly higher in patients with COVID-19 aged 18–39 years. The findings were consistent after adjustment for preexisting cardiovascular disease. COVID-19 hospitalization conferred a higher risk of acute myocarditis (HR, 6.47; 95% CI 2.53–16.52) or deep vein thrombosis (HR, 1.97; 95% CI 1.38–2.80), regardless of vaccination status. Conclusions Hospitalized patients with COVID-19 were not at an increased risk of cardiovascular outcomes compared to patients with non-COVID-19 pneumonia. Further studies are needed to evaluate whether the increased risk of cardiovascular outcomes is confined to younger patients.

Jiamin Yu

With the popularity of Telematics and Self-driving, more and more rating factors, such as mileage, route, driving behavior, etc., are introduced into actuarial models. There are quite a few doubts and disputes on the rationality and accuracy of the selection of rating variables, but it does not involve the widely accepted historical claim records. Recently, Tesla Insurance released a new generation of Safety Score-based insurance, irrespective of accident history. Forward-looking experts and scholars began to discuss whether claim history will disappear in the future auto insurance rate-making system. Therefore, this paper proposes a new risk variable elimination method as well as a real-time road risk model design framework and concludes that claim history will be regarded as a "noise" factor and deprecated in the Pay-How-You-Drive model.

Kerstin Awiszus, Yannick Bell, Jan Lüttringhaus et al.

Based on classical contagion models we introduce an artificial cyber lab: the digital twin of a complex cyber system in which possible cyber resilience measures may be implemented and tested. Using the lab, in numerical case studies, we identify two classes of measures to control systemic cyber risks: security- and topology-based interventions. We discuss the implications of our findings on selected real-world cybersecurity measures currently applied in the insurance and regulation practice or under discussion for future cyber risk control. To this end, we provide a brief overview of the current cybersecurity regulation and emphasize the role of insurance companies as private regulators. Moreover, from an insurance point of view, we provide first attempts to design systemic cyber risk obligations and to measure the systemic risk contribution of individual policyholders.

Desmond T. Jumbam, Emmanuella Amoako, Paa-Kwesi Blankson et al.

Background Conditions amenable to surgical, obstetric, trauma, and anaesthesia (SOTA) care are a major contributor to death and disability in Ghana. SOTA care is an essential component of a well-functioning health system, and better understanding of the state of SOTA care in Ghana is necessary to design policies to address gaps in SOTA care delivery. Objective The aim of this study is to assess the current situation of SOTA care in Ghana. Methods A situation analysis was conducted as a narrative review of published scientific literature. Information was extracted from studies according to five health system domains related to SOTA care: service delivery, workforce, infrastructure, finance, and information management. Results Ghanaians face numerous barriers to accessing quality SOTA care, primarily due to health system inadequacies. Over 77% of surgical operations performed in Ghana are essential procedures, most of which are performed at district-level hospitals that do not have consistent access to imaging and operative room fundamentals. Tertiary facilities have consistent access to these modalities but lack consistent access to oxygen and/or oxygen concentrators on-site as well as surgical supplies and anaesthetic medicines. Ghanaian patients cover up to 91% of direct SOTA costs out-of-pocket, while health insurance only covers up to 14% of the costs. The Ghanaian surgical system also faces severe workforce inadequacies especially in district-level facilities. Most specialty surgeons are concentrated in urban areas. Ghana’s health system lacks a solid information management foundation as it does not have centralized SOTA databases, leading to incomplete, poorly coded, and illegible patient information. Conclusion This review establishes that surgical services provided in Ghana are focused primarily on district-level facilities that lack adequate infrastructure and face workforce shortages, among other challenges. A comprehensive scale-up of Ghana’s surgical infrastructure, workforce, national insurance plan, and information systems is warranted to improve Ghana’s surgical system.

Feifei Cui, Yundan Jin, Haiying Wu et al.

ObjectiveBehavioral intentions to care for patients with infectious diseases are crucial for improving quality of care. However, there have been few studies of the behavioral intentions and factors influencing patient care by clinical nurses during the COVID-19 pandemic. This study aims to explore cognition, attitudes, subjective norms, self-efficacy, and behavioral intentions of clinical nurses while caring for COVID-19 patients and to explore any influencing factors.MethodA cross-sectional survey was conducted of nurses through convenience sampling in southeast China from February 2020 to March 2020. The questionnaire was developed based on the theory of planned behavior and self-efficacy.ResultsA total of 774 nurses completed the survey. Of these, 69.12% (535/774) reported positive behavioral intentions, 75.58% (585/774) reported a positive attitude, and 63.82% (494/774) reported having the confidence to care for patients. However, the lack of support from family and friends and special allowance affected their self-confidence. Attitude, self-efficacy, subjective norms, and ethical cognition were significantly positively correlated with behavioral intentions (r = 0.719, 0.690, 0.603, and 0.546, respectively, all P &lt; 0.001). Structural equation model showed that self-efficacy, attitude, ethical cognition, and subjective norms had positive effects on behavioral intentions (β = 0.402, 0.382, 0.091, and 0.066, respectively, P &lt; 0.01). The total effect of behavioral intentions was influenced by attitude, ethical cognition, self-efficacy, and subjective norms (β = 0.656, 0.630, 0.402, and 0.157, respectively, P &lt; 0.01). In addition, ethical cognition had a positive mediating effect on behavioral intentions (β = 0.539, P &lt; 0.001).ConclusionThe study results indicated that attitude, ethical cognition, and self-efficacy were the main factors influencing nurses' behavioral intention. Efforts should be made to improve nurses' attitude and self-efficacy through ethical education and training to increase behavioral intentions to care for patients with infectious diseases, which will improve the quality of nursing care.