Insurance participation, equity pledge and stock price crash risk: Evidence from China.

This paper analyzes the causes of equity pledge, external conduction mechanisms, and economic consequences from the perspective of insurance participation by integrating insurance participation, equity pledge, and stock price crash risk into a unified framework. An empirical analysis of sample data from listed companies in Shanghai and Shenzhen between 2007-2021, indicates that equity pledge reduces the risk of collapse as companies hedge the risk induced by the equity pledge. Further research has revealed that insurance participation can mitigate stock price crash risk brought by equity pledge through a regulatory effect, which is more pronounced for private companies and those with a high shareholding ratio, and companies in manufacturing industry. This is because private companies have a higher demand for capital as their property rights are not state-owned, the degree of separation of powers and agency conflicts is greater in companies held by large shareholders, manufacturing companies usually have stable earnings and cash flow performance, and the financial support provided by insurers for equity pledges at risk can effectively reduce the risk of their collapse.

Elicitation of security threats and vulnerabilities in Insurance chatbots using STRIDE.

Although chatbots are used a lot for customer relationship management (CRM), there needs to be more data security and privacy control strategies in chatbots, which has become a security concern for financial services institutions. Chatbots gain access to large amounts of vital company information and clients' personal information, which makes them a target of security attacks. The loss of data stored in chatbots can cause major harm to companies and customers. In this study, STRIDE (viz. Spoofing, Tampering, Repudiation, Information disclosure, Denial of service, Elevation of privilege) modelling was applied to identify the data security vulnerabilities and threats that pertain to chatbots used in the insurance industry. To do this, we conducted a case study of a South African insurance organisation. The adopted methodology involved data collection from stakeholders in the insurance organisation to identify chatbot use cases and understand chatbot operations. After that, we conducted a STRIDE-based analysis of the chatbot use cases to elicit security threats and vulnerabilities in the insurance chatbots in the organisation. The results reveal that security vulnerabilities associated with Spoofing, Denial of Service, and Elevation of privilege are more relevant to insurance chatbots. The most security threats stem from Tampering, Elevation of privilege, and Spoofing. The study extends the discussion on chatbot security. It fosters an understanding of security threats and vulnerabilities that pertain to insurance chatbots, which is beneficial for security researchers and practitioners working on the security of chatbots and the insurance industry.

Inequality in high-cost borrowing and unemployment insurance generosity in US states during the COVID-19 pandemic.

US consumers may turn to the private market for credit when income and government benefits fall short. The most vulnerable consumers have access only to the highest-cost loans. Prior research on trade-offs of credit with government welfare support cannot distinguish between distinct forms of unsecured credit due to data limitations. Here we provide insight on credit-welfare state trade-offs vis-à-vis unemployment insurance generosity by leveraging a large sample of credit data that allow us to separate credit cards, personal loans and alternative financial services loans and to analyse heterogeneity in credit use by household income. We find that more generous state unemployment insurance benefits were associated with a lower probability of high-cost credit use during the first seven quarters of the coronavirus disease 2019 (COVID-19) pandemic. This inverse association was concentrated among consumers living in low-income households. Our results support theories that public benefits are inversely associated with the use of costly credit.

Z-number network data envelopment analysis approach: A case study on the Iranian insurance industry.

The main aim of this research is to present an innovative method known as fuzzy network data envelopment analysis (FNDEA) in order to assess the performance of network decision-making units (DMUs) that possess a two-stage structure while taking into account the uncertainty of data. To attain this goal, we utilize various methodologies including the non-cooperative game (leader-follower) NDEA method, the concept of Z-number, credibility theory, and chance-constrained programming (CCP) to develop a model for the fuzzy NDEA approach. The FNDEA approach offers several advantages, such as the linearity of the presented FNDEA models, the ability to rank two-stage DMUs in situations of ambiguity, the provision of a unique efficiency decomposition method in an uncertain environment, and the capability to handle Z-information. To demonstrate the applicability and effectiveness of the proposed approach, we implement the Z-number network data envelopment analysis (ZNDEA) approach in assessing the performance of Iranian private insurance companies. The results of this implementation reveal that the proposed ZNDEA method is suitable and effective for measuring and ranking insurance companies in situations where data ambiguity is present.

