Hasil untuk "Insurance"

Joyjit Roy, Samaresh Kumar Singh

Commercial insurance underwriting is a labor-intensive process that requires manual review of extensive documentation to assess risk and determine policy pricing. While AI offers substantial efficiency improvements, existing solutions lack comprehensive reasoning capabilities and internal mechanisms to ensure reliability within regulated, high-stakes environments. Full automation remains impractical and inadvisable in scenarios where human judgment and accountability are critical. This study presents a decision-negative, human-in-the-loop agentic system that incorporates an adversarial self-critique mechanism as a bounded safety architecture for regulated underwriting workflows. Within this system, a critic agent challenges the primary agent's conclusions prior to submitting recommendations to human reviewers. This internal system of checks and balances addresses a critical gap in AI safety for regulated workflows. Additionally, the research develops a formal taxonomy of failure modes to characterize potential errors by decision-negative agents. This taxonomy provides a structured framework for risk identification and risk management in high-stakes applications. Experimental evaluation using 500 expert-validated underwriting cases demonstrates that the adversarial critique mechanism reduces AI hallucination rates from 11.3% to 3.8% and increases decision accuracy from 92% to 96%. At the same time, the framework enforces strict human authority over all binding decisions by design. These findings indicate that adversarial self-critique supports safer AI deployment in regulated domains and offers a model for responsible integration where human oversight is indispensable.

Katia Colaneri, Federico D'Amario, Daniele Mancinelli

Given the increasing importance of environmental, social and governance (ESG) factors, particularly carbon emissions, we investigate optimal proportional portfolio insurance (PPI) strategies accounting for carbon footprint reduction. PPI strategies enable investors to mitigate downside risk while retaining the potential for upside gains. This paper aims to determine the multiplier of the PPI strategy to maximise the expected utility of the terminal cushion, where the terminal cushion is penalised proportionally to the realised volatility of stocks issued by firms operating in carbon-intensive sectors. We model the risky assets' dynamics using geometric Brownian motions whose drift rates are modulated by an unobservable common stochastic factor to capture market-specific or economy-wide state variables that are typically not directly observable. Using classical stochastic filtering theory, we formulate a suitable optimization problem and solve it for CRRA utility function. We characterise optimal carbon penalised PPI strategies and optimal value functions under full and partial information and quantify the loss of utility due incomplete information. Finally, we carry a numerical analysis showing that the proposed strategy reduces carbon emission intensity without compromising financial performance.

Yang-Fan Liu, Te-Li Chen, Jian-Wei Guo et al.

<i>Background and Objectives:</i> Diabetes mellitus (DM) significantly impacts post-surgical recovery and fracture healing; however, few studies have specifically investigated the impact of DM on outcomes in patients undergoing surgical stabilization of rib fractures (SSRF). This study investigated the potential influence of DM on perioperative outcomes following SSRF, using data from Taiwan’s National Health Insurance Research Database (NHIRD). <i>Materials and Methods:</i> Data of 1603 patients with multiple rib fractures who underwent SSRF between 2001 and 2019 were retrospectively analyzed. Patients were categorized into three groups: no DM, DM without chronic complications, and DM with chronic complications. The associations between DM status and perioperative outcomes, including hospital length of stay (LOS), in-hospital mortality, readmission rates, and complications such as pneumonia, surgical site infection (SSI), acute myocardial infarction (AMI), and total hospital costs were determined using univariate and multivariable regression analyses. <i>Results:</i> The mean age of the 1603 patients was 52.0 years, and 71% were male. Patients with DM and chronic complications had higher risks of 14-day readmission (adjusted odds ratio [aOR] = 2.99; 95% confidence interval [CI]: 1.18–7.62), 15–30 day readmission (aOR = 3.28; 95% CI: 1.25–8.60), SSI (aOR = 2.90; 95% CI: 1.37–6.14), AMI (aOR = 3.44; 95% CI: 1.28–9.24), and acute respiratory distress syndrome (ARDS) (aOR = 1.96; 95% CI: 1.03–3.74). In conclusion, DM, particularly DM with chronic complications, significantly increases the risk of adverse short-term outcomes following SSRF. <i>Conclusions:</i> These findings emphasize the need for enhanced care for patients with DM to optimize the outcomes of SSRF.

