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Children with rare cholestatic liver diseases, such as Alagille syndrome, progressive familial intrahepatic cholestasis, and biliary atresia typically require liver transplantation (LT). The objective of this analysis was to assess the economic burden of LT on these patients. Health care resource utilization and costs associated with pediatric LT were retrospectively assessed using insurance claims data from the US IBM MarketScan Commercial and Medicaid databases collected between October 2015 and December 2019. Inclusion criteria were as follows: ≥1 procedure code for LT, <18 years old at transplant, and ≥6 months of insurance eligibility at baseline. A cholestatic liver disease population who received LT was selected in the absence of specific diagnosis codes by excluding other severe liver conditions (ie, acute liver failure, malignancy) and by excluding severely decompensated individuals requiring ICU admission before LT. Annualized rates were reported. Over a mean study duration of 1.8 years, 53 commercially insured and 100 Medicaid-insured children received LT, with mean (SD) ages at baseline of 6.9 (6.0) and 5.7 (5.4) years, respectively. During this period, commercially insured and Medicaid-insured patients had annualized means of 65.3 and 52.8 medical visits, respectively. Most were outpatient visits, although the burden of inpatient visits was also high, with mean inpatient stays (inclusive of LT stay) of 37.2 and 31.6 days per year, respectively. Commercially insured and Medicaid-insured patients averaged US$512,124 and $211,863 in medical costs and $26,998 and $15,704 in pharmacy costs, respectively. These costs remained substantial throughout the first year after transplant. Overall, pediatric LT resulted in substantial health care resource utilization and cost burden in both commercially- and Medicaid-insured patients. Novel targeted medications that negate the need for pediatric LT could decrease the associated morbidity and costs.

BACKGROUND: National Comprehensive Cancer Network guideline adherence improves cancer outcomes. In rectal cancer, guideline adherence is distributed differently by race/ethnicity, socioeconomic status, and insurance. OBJECTIVE: This study aimed to determine the independent effects of race/ethnicity, socioeconomic status, and insurance status on rectal cancer survival after accounting for differences in guideline adherence. DESIGN: This was a retrospective study. SETTINGS: The study was conducted using the California Cancer Registry. PATIENTS: This study included patients aged 18 to 79 years diagnosed with rectal adenocarcinoma between January 1, 2004, and December 31, 2017, with follow-up through November 30, 2018. Investigators determined whether patients received guideline-adherent care. MAIN OUTCOME MEASURES: ORs and 95% CIs were used for logistic regression to analyze patients receiving guideline-adherent care. Disease-specific survival analysis was calculated using Cox regression models. RESULTS: A total of 30,118 patients were examined. Factors associated with higher odds of guideline adherence included Asian and Hispanic race/ethnicity, managed care insurance, and high socioeconomic status. Asians (HR, 0.80; 95% CI, 0.72-0.88; p < 0.001) and Hispanics (HR, 0.91; 95% CI, 0.83-0.99; p = 0.0279) had better disease-specific survival in the nonadherent group. Race/ethnicity were not factors associated with disease-specific survival in the guideline adherent group. Medicaid disease-specific survival was worse in both the nonadherent group (HR, 1.56; 95% CI, 1.40-1.73; p < 0.0001) and the guideline-adherent group (HR, 1.18; 95% CI, 1.08-1.30; p = 0.0005). Disease-specific survival of the lowest socioeconomic status was worse in both the nonadherent group (HR, 1.42; 95% CI, 1.27-1.59) and the guideline-adherent group (HR, 1.20; 95% CI, 1.08-1.34). LIMITATIONS: Limitations included unmeasured confounders and the retrospective nature of the review. CONCLUSIONS: R

Cleverea is a fully digital insurance company, established in 2019. The insurance technology industry in Spain is not very developed, so new problems arise daily that have yet to be solved. This project aims to model customer behavior of the company's clients in order to gain a better understanding of why customers make certain decisions and to implement measures that can increase profits. To achieve this, Markov chains will be used, which is a mathematical model that describes a system with different states and transitions., Cleverea es una empresa aseguradora totalmente digital fundada en 2019. El sector tecnológico de seguros en España está poco desarrollado, así que aparecen nuevos problemas a diario que todavía no se han resuelto. Este proyecto pretende abordar una manera para modelar el comportamiento de los clientes en esta empresa. De esta manera, se busca entender mejor por qué los clientes hacen ciertas decisiones y poder realizar medidas para incrementar los beneficios. Para ello se utilizarán principalmente las cadenas de Markov, un modelo matemático que sirve para describir un sistema con diferentes estados con transiciones.