Reducing delivery insurance costs through risk score model for food delivery company.

In this paper, we propose a novel pricing model for delivery insurance in a food delivery company in Latin America, with the aim of reducing the high costs associated with the premium paid to the insurer. To achieve this goal, a thorough analysis was conducted to estimate the probability of losses based on delivery routes, transportation modes, and delivery drivers' profiles. A large amount of data was collected and used as a database, and various statistical models and machine learning techniques were employed to construct a comprehensive risk profile and perform risk classification. Based on the risk classification and the estimated probability associated with it, a new pricing model for delivery insurance was developed using advanced mathematical algorithms and machine learning techniques. This new pricing model took into account the pattern of loss occurrence and high and low-risk behaviors, resulting in a significant reduction of insurance costs for both the contracting company and the insurer. The proposed pricing model also allowed for greater flexibility in insurance contracting, making it more accessible and appealing to delivery drivers. The use of estimated loss probabilities and a risk score for the pricing of delivery insurance proved to be a highly effective and efficient alternative for reducing the high costs associated with insurance, while also improving the profitability and competitiveness of the food delivery company in Latin America.

Economic burden of patients with post-surgical chronic and transient hypoparathyroidism in the United States examined using insurance claims data.

BACKGROUND: Hypoparathyroidism (HP) is a rare endocrine disease commonly caused by the removal or damage of parathyroid glands during surgery and resulting in transient (tHP) or chronic (cHP) disease. cHP is associated with multiple complications and comorbid conditions; however, the economic burden has not been well characterized. The objective of this study was to evaluate the healthcare resource utilization (HCRU) and costs associated with post-surgical cHP, using tHP as a reference. METHODS: This analysis of a US claims database included patients with both an insurance claim for HP and thyroid/neck surgery between October 2014 and December 2019. cHP was defined as an HP claim ≥ 6 months following surgery and tHP was defined as only one HP claim < 6 months following surgery. The cHP index date was the first HP diagnosis claim following their qualifying surgery claim, whereas the tHP index date was the last HP diagnosis claim following the qualifying surgery claim. Patients were continuously enrolled at least 1 year pre- and post-index. Patients' demographic and clinical characteristics, all-cause HCRU, and costs were descriptively analyzed. Total all-cause costs were calculated as the sum of payments for hospitalizations, emergency department, office/clinic visits, and pharmacy. RESULTS: A total of 1,406 cHP and 773 tHP patients met inclusion criteria. The average age (52.1 years cHP, 53.5 years tHP) and representation of females (83.2% cHP, 81.2% tHP) were similar for both groups. Neck dissection surgery was more prevalent in cHP patients (23.6%) than tHP patients (5.3%). During the 1-2 year follow-up period, cHP patients had a higher prevalence of inpatient admissions (17.4%), and emergency visits (26.0%) than the reference group -tHP patients (14.4% and 21.4% respectively). Among those with a hospitalization, the average number of hospitalizations was 1.5-fold higher for cHP patients. cHP patients also saw more specialists, including endocrinologists (28.7% cHP, 15.8% tHP), cardiologists (16.7% cHP, 9.7% tHP), and nephrologists (4.6% cHP, 3.3% tHP). CONCLUSION: This study demonstrates the increased healthcare burden of cHP on the healthcare system in contrast to patients with tHP. Effective treatment options are needed to minimize the additional resources utilized by patients whose HP becomes chronic.

Differences in Health Care Utilization for Asthma by Children with Medicaid versus Private Insurance.