Jihwan Park

<b>Purpose</b>: Despite increasing rates of prostate cancer among men, prostate cancer risk assessments continue to rely on invasive laboratory tests like prostate-specific antigen and Gleason score tests. This study aimed to develop a noninvasive, data-driven risk model for patients to evaluate themselves before deciding whether to visit a hospital. <b>Materials and Methods</b>: To train the model, data from the National Health Insurance Sharing Service cohort datasets, comprising 347,575 individuals, including 1928 with malignant neoplasms of the prostate, 5 with malignant neoplasms of the penis, 18 with malignant neoplasms of the testis, and 14 with malignant neoplasms of the epididymis, were used. The risk model harnessed easily accessible inputs, such as history of treatment for diseases including stroke, heart disease, and cancer; height; weight; exercise days per week; and duration of smoking. An additional 286,727 public datasets were obtained from the National Health Insurance Sharing Service, which included 434 (0.15%) prostate cancer incidences. <b>Results</b>: The risk calculator was built based on Cox proportional hazards regression, and I validated the model by calibration using predictions and observations. The concordance index was 0.573. Additional calibration of the risk calculator was performed to ensure confidence in accuracy verification. Ultimately, the actual proof showed a sensitivity of 60 (60.5) for identifying a high-risk population. <b>Conclusions</b>: The feasibility of the model to evaluate prostate cancer risk without invasive tests was demonstrated using a public dataset. As a tool for individuals to use before hospital visits, this model could improve public health and reduce social expenses for medical treatment.

Panyi Dong, Zhiyu Quan, Brandon Edwards et al.

The report demonstrates the benefits (in terms of improved claims loss modeling) of harnessing the value of Federated Learning (FL) to learn a single model across multiple insurance industry datasets without requiring the datasets themselves to be shared from one company to another. The application of FL addresses two of the most pressing concerns: limited data volume and data variety, which are caused by privacy concerns, the rarity of claim events, the lack of informative rating factors, etc.. During each round of FL, collaborators compute improvements on the model using their local private data, and these insights are combined to update a global model. Such aggregation of insights allows for an increase to the effectiveness in forecasting claims losses compared to models individually trained at each collaborator. Critically, this approach enables machine learning collaboration without the need for raw data to leave the compute infrastructure of each respective data owner. Additionally, the open-source framework, OpenFL, that is used in our experiments is designed so that it can be run using confidential computing as well as with additional algorithmic protections against leakage of information via the shared model updates. In such a way, FL is implemented as a privacy-enhancing collaborative learning technique that addresses the challenges posed by the sensitivity and privacy of data in traditional machine learning solutions. This paper's application of FL can also be expanded to other areas including fraud detection, catastrophe modeling, etc., that have a similar need to incorporate data privacy into machine learning collaborations. Our framework and empirical results provide a foundation for future collaborations among insurers, regulators, academic researchers, and InsurTech experts.

Islam Abdeljawad, Mamunur Rashid, Muiz Abu Alia et al.

Conventional banks are 'indirectly' allowed to take more risk under the shadow of sovereign guarantees. Banks commit moral hazards as any major banking crisis will be 'cushioned' by deposit insurance and bailed out using the taxpayer's money. This study offers an alternative explanation for the determinants of banks' credit risk, particularly those from the Islamic regions. Although conventional banks and Islamic banks may share state and social cushioning systems, Islamic banks are strictly prohibited by moral and religious principles from gambling with depositors' funds, even if there is a cushion available to bail them out. However, banks belonging to collective societies, such as those in the MENA area, may be inclined to take more risks due to the perception of having a larger safety net to protect them in the event of failure. We analyse these theoretical intersections by utilising a dataset consisting of 320 banks from 20 countries, covering the time span from 2006 to 2021. Our analysis employs a combination of Ordinary Least Squares (OLS), Fixed Effects (FE), and 2-step System-GMM methodologies. Our analysis reveals that Islamic banks are less exposed to credit risk compared to conventional banks. We contend that the stricter ethical and moral ground and multi-layer monitoring system amid protracted geopolitical and post-pandemic crises impacting Islamic countries contribute to the lower credit risk. We examine the consequences for credit and liquidity management in Islamic banks and the risk management strategies employed by Islamic banks, which can serve as a valuable reference for other banks.