Outline: Policy & Practice Transformation Paying for US healthcare - a brief history How does the way we pay for healthcare affect the way we practice? Value Based Care and looking ahead

Objective: To determine the impact of health insurance in the economy of Peruvian households during the 2010-2019 period. Material and Methods: This is a cross-sectional analytical study that used the database of the National Peruvian Household Surveys from years 2010, 2014, and 2019, aiming to analyze the impact of health insurance in terms of pocket money spending for health issues, catastrophic healthcare spending, and impoverishment in Peruvian households, and also to determine the presence of other associated factors. Results: During the study period, it was observed that Peruvian households reduced their monthly average pocket money spending for health issues (119.9 PEN in 2010 and 107.9 PEN in 2029), as well as the percentage of household with catastrophic healthcare expenses (4.06% in 2010 to 3.47% in 2019), and the percentage of households who became impoverished because of pocket money expenses for health issues (1.78% in 2020 to 1.51% in 2019). Factors associated to catastrophic healthcare expenses and to impoverishment were lower educational level for the household leader, the presence of family members with chronic diseases, and living in a rural area. The absence of health insurance was significantly associated to a greater risk for catastrophic healthcare expenses, but not to impoverishment. Conclusions:Increased healthcare insurance coverage contributes to financial protection of Peruvian households against pocket money spending for health issues; however, barriers for effective access to healthcare services, and other socioeconomical factors may significantly limit this impact., Objetivo: Determinar el impacto del aseguramiento en salud en la economía de los hogares peruanos en el periodo 2010-2019. Materiales y Métodos: Estudio analítico transversal, que utilizó la base de datos de la Encuesta Nacional de Hogares de los años 2010, 2014 y 2019 para analizar el impacto del aseguramiento en salud en términos de gasto de bolsillo en salud, gasto catastrófico y empobrecimiento de los hogares peruanos, así como determinar qué otros factores se encuentran asociados. Resultados: Durante el periodo de estudio se observó que los hogares peruanos presentaron una disminución del gasto de bolsillo en salud promedio mensual (S/.119,9 en 2010 a S/.107,9 en 2019), así como del porcentaje de hogares con gasto catastrófico en salud (4,06 % en 2010 a 3,47 % en 2019) y del porcentaje de hogares que empobrecen por gastos de bolsillo en salud (1,78 % en 2010 a 1,51 % en 2019). Los factores asociados al gasto catastrófico en salud y al empobrecimiento fueron el menor nivel de escolaridad del jefe del hogar, la presencia de miembros con enfermedad crónica y el área de residencia rural. La ausencia de aseguramiento en salud se asoció significativamente a un mayor riesgo de gasto de bolsillo en salud catastrófico, mas no al empobrecimiento. Conclusiones: El aumento de la cobertura de aseguramiento en salud contribuye a la protección financiera de los hogares peruanos frente al gasto de bolsillo en salud; sin embargo, las barreras para el acceso efectivo a los servicios de salud y otros factores socioeconómicos pueden limitar significativamente su impacto

Effective risk management is key to strengthening the resilience of the most vulnerable. Insurance products can help achieve this goal. Yet, in particular in low-income countries, not all can afford the regular premiums. Instead, informal risk-sharing within social networks plays a crucial role in protecting against unpredictable environmental shocks such as droughts and floods. However, this support may not reach households in need if income is heterogeneously distributed and poor households are not connected to those with sufficient resources to share. To study the determinants of vulnerability to extreme events when insurance is available but not affordable to all, we aggregate outcomes of an empirically informed agent-based model in a regression model. We show that not only a household's own financial situation is important for shock resilience, but also the household's position in the network and the financial situation of connected households. We demonstrate the transferability of our results by achieving high prediction accuracy for an empirical risk-sharing network of a village in the Philippines. The study demonstrates how model-based results can help detect vulnerable households. This can be used to develop a reliable identification tool to leverage external support and effectively target subsidies for different types of shocks.

The longstanding companionship between humans and pets, particularly cats and dogs, has evolved to the point where they are considered integral members of the family. However, despite their elevated status in our lives, the legal classi- fication of pets as objects remains prevalent in insurance law. There is a certain dichotomy between the objectification of pets and the strong animal protection system we have in Sweden, which places a particularly high value on animal welfare. Swedish law regulates animal cruelty, emphasizing both prevention and punishment. Furthermore, the Swedish Supreme Court recognizes the justifica- tion of receiving compensation exceeding an animal's economic value for its care, distinguishing pets from mere material possessions. In Sweden, we have a high rate of insured pets, and pet insurance policies differ significantly from other types of insurance. This divergence presents challenges for consumers in comprehending the coverage provided. With the insurance comes both terms and conditions that tell you what is and isn’t cov- ered by the insurance. The insurance has certain limitations, and for the set price you get just a certain amount of coverage. In recent years, rising veterinary costs have contributed to increased pet insurance premiums, leaving consumers with questions about pricing structures. The complexity of pricing extends to veterinary clinics offering advanced care and insurance companies responsible for covering these expenses. However, the absence of legal price limitations hampers transparency and hinders consumer understanding. Customers strug- gle to ascertain veterinary costs in advance and often question the reasons be- hind specific pet insurance prices, necessitating clearer communication from insurance providers regarding coverage and significant limitations. This study delves into the associated problems and proposes potential solu- tions. Despite improvements in clarity over the past decade, challenges persist

The adoption of the General Data Protection Regulation (GDPR) has resulted in a significant shift in how the data of European Union citizens is handled. A variety of data sharing challenges in scenarios such as smart cities have arisen, especially when attempting to semantically represent GDPR legal bases, such as consent, contracts and the data types and specific sources related to them. Most of the existing ontologies that model GDPR focus mainly on consent. In order to represent other GDPR bases, such as contracts, multiple ontologies need to be simultaneously reused and combined, which can result in inconsistent and conflicting knowledge representation. To address this challenge, we present the smashHitCore ontology. smashHitCore provides a unified and coherent model for both consent and contracts, as well as the sensor data and data processing associated with them. The ontology was developed in response to real-world sensor data sharing use cases in the insurance and smart city domains. The ontology has been successfully utilised to enable GDPR-complaint data sharing in a connected car for insurance use cases and in a city feedback system as part of a smart city use case.