Asthma is the most common chronic disease in children, disproportionately affects families with lower incomes, and is a leading reason for acute care visits and hospitalizations. This retrospective cohort study used the Massachusetts All Payer Claims Database (2014-2018) to examine differences in acute care utilization and quality of care for asthma between Medicaid- and privately insured children in Massachusetts. Outcomes included acute care use (emergency department [ED] or hospitalization), ED visits with asthma, routine asthma visits, and filled prescriptions for asthma medications. Multivariable logistic regression was used to account for differences in demographics, ZIP codes, health status, and asthma severity. Overall, 10.0% of Medicaid-insured children and 5.6% of privately insured were classified as having asthma. Among 317,596 child-year observations for children with asthma, 64.4% were insured by Medicaid. Medicaid-insured children had higher rates of any acute care use (50.4% vs. 30.0%) and ED visits with an asthma diagnosis (27.2% vs. 13.3%) compared to privately insured children. Only 65.4% of Medicaid enrollees had at least one routine asthma visit compared to 74.3% of privately insured children. Most children received at least one asthma medication (88.6% Medicaid vs. 83.3% privately insured), but a higher percentage of Medicaid-insured children received at least one rescue medication (84.0% vs. 73.7%), and a lower percentage of Medicaid-insured (46.1% vs. 49.2%) received a controller medication. These results suggest that opportunities for improvement in childhood asthma persist, particularly for children insured by Medicaid.

[Swiss healthcare system: a bulimic machine]. / Système de santé suisse : une machine boulimique.

Healthcare costs are a sensitive issue in Switzerland, in particular because of the financial burden of insurance premiums on households. The amount of resources allocated and their significant and regular increase seem to be out of control. But what do these costs really represent? How do we fuel our "machine" and what is the combustion mechanism behind it? At a time when debates are often very much focused on individual interests, this article attempts to answer these questions and to examine the sustainability of a health policy that focuses above all on illness and the cost of care.

Les coûts de la santé sont un sujet sensible en Suisse, notamment du fait du poids financier des primes d'assurance qui pèse sur les ménages. Le montant des ressources allouées et leur augmentation significative et régulière semble non maîtrisable. Mais que représentent réellement ces coûts ? Comment alimente-t-on notre « machine ¼ et quelle est la mécanique de combustion qui se cache derrière ? À l'heure où les débats sont souvent très orientés autour des intérêts de chacun, cet article tente de répondre à ces questions et interroge la durabilité d'une politique de santé focalisée avant tout sur la maladie et le coût des soins.

County medical community, medical insurance package payment, and hierarchical diagnosis and treatment-Empirical analysis of the impact of the pilot project of compact county medical communities in Sichuan Province.

Hierarchical diagnosis and treatment (HDT) is an important exploration direction to alleviate the rising pressure of health expenses and medical insurance fund expenditure in China, and to maintain and protect the public health in this country. In recent years, the construction of compact county medical communities (CCMC) has become the primary approach for implementing the HDT. Utilizing the quasi-natural experiment of the pilot project of CCMC in Sichuan Province in 2019, coupled with county-level data extracted from the ' Sichuan Provincial Health Statistics Yearbook ' spanning the years 2008 to 2021, this research evaluates the effect of the pilot project of CCMC on promoting HDT under the medical insurance package payment model. The results show that the pilot project of CCMC has significantly increased the number of consultations per capita of medical and health institutions in pilot counties by 0.434 times, of which the number of consultations per capita of primary medical institutions has increased by 0.340 times; the number of hospitalizations per capita in public hospitals and primary medical institutions in pilot counties increased significantly, and the surgery rate of inpatients in public hospitals increased by 5% compared to before the pilot. There was no significant impact on the allocation of medical facilities and human resources in the pilot counties. Therefore, the construction of CCMC under the medical insurance package payment mode has promoted the realization of the county-level HDT. These findings provide valuable insights for healthcare policy, especially in developing and implementing effective strategies for HDT in county-level medical institutions.