Kendra L. Ratnapradipa, Tingting Li, Mei-Chin Hsieh et al.

BackgroundLiver cancer incidence increased in the US from 1975 through 2015 with heterogeneous rates across subpopulations. Upstream or distal area-level factors impact liver cancer risks.ObjectiveThe aim of this study was to examine the association between area-level deprivation and hepatocellular carcinoma (HCC) incidence and survival. We also explored the association between area deprivation and treatment modalities.MethodsLouisiana Tumor Registry identified 4,151 adult patients diagnosed with malignant HCC from 2011 to 2020 and linked residential address to census tract (CT)-level Area Deprivation Index (ADI) categorized into quartiles (Q1 = least deprived). ANOVA examined the association between ADI quartile and CT age-adjusted incidence rate (AAIR) per 100,000. Chi-square tested the distribution of demographic and clinical characteristics across ADI quartiles. Kaplan–Meier and proportional hazard models evaluated survival by deprivation quartile.ResultsAmong the 1,084 CTs with incident HCC, the average (SD) AAIR was 8.02 (7.05) HCC cases per 100,000 population. ADI was observed to be associated with incidence, and the mean (SD) AAIR increased from 5.80 (4.75) in Q1 to 9.26 (7.88) in Q4. ADI was also associated with receipt of surgery (p &lt; 0.01) and radiation (p &lt; 0.01) but not chemotherapy (p = 0.15). However, among those who received chemotherapy, people living in the least deprived areas began treatment approximately 10 days sooner than those living in other quartiles. Q4 patients experienced the worst survival with a median of 247 (95% CI 211–290) days vs. Q1 patients with a median of 474 (95% CI 407–547) days (p &lt; 0.0001). Q4 had marginally poorer survival (HR 1.20, 1.05–1.37) than Q1 but the association became non-significant (HR 1.12, 0.96–1.30) when adjusted for rurality, liquor store density, sex, race/ethnicity, age, insurance, BMI, stage, hepatitis diagnosis, and comorbidities.ConclusionIncreasing neighborhood (CT) deprivation (ADI) was observed to be associated with increased HCC incidence and poorer HCC survival. However, the association with poorer survival becomes attenuated after adjusting for putative confounders.

Zoltán Kiss, Zoltán Kiss, Tamás G. Szabó et al.

BackgroundThe nationwide HUN-CANCER EPI study examined cancer incidence and mortality rates in Hungary from 2011 to 2019.MethodsUsing data from the National Health Insurance Fund (NHIF) and Hungarian Central Statistical Office (HCSO), our retrospective study analyzed newly diagnosed malignancies between Jan 1, 2011, and Dec 31, 2019. Age-standardized incidence and mortality rates were calculated for all and for different tumor types using both the 1976 and 2013 European Standard Populations (ESP).FindingsThe number of newly diagnosed cancer cases decreased from 60,554 to 56,675 between 2011–2019. Age-standardized incidence rates were much lower in 2018, than previously estimated (475.5 vs. 580.5/100,000 person-years [PYs] in males and 383.6 vs. 438.5/100,000 PYs in females; ESP 1976). All-site cancer incidence showed a mean annual decrease of 1.9% (95% CI: 2.4%-1.4%) in men and 1.0% (95% CI:1.42%-0.66%) in women, parallel to mortality trends (-1.6% in males and -0.6% in females; ESP 2013). In 2018, the highest age-standardized incidence rates were found for lung (88.3), colorectal (82.2), and prostate cancer (62.3) in men, and breast (104.6), lung (47.7), and colorectal cancer (45.8) in women. The most significant decreases in incidence rates were observed for stomach (4.7%), laryngeal (4.4%), and gallbladder cancers (3.5%), with parallel decreases in mortality rates (3.9%, 2.7% and 3.2%, respectively).InterpretationWe found a lower incidence of newly diagnosed cancer cases for Hungary compared to previous estimates, and decreasing trends in cancer incidence and mortality, in line with global findings and the declining prevalence of smoking.