A widely held view is that small firms in developing countries are prevented from making profitable investments by lack of access to credit and insurance markets. One solution is to provide repayment flexibility in credit contracts. Repayment flexibility eases both the credit constraint, as it allows for increased spending during the startup phase, and offers insurance, in case of fluctuations in income. In a field experiment among traditional microfinance clients and larger collateralized borrowers in Bangladesh, we randomly assign the option to delay up to 2 monthly repayments at any point during a 12-month loan cycle. The flexible contract leads to substantial improvements in the traditional microfinance clients’ business outcomes, driven by borrowers in the upper tail of the distribution. In addition, we find a significant impact on socioeconomic status, combined with lower default rates. We show theoretically and empirically that these effects are induced by an increase in entrepreneurial risk taking, implying that the primary mechanism is insurance provision. Repayment flexibility also attracts less risk-averse borrowers interested in business expansion. At the same time, the effects for the larger loan are much more modest. Our findings suggest that lack of insurance is an important constraint for small firms but that a simple financial product that increases repayment flexibility can be an effective tool for enabling enterprise growth.

This study has employed Bayesian Model Averaging (BMA) to identify the most suitable model for assessing the eligibility of Vietnamese coffee farmers for bank loans, effectively avoiding overfitting and ensuring that only the most crucial variables were considered in the analysis. Findings from the study indicate that factors such as ethnicity, labor, yield, land ownership, and willingness to participate (WTP) in coffee insurance significantly influenced the farmers' eligibility for bank loans. Moreover, the study suggests that banks and insurance companies should also take into account additional factors, such as socio-economic context, household size and composition, land ownership, and risk-sharing programs, to enhance access to credit. With this valuable information, banks can forge partnerships with insurance companies to craft highly effective loan programs and insurance products tailored to Vietnamese farmers' unique needs. The simplicity, practicality, and strong predictive ability of the model chosen by BMA make it a valuable tool for guiding policy decisions.

This study has employed Bayesian Model Averaging (BMA) to identify the most suitable model for assessing the eligibility of Vietnamese coffee farmers for bank loans, effectively avoiding overfitting and ensuring that only the most crucial variables were considered in the analysis. Findings from the study indicate that factors such as ethnicity, labor, yield, land ownership, and willingness to participate (WTP) in coffee insurance significantly influenced the farmers' eligibility for bank loans. Moreover, the study suggests that banks and insurance companies should also take into account additional factors, such as socio-economic context, household size and composition, land ownership, and risk-sharing programs, to enhance access to credit. With this valuable information, banks can forge partnerships with insurance companies to craft highly effective loan programs and insurance products tailored to Vietnamese farmers' unique needs. The simplicity, practicality, and strong predictive ability of the model chosen by BMA make it a valuable tool for guiding policy decisions.