Androgen deprivation therapy-related fracture risk in prostate cancer: an insurance claims database study in Japan.

INTRODUCTION: Androgen deprivation therapy (ADT) is widely used for the treatment of prostate cancer. ADT is associated with reduced bone density leading to an increased risk of osteoporotic fracture. The objective of this retrospective cohort study was to quantify fracture risk in men treated with ADT for prostate cancer in real-world practice in Japan. MATERIALS AND METHODS: Data were extracted from the Japanese Medical Data Vision (MDV) database. Men initiating ADT for treatment of prostate cancer between April 2010 and March 2021 were identified and matched to a cohort of prostate cancer patients not taking ADT using a propensity score. Fracture rates were estimated by a cumulative incidence function and compared between cohorts using a Cox cause-specific hazard model. Information was extracted on demographics, comorbidities and bone densitometry. RESULTS: 30,561 men with PC starting ADT were matched to 30,561 men with prostate cancer not treated with ADT. Following ADT initiation, <5% of men underwent bone densitometry. Prescription of ADT was associated with an increased fracture risk compared to not taking ADT (adjusted hazard ratio: 1.63 [95% CI 1.52-1.75]). CONCLUSION: ADT is associated with a 1.6-fold increase in the risk of osteoporotic fracture in men with prostate cancer. Densitometry in this population is infrequent and monitoring urgently needs to be improved in order to implement effective fracture prevention.

A systematic review of the use of in-vehicle telematics in monitoring driving behaviours.

BACKGROUND: Road traffic deaths are increasing globally, and preventable driving behaviours are a significant cause of these deaths. In-vehicle telematics has been seen as technology that can improve driving behaviour. The technology has been adopted by many insurance companies to track the behaviours of their consumers. This systematic review presents a summary of the ways that in-vehicle telematics has been modelled and analysed. METHODOLOGY: Electronic searches were conducted on Scopus and Web of Science. Studies were only included if they had a sample size of 10 or more participants, collected their data over at least multiple days, and were published during or after 2010. 45 relevant papers were included in the review. 27 of these articles received a rating of "good" in the quality assessment. RESULTS: We found a divide in the literature regarding the use of in-vehicle telematics. Some articles were interested in the utility of in-vehicle telematics for insurance purposes, while others were interested in determining the influence that in-vehicle telematics has on driving behaviour. Machine learning analyses were the most common forms of analysis seen throughout the review, being especially common in articles with insurance-based outcomes. Acceleration, braking, and speed were the most common variables identified in the review. CONCLUSION: We recommend that future studies provide the demographical information of their sample so that the influence of in-vehicle telematics on the driving behaviours of different groups can be understood. It is also recommended that future studies use multi-level models to account for the hierarchical structure of the telematics data. This hierarchical structure refers to the individual trips for each driver.

Treatment setting and buprenorphine discontinuation: an analysis of multi-state insurance claims.