Rich Ryan

Unemployment insurance provides temporary cash benefits to eligible unemployed workers. Benefits are sometimes extended by discretion during economic slumps. In a model that features temporary benefits and sequential job opportunities, a worker's reservation wages are studied when policymakers can make discretionary extensions to benefits. A worker's optimal labor-supply choice is characterized by a sequence of reservation wages that increases with weeks of remaining benefits. The possibility of an extension raises the entire sequence of reservation wages, meaning a worker is more selective when accepting job offers throughout their spell of unemployment. The welfare consequences of misperceiving the probability and length of an extension are investigated. Properties of the model can help policymakers interpret data on reservation wages, which may be important if extended benefits are used more often in response to economic slumps, virus pandemics, extreme heat, and natural disasters.

Jonelle Angelo S. Cenita, Paul Richie F. Asuncion, Jayson M. Victoriano

The study aimed to evaluate the regression models' performance in predicting the cost of medical insurance. The Three (3) Regression Models in Machine Learning namely Linear Regression, Gradient Boosting, and Support Vector Machine were used. The performance will be evaluated using the metrics RMSE (Root Mean Square), r2 (R Square), and K-Fold Cross-validation. The study also sought to pinpoint the feature that would be most important in predicting the cost of medical insurance.The study is anchored on the knowledge discovery in databases (KDD) process. (KDD) process refers to the overall process of discovering useful knowledge from data. It show the performance evaluation results reveal that among the three (3) Regression models, Gradient boosting received the highest r2 (R Square) 0.892 and the lowest RMSE (Root Mean Square) 1336.594. Furthermore, the 10-Fold Cross-validation weighted mean findings are not significantly different from the r2 (R Square) results of the three (3) regression models. In addition, Exploratory Data Analysis (EDA) using a box plot of descriptive statistics observed that in the charges and smoker features the median of one group lies outside of the box of the other group, so there is a difference between the two groups. It concludes that Gradient boosting appears to perform better among the three (3) regression models. K-Fold Cross-Validation concluded that the three (3) regression models are good. Moreover, Exploratory Data Analysis (EDA) using a box plot of descriptive statistics ceases that the highest charges are due to the smoker feature.

Won Seok Lee, Jae Kyoon Hwang, Jiin Ryu et al.

PurposeThis study aimed to investigate associations of socioeconomic status (SES) with asthma exacerbation and asthma-related hospital utilization factors among children with asthma in the Republic of Korea.MethodsThis study retrospectively analyzed population-level data from the Korean National Health Insurance Service, collected from 2013 through 2019. SES was classified into five categories according to the national health insurance premiums quantiles (0 [lowest] to 4 [highest]). The hazard ratios (HRs) for asthma exacerbation, emergency department (ED) visits, hospital admission, and intensive care unit (ICU) admission were analyzed with respect to SES.ResultsAmong the five SES groups, SES group 0 (medical aid), had the highest tallies and proportions of children who experienced asthma exacerbations (n = 1,682, 4.8%), ED visits (n = 932, 2.6%), hospital admission (n = 2,734, 7.7%) and ICU admission (n = 14, 0.04%). Compared with SES group 4, SES group 0 had adjusted HRs of 3.73 (p = 0.0113) and 1.04 (p &lt; 0.0001) for ventilator support/tracheal intubation and administration of systemic corticosteroids, respectively. Relative to group 4, the adjusted HRs for ED visits, hospital admission, and ICU admission in group 0 were 1.88 (p &lt; 0.0001), 2.20 (p &lt; 0.0001), and 7.12 (p &lt; 0.0001), respectively. In the survival analysis, group 0 had a significantly higher risk of ED presentation, hospital admission, and ICU admission than the other groups (log-rank p &lt; 0.001).ConclusionCompared with children of higher SES, those in the lowest SES group had increased risk of asthma exacerbation, hospital admission, and receiving treatment for severe asthma symptoms.