İşletmelerin ortakları, yöneticileri, çalışanları ve müşterileri tarafından yapılan hileli işlemler nedeniyle işletme varlıklarının kötüye kullanımı söz konusu olmaktadır. Bu durum bir taraftan işletmelerin karlılığı üzerinde olumsuz etkiye sahipken diğer taraftan işletmelerin sürekliliği üzerinde de ciddi tehlike oluşturabilmektedir. Bu nedenlerden dolayı işletmelerde hilelerin tespit edilmesi, ekonomik değerinin hesaplanması ve hilenin oluşmasına zemin hazırlayan şartların ortadan kaldırılmasına yönelik bir sistemin geliştirilmesine ihitiyaç duyulmuştur. Bu ihtiyacı karşılayabilmek amacıyla muhasebenin alt bilim dalı olan "Adli Muhasebe" doğmuştur. Adli muhasebe, hile ve suistimal olaylarına ilişkin olarak hilelerin belirlenmesi, hileleri yapan kişi veya kişilerin belirlenmesi, hile tutarının belirlenmesi ve bunlara ilişkin olarak yapılan çalışmaların raporlanmasını sağlamaktadır. Adli muhasebe hizmeti temel olarak muhasebe, kriminal, psikoloji, tıp, hukuk ve diğer bilim dallarında bütünleşik bir şekilde bilgiye sahip olan uzmanlar tarafından yerine getirilmekte olup bu çerçevede adli muhasebe uzmanlarınca işletmelere, yargı mensuplarına, kolluk kuvvetlerine ve diğer hizmet alıcılarına "Uzman Tanıklık Desteği", "Dava Desteği" ve "Hile Denetçilik Desteği" hizmetleri sunulmaktadır. Bu çalışmanın amacı sigortacılık sektöründe meydana gelen hile ve usulsüzlüklerin tespitinde, ekonomik maliyetinin hesaplanması ve önlenmesinde sigorta hakemlerinin bakış açısıyla adli muhasebeye ihtiyaç olup olmadığının belirlenmesidir. Araştırma için ihtiyaç duyulan verilerin sağlanması amacıyla hazırlanan anket formu Sigorta Tahkim Komisyonu tarafından görevlendirilen "Hayat Dışı Sigorta Branşı"nda 242 hakem ve "Hayat Sigortası Branşı"nda görevli 15 hakem olmak üzere 259 hakeme internet ortamında gönderilmiştir. Elde edilen veriler SPSS 25.0 istatistik programı aracılığıyla analiz edilmiştir. Bulgular sigorta hileleri alt ölçeği ve adli muhasebe alt ölçeğine göre analiz edilmiştir. Ana, Misuse of business assets occurs due to fraudulent transactions by business partners, managers, employees and customers. On the one hand, this situation has a negative effect on the profitability of the enterprises, on the other hand, it can create a serious danger on the continuity of the enterprises. For these reasons, it was necessary to develop a system for detecting fraud in businesses, calculating their economic value, and eliminating the conditions that paved the way for fraud. In order to meet this need, "Forensic Accounting", a sub-discipline of accounting, was born. Forensic accounting provides for the identification of frauds, the identification of the person or persons who committed the fraud, the determination of the amount of fraud and the reporting of the studies carried out in relation to these incidents of fraud and abuse. Forensic accounting service is basically performed by experts who have integrated knowledge in accounting, criminal, psychology, medicine, law and other disciplines, "Litigation Support" and "Fraud Audit Support" services are offered. The aim of this study is to determine whether there is a need for forensic accounting from the point of view of insurance arbitrators in detecting fraud and irregularities in the insurance sector, calculating and preventing economic costs. The questionnaire, which was prepared to provide the data needed for the research, was sent to 259 arbitrators, 242 arbitrators in the "Non-Life Insurance Branch" and 15 arbitrators in the "Life Insurance Branch" assigned by the Insurance Arbitration Commission. The obtained data were analyzed using SPSS 25.0 statistical program. The data obtained was analyzed using the statistical program SPSS 25.0. The findings were analyzed according to the sub-scales of insurance fraud and forensic accounting. The analysis revealed that forensic accounting would be effective in preventing insurance fraud.

Annual report of the Utah Department of Insurance.

This annual report provides an informative look at the efforts, accomplishments, and challenges of the Utah Department of Insurance Fraud Division.

Climate change is a significant threat, and insurance can provide a significant impulse to provide systemic responses. While several normative frameworks for sustainable business models have been developed, it is still unclear what customers expect and how companies should actually act in their specific business environments. We investigated customer expectations in the context of Swiss retail insurance and found that less than a fifth of customers consider sustainability a very important factor in their next purchase decision, and that core customers in the 35–54 age range are comparatively less concerned about sustainability in general. Customers place most value on social rather than environmental issues. Insurers should improve their efforts in the core business, especially regarding sustainable claims handling, rather than regarding investment management or their own footprint. On the other hand, more than 40% of customers do not feel they know enough to have an opinion about their insurer’s efforts toward sustainability, and there were no significant differences in customer perceptions among the different insurers. These results should have profound implications for communication, business model development, and business transformation efforts for insurers. They also provide important missing detail about customer expectations regarding sustainability in the academic literature.

Purpose: The purpose of this study is to examine the differences in leadership styles prevalent in the public sector with those working in the banking and insurance industries. Cluster variables from both industries included in the analysis are as follows: Idealized influence, inspiring motivation, intellectual stimulation, and individualized consideration are all components of leadership. Theoretical Framework: Due to its apparent efficacy, transformational leadership has received a lot of attention from public sector researchers over the past decade. Successful leaders alter their teams by enlisting their followers' help in effecting change. A transformational leader is one who "transforms" their followers by inspiring them to make positive personal and professional shifts. Design / Methodology / Approach:The study is exploratory research design using Quantitative data collected from the Banking and Insurance sector employees. The study uses a well-structured questionnaire using Likert scale items. The sample was chosen on Convenience basis from 5 select public sector Insurance companies and 5 select public sector Insurance companies. 100 Questionnaires each were distributed and 97 valid responses were selected for banking industry and 90 responses from Insurance Industry were selected for the study. Paired t test using SPSS software was utilised for analysing the data in the study. Findings:The findings of the study show that there is significant difference between the leadership styles practices in Banking and Insurance industry. The banking sector employees showed a greater inclination towards transformational leadership with higher mean scores and statistically significant outcomes. Research Implications: Banking and insurance each have their own distinct cultures and management philosophies; as a result, they cannot be studied as a single entity under the umbrella of the BFSI sector. Additional research on the various leadership styles currently in us