BACKGROUND: Potential differences in buprenorphine treatment outcomes across various treatment settings are poorly characterized in multi-state administrative data. We thus evaluated the association of opioid use disorder (OUD) treatment setting and insurance type with risk of buprenorphine discontinuation among commercial insurance and Medicaid enrollees initiated on buprenorphine. METHODS: In this observational, retrospective cohort study using the Merative MarketScan databases (2006-2016), we analyzed buprenorphine retention in 58,200 US adults with OUD. Predictor variables included insurance status (Medicaid vs commercial) and treatment setting, operationalized as substance use disorder (SUD) specialty treatment facility versus outpatient primary care physicians (PCPs) versus outpatient psychiatry, ascertained by linking physician visit codes to buprenorphine prescriptions. Treatment setting was inferred based on timing of prescriber visit claims preceding prescription fills. We estimated time to buprenorphine discontinuation using multivariable cox regression. RESULTS: Among enrollees with OUD receiving buprenorphine, 26,168 (45.0%) had prescriptions from SUD facilities without outpatient buprenorphine treatment, with the remaining treated by outpatient PCPs (n = 23,899, 41.1%) and psychiatrists (n = 8133, 13.9%). Overall, 50.6% and 73.3% discontinued treatment at 180 and 365 days respectively. Buprenorphine discontinuation was higher among enrollees receiving prescriptions from SUD facilities (aHR = 1.03[1.01-1.06]) and PCPs (aHR = 1.07[1.05-1.10]). Medicaid enrollees had lower buprenorphine retention than those with commercial insurance, particularly those receiving buprenorphine from SUD facilities and PCPs (aHR = 1.24[1.20-1.29] and aHR = 1.39[1.34-1.45] respectively, relative to comparator group of commercial insurance enrollees receiving buprenorphine from outpatient psychiatry). CONCLUSION: Buprenorphine discontinuation is high across outpatient PCP, psychiatry, and SUD treatment facility settings, with potentially lower treatment retention among Medicaid enrollees receiving care from SUD facilities and PCPs.

Inappropriate wrist MRI: did guidelines have an impact?

OBJECTIVES: To assess the national prevalence and cost of inappropriate MRI in patients with wrist pain prior to and following American College of Radiology (ACR) guideline publication. STUDY DESIGN: We used administrative claims from the IBM MarketScan Research Databases to evaluate the appropriateness of wrist MRI in a national cohort of patients with commercial insurance or Medicare Advantage. METHODS: Adult patients with a diagnosis of wrist pain between 2016 and 2019 were included and followed for 1 year. We made assessments of appropriateness based on ACR guidelines for specific wrist pain etiologies. We tabulated the total costs and out-of-pocket expenses associated with inappropriate MRI studies using weighted mean payments for facility and professional fees. We performed segmented logistic regression on interrupted time series data to identify predictors of receiving inappropriate imaging and the impact of guideline publication on MRI use. RESULTS: The study cohort consisted of 867,119 individuals. Of these, 40,164 individuals (4.6%) had MRI, of whom 52.6% received an inappropriate study. Inappropriate studies accounted for $44,493,234 in total payments and $8,307,540 in out-of-pocket expenses. The interrupted time series found an approximately 1% monthly decrease in the odds of receiving an inappropriate study after guideline dissemination. CONCLUSIONS: MRI as a diagnostic tool for wrist pain is often inappropriate and expensive. Our findings support interventions to increase guideline adherence, such as integrated clinical decision support tools.

Identification of high-risk beneficiaries in private healthcare insurance.

The objective of this study was to apply the Knowledge Discovery in Databases process to find out if beneficiaries of a private healthcare insurance would belong, at least once, to the 'very high cost' and 'complex cases' groups throughout the 12 months after the month when algorithms were applied. Datasets were built containing information on beneficiaries' effective use of their health plan, as well as their characteristics. Five machine learning algorithms were used, namely Random forest, Extra tree, Xgboost, Naive bayes and K-nearest neighbor. The K-nearest neighbor algorithm had a recall rate of 81.12%, 83.77% precision and an Area Under the Curve (AUC) value of 0.9045. The study also revealed that categorization occurs, on average, 8.11 months before a beneficiary entering, for the first time, a high-risk group, considering the dataset classification from January 2019 to June 2020.

Trends in HIV preexposure prophylaxis utilization and spending among individuals with commercial insurance.

In a cross-sectional analysis of HIV preexposure prophylaxis (PrEP) utilization by commercially insured patients from 2019 to 2021, most prescriptions were for branded formulations of PrEP despite the availability of a generic version. Accounting for the modest relative clinical benefit of branded TAF/FTC (tenofovir alafenamide fumarate/emtricitabine) PrEP over generic TDF/FTC (tenofovir disoproxil fumarate/emtricitabine) PrEP, use of generic TDF/FTC PrEP would have reduced commercial insurers' spending by 33%.