Deciding if an online entity is trustworthy can be challenging. How do you decide if you can go into business with an unknown company, offering an enticing product? This thesis project aimed to enhance consumer trust in Insify, a starting business insurance company operating in a competitive market. The objective was to identify trust indicators and evaluate their impact on conversion rates, ultimately seeking ways to improve consumer trust. Insify is an InsurTech company aiming to simplify and digitize insurance processes. They offer disability, property & casualty, and health insurance directly to customers, targeting self-employed entrepreneurs and small to medium-sized enterprises. However, they face competition from established insurers and challenges associated with digitalization in a crowded market. In the e-commerce realm, building consumer trust is challenging but crucial. Early UX designers incorporated trust-building elements into online spaces. However, during the past decade, deceptive design practices emerged, complicating the trust-building process and increasing consumer skepticism towards the online provision of personal information. The project follows the Double Diamond design method, involving literature research, expert interviews, customer surveys, and A/B testing to redefine trust indicators and enhance the customer journey. In the final section of the design phase a strategic roadmap is presented, highlighting future opportunities for Insify. The research findings revealed that customers value personal contact and support. The customer survey indicated the significance of insurance premiums and coverage for business insurance customers. Trust-building was identified as a multifaceted process that extends beyond competence, integrity, and benevolence, indicating a need for a connected set of trust indicators throughout the customer journey. However, the research project faced limitations, suc, Strategic Product Design

BackgroundMen who have sex with men (MSM) have suboptimal uptake of human papillomavirus (HPV) and meningococcal vaccines. This study examines barriers and facilitators to HPV and meningococcal vaccination among MSM in a large, racially/ethnically diverse, and medically underserved U.S. region.MethodsIn 2020, we conducted five focus groups with MSM living in the Inland Empire, California. Participants discussed (1) their knowledge about and attitudes toward HPV, meningococcal disease, and related vaccines; and (2) factors that would encourage or discourage vaccine uptake. Data were systematically analyzed to identify salient barriers and facilitators to vaccination.ResultsParticipants (N = 25) had a median age of 29. Most were Hispanic (68%), self-identified as gay (84%), and had college degrees (64%). Key barriers to vaccination included: (1) limited awareness and knowledge about HPV and meningococcal disease, (2) reliance on mainstream healthcare providers for vaccine information, (3) stigma and reluctance to disclose sexual orientation, (4) uncertainty about health insurance coverage and vaccine costs, and (5) distance and time required to access vaccines. Key facilitators to vaccination were: (1) vaccine confidence, (2) perceived severity of HPV and meningococcal disease, (3) bundling vaccination into routine healthcare, and (4) pharmacies as vaccination sites.ConclusionsFindings highlight opportunities for HPV and meningococcal vaccine promotion, including targeted education and awareness campaigns for MSM, LGBT inclusivity training for healthcare providers, and structural interventions to improve vaccine accessibility.

BackgroundApproximately 5% of cancer patients in the United States presented with metastatic bone disease (MBD) at diagnosis. Current study explores the disparities in survival for patients with MBD.MethodsPatients with the diagnosis of MBD at presentation for the five most common primary anatomical sites were extracted from Surveillance, Epidemiology, and End Results Census tract-level dataset (2010-2016). Kaplan-Meier and Cox Proportional Hazard models were used to evaluate survival, and prognostic factors for each cohort. Prognostic significance of socioeconomic status (SES) and insurance status were ascertained.ResultsThe five most common anatomical-sites with MBD at presentation included "lung" (n = 59 739), "prostate" (n = 19 732), "breast" (n = 16 244), "renal and urothelium" (n = 7718) and "colon" (n= 3068). Lower SES was an independent risk factor for worse disease-specific survival (DSS) for patients with MBD originating from lung, prostate, breast and colon. Lack of insurance was an independent risk factor for worse DSS for MBD patients with primary tumors in lung and breast.ConclusionsMBD patients from the five most common primary sites demonstrated SES and insurance-related disparities in disease-specific survival. This is the first and largest study to explore SES and insurance-related disparities among patients specifically afflicted with MBD. Our findings highlight vulnerability of patients with MBD across multiple primary sites to financial toxicity.

BackgroundDepression is a common neuropsychiatric consequence of stroke, but there is little empiric evidence regarding clinical diagnosis and management of poststroke depression.MethodsRetrospective cohort study among 831 471 privately insured patients with first stroke in the USA from 2003 to 2020. We identified diagnoses of poststroke depression using codes from the International Classification of Diseases. We identified treatment based on prescriptions for antidepressants. We used Cox proportional hazards regression analysis to examine rates of poststroke depression diagnosis by gender, age and race/ethnicity. Among individuals who received a diagnosis of poststroke depression, we estimated treatment rates by gender, race/ethnicity and age using negative binomial regression analysis.ResultsAnnual diagnosis and treatment rates for poststroke depression increased from 2003 to 2020 (both p for trend<0.001). Diagnosis rates were higher in women than men (HR 1.53, 95% CI 1.51 to 1.55), lower among members of racial/ethnic minorities (vs white patients: Asian HR 0.63, 95% CI 0.60 to 0.66; Black HR 0.76, 95% CI 0.74 to 0.78; Hispanic HR 0.88, 95% CI 0.86 to 0.90) and varied by age. Among individuals diagnosed with poststroke depression, 69.8% were prescribed an antidepressant. Rates of treatment were higher in women vs men (rate ratio, RR=1.19, 95% CI: 1.17 to 1.21), lower among members of racial/ethnic minorities (vs white patients: Asian RR 0.85, 95% CI 0.80 to 0.90; Black RR 0.92, 95% CI 0.89 to 0.94; Hispanic RR 0.96, 95% CI 0.93 to 0.99) and higher among older patients.ConclusionsIn this insured population, we identify potential inequities in clinical management of poststroke depression by gender, race/ethnicity and age that may reflect barriers other than access to healthcare.

PurposeThe purpose of this report, commissioned by Teen Cancer America and performed by Deloitte Access Economics in 2021, was to estimate the total costs incurred by adolescent and young adults (AYAs) after cancer diagnosis in the United States (US) over their life course.MethodsThe incidence of cancer in 2019 among AYAs age 15-39 years was estimated from the US Cancer Statistics Public Use Database, and relative survival was projected from the Surveillance, Epidemiology, and End Results Program. Cost domains included health system, productivity, and well-being costs. Components were estimated with published literature and pooled data from the Medical Expenditure Panel Survey from 2008 to 2012 and inflated to 2019 dollars.ResultsThe economic and human costs of cancer in AYAs are substantial-$23.5 billion overall, corresponding to $259,324 per person over the lifetime. The majority of costs are borne by AYA cancer survivors themselves in the form of lost productivity, loss of well-being, and loss of life.ConclusionThese findings underscore the need to address the burden of cancer in AYAs through targeted programs for AYAs, such as financial navigation and health insurance literacy interventions, as well as local and national policy initiatives to address access to and enhanced coverage for clinical trials participation, fertility services, and survivorship care.

ObjectiveTo further elucidate the relationship between low socioeconomic status (SES) and larger, more complex stones requiring staged surgical interventions. Specifically, we aimed to determine if underinsurance (Medicaid, Medicare, and self-pay insurance types) is associated with multiple surgeries within 1 year.MethodsWe performed a retrospective longitudinal analysis of prospectively collected data from the California statewide Department of Health Care Access and Information (HCAI) dataset. We included adult patients who had their first recorded kidney stone encounter between 2009 and 2018 and underwent at least 1 urologic stone procedure. We followed these patients within the dataset for one year after their initial surgery to assess for factors predicting multiple surgical treatments for stones.ResultsA total of 156,319 adults were included in the study. The proportions of individuals in private insurance, Medicaid, Medicare and self-pay/indigent groups differed by the presence or absence of additional surgeries (64.0%, 13.5%, 19.4%, and 0.1%, vs 70.3%, 10.1%, 16.6%, and 0.1%, respectively). Compared to private insurance, Medicaid (1.46 [1.40-1.53] P < .001) and Medicare (1.15 [1.10-1.20] P < .001) insurance types were associated with significantly greater odds of multiple surgeries, whereas no significant association was seen in the self-pay/indigent insurance type (1.35 [0.83-2.19], P = 1.0).ConclusionIn a statewide, California database from 2009 to 2018, underinsured adults had higher odds of undergoing a second procedure for kidney stones within 1 year of initial surgical treatment. This study adds to the expanding body of literature linking suboptimal healthcare access and disparate outcomes for kidney stone patients.

The present study talked about educational leaders of our educational sectors. Emphasize was not only laid on their role but it also negotiated their impact towards character building of students and later, communal benefits. Little grain of learning had always made a beautiful land for practice for those learnt strategies i.e., security, alertness, progress, upgradation, growth, maturity and transformation. Role of educational leaders is about, how they motivated their sub-ordinates and transformed them altogether. Survey method was adopted through which data was gathered from the purposive sample of secondary level teachers (N=150), from the public/private schools, those belong to city Okara, all public/private school teachers as, population. For rationalization of researchable questions, construction of a questionnaire was made with large proportion having restricted response. Quantitively analyzed results presented significant difference on transformational growth of teachers from public and private schools. It was also observed that private schools had better setup for awarding incentives, upgradation, behavior, environment, security, insurance, motivation and instructional aids that had positive impact on the leadership as well helped student to be mindful.

This research identifies how it has been interpreted by the high courts the regime on precontractual non-disclosure and misrepresentation set in article 1058 of the Colombian Commercial Code has been interpreted. It shows that up to the first half of the 20th century the Courts tended to side with insurance companies by focusing on the insured’s precontractual disclosure duties, but that during the last decade a shift has occurred and novel interpretation that favor the insured’s position have become prevalent., Esta investigación identifica cómo ha sido interpretado por las altas cortes el artículo 1058 c.co. a la hora de resolver reclamaciones de seguros en las que las aseguradoras se niegan a pagar la indemnización por considerar que las tomadoras incumplieron con su deber precontractual de información. Se evidencia que las primeras interpretaciones favorecían la defensa planteada por las aseguradoras, pero que esta postura cambió al inclinarse las cortes por interpretaciones que privilegian a las demandantes, de tal forma que se tiende a mantener la validez del contrato de seguro y a condenar al pago de la indemnización.