Has the Integrated Medical Insurance System promoted return-to-hometown entrepreneurship among migrant workers? Evidence from China.

An important way to reduce urban-rural disparity lies in encouraging migrant workers to return to their hometowns for entrepreneurship. This paper examines the effect of the Integrated Medical Insurance System on the return-to-hometown entrepreneurship among migrant workers. Using microdata from the China Household Finance Survey (CHFS) spanning from 2013 to 2019, we find that the Integrated Medical Insurance System (IMIS) significantly increases the likelihood of migrant workers returning to their hometowns for entrepreneurship by 0.44%. This result remains stable after a series of robustness checks. Heterogeneity results indicate that this "pullback effect" is more pronounced for those who are male and with lower educational levels, higher income, larger social networks, and lower risk preferences. Finally, the interaction between the Mass Entrepreneurship and Innovation policy (MEI) and IMIS can create a more significant combined effect in promoting the return of migrant workers to their hometowns for entrepreneurial activities.

Real-world biologic treatment patterns and healthcare resource utilization in psoriasis patients using an insurance claims database in Japan.

BACKGROUND: With advent of newer treatments for psoriasis, real-world use of biologics in Japan is evolving. METHODS: This retrospective study utilized data from patients with ≥1 psoriasis-related biologic claims record between January 2016 and December 2020 in Japan to evaluate treatment patterns, healthcare resource utilization (HCRU), and associated costs. Data were analyzed using descriptive statistics. RESULTS: Of 1,614 eligible patients, 72.5% were male, 29.2% had comorbid hypertension and 26.6% had comorbid cardiovascular disease. Interleukin (IL)-17 and tumor necrosis factor alpha (TNFα) inhibitors were commonly prescribed across lines of treatment, while IL-23 inhibitors were most considered for switches (92% of switches were from IL-12/23/IL-17/TNFα inhibitors). The overall mean adherence rate for all classes was 80.1%, but adherence varied across biologics. Infliximab and IL-23 inhibitor users exhibited optimal medical possession ratios, reflecting the best adherence rates. Overall HCRU (visits/patient-year) was 9.05 for outpatient visits, 0.09 for inpatient hospitalization, and 0.5 for psoriasis-related phototherapy. HCRU associated with hospitalization was slightly higher for bio-experienced patients and so was the overall costs per patient-year relative to bio-naïve patients. CONCLUSION: Variable adherence rates observed suggest the need for improvement in treatment management with different biologics. Bio-experienced patients burdened by disease progression and treatment switches may result in increased HCRU.

Impact of COVID-19 Infection on Health-Related Quality of Life in the Japanese Population: A Large Health-Insurance-Based Database Study.

Evidence for acute or long-term coronavirus disease 2019 (COVID-19) infection is relatively limited. We aimed to evaluate the impact of COVID-19 infection on health-related quality of life (HRQoL) in the Japanese population. Eligible study participants were 13,365 employees and their dependents who answered questionnaires at baseline and 18 months later and who had at least 6 months of continuous enrolment before and after baseline. Of the 711 study participants who developed COVID-19 infection, 29.0% reported a decline in HRQoL, whereas 25.2% of uninfected participants reported a decline. The adjusted odds ratios (95% confidence intervals) for the association between COVID-19 infection and declines in HRQoL in the age categories of less than 30 years, 30s, 40s, 50s, and 60 years or higher were 0.54 (0.15-1.92), 1.70 (1.03-2.81), 1.14 (0.82-1.57), 1.05 (0.77-1.42), and 0.87 (0.46-1.64), respectively. This study demonstrates a differential association between COVID-19 infection and declines in HRQoL by age group. A 1.7-fold increase in the odds of negative changes in HRQoL was observed in only those in their 30s. Further studies are needed to elucidate differences in the impact of COVID-19 infection on HRQoL between younger people such as those in their 30s and the older population.