Business cycle asymmetry of earnings pass-through How does the firm's role as an insurance provider vary over the business cycle? Using Swedish administrative data, I document that idiosyncratic firm productivity shocks are passed through workers' earnings asymmetrically. In non-recessions, firms are good insurers against negative shocks. In downturns, they pass through a larger share of their shock. Regardless of the state of the economy, instead, positive shocks are mainly passed through when sizeable. I rationalize these findings using a directed search model of the labor market with recursive contracts. Moral hazard risk associated with on-the-job search is key to generating pass-through and the increased risk of firm disaster in recessions is necessary for matching the empirical facts. As the wage growth distribution features procyclical skewness and acyclical variance, the model also suggests a new mechanism for explaining trends in income risk variation over the business cycle. Welfare calculations reveal that workers would be willing to give up a non-negligible share of consumption to avoid this source of uncertainty. Inferring income properties from portfolio choices Two main views exist on the nature of the labor income process: according to one, income shocks are very persistent and agents face similar life-cycle profiles - Restricted Income Profiles (RIP); according to the other, income shocks are not very persistent and life-cycle profiles are individual-specific - Heterogeneous Income Profiles (HIP). This paper studies the implications of these two views in a portfolio choice model in order to discover identification restrictions allowing to discern between them. I find that HIP and RIP imply different life-cycle patterns of the participation and conditional risky share choices but similar patterns of consumption and saving. Crucial for this result is the inclusion of cyclical skewness in the stochastic process for income, which enables us to correctly

The longstanding companionship between humans and pets, particularly cats and dogs, has evolved to the point where they are considered integral members of the family. However, despite their elevated status in our lives, the legal classi- fication of pets as objects remains prevalent in insurance law. There is a certain dichotomy between the objectification of pets and the strong animal protection system we have in Sweden, which places a particularly high value on animal welfare. Swedish law regulates animal cruelty, emphasizing both prevention and punishment. Furthermore, the Swedish Supreme Court recognizes the justifica- tion of receiving compensation exceeding an animal's economic value for its care, distinguishing pets from mere material possessions. In Sweden, we have a high rate of insured pets, and pet insurance policies differ significantly from other types of insurance. This divergence presents challenges for consumers in comprehending the coverage provided. With the insurance comes both terms and conditions that tell you what is and isn’t cov- ered by the insurance. The insurance has certain limitations, and for the set price you get just a certain amount of coverage. In recent years, rising veterinary costs have contributed to increased pet insurance premiums, leaving consumers with questions about pricing structures. The complexity of pricing extends to veterinary clinics offering advanced care and insurance companies responsible for covering these expenses. However, the absence of legal price limitations hampers transparency and hinders consumer understanding. Customers strug- gle to ascertain veterinary costs in advance and often question the reasons be- hind specific pet insurance prices, necessitating clearer communication from insurance providers regarding coverage and significant limitations. This study delves into the associated problems and proposes potential solu- tions. Despite improvements in clarity over the past decade, challenges persist

This thesis investigates Natural Language Processing (NLP) techniques to extract relevant information from long and unstructured insurance policy documents. The goal is to reduce the amount of time required by readers to understand the coverage within the documents. The study uses predefined insurance policy coverage parameters, created by industry experts to represent what is covered in the policy documents. Three NLP approaches are used to classify the text sequences as insurance parameter classes. The thesis shows that using SBERT to create vector representations of text to allow cosine similarity calculations is an effective approach. The top scoring sequences for each parameter are assigned that parameter class. This approach shows a significant reduction in the number of sequences required to read by a user but misclassifies some positive examples. To improve the model, the parameter definitions and training data were combined into a support set. Similarity scores were calculated between all sequences and the support sets for each parameter using different pooling strategies. This few-shot classification approach performed well for the use case, improving the model’s performance significantly. In conclusion, this thesis demonstrates that NLP techniques can be applied to help understand unstructured insurance policy documents. The model developed in this study can be used to extract important information and reduce the time needed to understand the contents of aninsurance policy document. A human expert would however still be required to interpret the extracted text. The balance between the amount of relevant information and the amount of text shown would depend on how many of the top-scoring sequences are classified for each parameter. This study also identifies some limitations of the approach depending on available data. Overall, this research provides insight into the potential implications of NLP techniques for information extraction and the insurance indu

The aim of this thesis consist of three parts. Firstly, the aim was to developan accurate historical inflation index suitable for the insurance business, usinginformation about insurance matters. The calculated inflation index was compared to an in-house benchmark at the insurance company Gjensidige, it wasfound to be a good match. Secondly, to determine the best model for explainingthe Swedish CPI inflation shocks, the thesis employed Multi Linear, RandomForest and XGBoost Regression. Thirdly, feature importance estimation wasconducted to identify which macroeconomic variables that were the most important in explaining inflation. Also, a time lag analysis was implemented tobetter understand with what delay these features best explain the inflation. Theresults revealed that Random Forest and Multi Linear Regression were the mostsuitable model candidates in terms of performance and transparency based onthe available dataset. Furthermore, the study found that unemployment rate,interest rate, and energy were the most crucial features in explaining inflation.It was also found that features with a low time lag entailed a high importance.The belief is that the study’s findings can assist insurance companies in developing a more agile product pricing process and sharpen their awareness towardsimportant macroeconomic variables. Overall, this study can be a valuable resource for insurance companies seeking to avoid underwriting risk and gain abetter understanding of the inflation’s underlying drivers.

Since its introduction by Max Otto Lorenz, the Lorenz curve has been utilizedin several financial contexts. By using regression analysis to approximate theclaim cost of policyholders, a vector consisting of policyholder characteristics canbe obtained. The ordered Lorenz curve can subsequently be used to understandwhat commonalities are shared between profitable policyholders. This allows forbetter management of the insurance portfolio and thus better customer relationstowards both the policyholders and the insurer, which is important for an insuranceconsultancy agency. The aim of this thesis was to investigate which attributesapproximate the policyholder claim costs and consequently obtain insight into whatattributes are shared among profitable portfolio clients. The results presented inthis thesis show that a multi-linear regression model, transformed using the Box-Cox method is insufficient to approximate the claim costs in a convincing manner.The model obtained in the thesis was capable of identifying significant regressorsbut the overall result displayed uncertainties in regards to overall goodness of fit.This means that the variability explained by the regression model only represents4.95% of the variability in the claim cost data. Thus, the relativity measureintroduced in section 2.1.1 was deemed uninterruptible in a meaningful way.Consequently, the empirical distribution functions presented in section 1.1 wouldbe based on a faulty order statistic, and in turn the visualization of an orderedLorenz curve with such a relativity measure is unnecessary., Sedan Lorenzkurvan introducerades av Max Otto Lorenz 1904 har den använtsinom flera finansiella sammanhang. Genom att använda regressionsanalys föratt approximera försäkringstagares skadekostnader kan en vektor som består avförsäkringstagarnas attribut erhållas. Den sorterade Lorenzkurvan kan i sin turanvändas för att förstå vilka gemensamma attribut som delas mellan lönsammaförsäkringstagare. Detta möjliggör bättre hantering av försäkringsportföljen ochdärmed bättre kundrelationer mot både försäkringstagarna och försäkringsbolaget,något som är viktigt för försäkringsförmedlare. Syftet med denna avhandling var attundersöka vilka egenskaper som approximerar försäkringstagarnas skadekostnaderoch därmed få insikt i vilka attribut som delas bland lönsamma portföljkunder.Resultaten som presenteras i denna avhandling visar att en multilinjär regressionsmodell,som transformeras med Box-Cox-metoden, är otillräcklig för att approximeraskadekostnader på ett övertygande sätt. Modellen som erhölls i avhandlingenkunde identifiera signifikanta regressorer, men det övergripande resultatet visadeosäkerheter när det gäller den generella anpassning. Detta innebär att variabilitetensom förklaras av regressionsmodellen bara representerar 4,95% av variabilitetenbland skadekostnadsdatan. Därmed ansågs relativitetsmåttet som introduceras iavsnitt 2.1.1 vara oanvändbart på ett meningsfullt sätt. Följaktligen ger de empiriskafördelningsfunktionerna som presenteras i avsnitt 1.1 ett felaktig sorteringsmåttsom i sin tur medför att visualiseringen av en sorterad Lorenzkurva baserad påovannämnda mått är onödigt.

Business cycle asymmetry of earnings pass-through How does the firm's role as an insurance provider vary over the business cycle? Using Swedish administrative data, I document that idiosyncratic firm productivity shocks are passed through workers' earnings asymmetrically. In non-recessions, firms are good insurers against negative shocks. In downturns, they pass through a larger share of their shock. Regardless of the state of the economy, instead, positive shocks are mainly passed through when sizeable. I rationalize these findings using a directed search model of the labor market with recursive contracts. Moral hazard risk associated with on-the-job search is key to generating pass-through and the increased risk of firm disaster in recessions is necessary for matching the empirical facts. As the wage growth distribution features procyclical skewness and acyclical variance, the model also suggests a new mechanism for explaining trends in income risk variation over the business cycle. Welfare calculations reveal that workers would be willing to give up a non-negligible share of consumption to avoid this source of uncertainty. Inferring income properties from portfolio choices Two main views exist on the nature of the labor income process: according to one, income shocks are very persistent and agents face similar life-cycle profiles - Restricted Income Profiles (RIP); according to the other, income shocks are not very persistent and life-cycle profiles are individual-specific - Heterogeneous Income Profiles (HIP). This paper studies the implications of these two views in a portfolio choice model in order to discover identification restrictions allowing to discern between them. I find that HIP and RIP imply different life-cycle patterns of the participation and conditional risky share choices but similar patterns of consumption and saving. Crucial for this result is the inclusion of cyclical skewness in the stochastic process for income, which enables us to correctly