Jacelle Warren, Kirsten Vallmuur, Victoria McCreanor et al.

Introduction In many jurisdictions, people experiencing an injury often pursue compensation to support their treatment and recovery expenses. Healthcare costs form a significant portion of payments made by compensation schemes. Compensation scheme regulators need accurate and comprehensive data on injury severity, treatment pathways and outcomes to enable scheme modelling, monitoring and forecasting. Regulators routinely rely on data provided by insurers which have limited healthcare information. Health data provide richer information and linking health data with compensation data enables the comparison of profiles, patterns, trends and outcomes of injured patients who claim and injured parties who are eligible but do not claim.Methods and analysis This is a retrospective population-level epidemiological data linkage study of people who have sought ambulatory, emergency or hospital treatment and/or made a compensation claim in Queensland after suffering a transport or work-related injury, over the period 1 January 2011 to 31 December 2021. It will use person-linked data from nine statewide data sources: (1) Queensland Ambulance Service, (2) Emergency Department, (3) Queensland Hospital Admitted Patients, (4) Retrieval Services, (5) Hospital Costs, (6) Workers’ Compensation, (7) Compulsory Third Party Compensation, (8) National Injury Insurance Scheme and (9) Queensland Deaths Registry. Descriptive, parametric and non-parametric statistical methods and geospatial analysis techniques will be used to answer the core research questions regarding the patient’s health service use profile, costs, treatment pathways and outcomes within 2 years postincident as well as to examine the concordance and accuracy of information across health and compensation databases.Ethics and dissemination Ethics approval was obtained from the Royal Brisbane and Women’s Hospital Human Research Ethics Committee, and governance approval was obtained via the Public Health Act 2005, Queensland. The findings of this study will be used to inform key stakeholders across the clinical, research and compensation regulation area, and results will be disseminated through peer-reviewed journals, conference presentations and reports/seminars with key stakeholders.

Myunhee Lee, Yu Ah Hong, Jun-Pyo Myong et al.

<h4>Background</h4>Although statins are an effective strategy for the secondary prevention of atherosclerotic cardiovascular disease (ASCVD) in the general population, the benefits for dialysis patients are controversial. We sought to assess trends of statin use and evaluate outcomes of statin therapy in dialysis patients with different types of ASCVD.<h4>Methods</h4>This nationwide retrospective population-based cohort study using data from the Korean National Health Insurance Service included adult patients (aged ≥ 18 years) undergoing chronic dialysis who had an initial ASCVD event in the time period of 2013 to 2018. Annual trends of statin use according to age, sex, and ASCVD types were analyzed. The association between 1-year mortality and statin use was examined using multivariable Cox proportional hazards regression analyses.<h4>Results</h4>Among 17,242 subjects, 9,611(55.7%) patients were statin users. The overall prevalence of statin use increased from 52.9% in 2013 to 57.7% in 2018; the majority (77%) of dialysis patients were prescribed moderate-intensity statins. The proportions of low- or moderate-intensity statin use were similar, but high-intensity statin use increased from 5.7% in 2013 to 10.5% in 2018. The use of the statin/ezetimibe combination has gradually increased since 2016. Statin use was independently associated with the reduced 1-year all-cause mortality after adjusting for confounding factors (hazard ratio [HR] 0.89, 95% confidence interval [CI] 0.80-0.96, P = 0.004).<h4>Conclusion</h4>The prevalence of statin prescriptions in dialysis patients after ASCVD event increased from 2013 to 2018. Most patients received moderate-intensity statin. However, high-intensity statin and statin/ezetimibe combination therapy has remarkably increased. Statin use was associated with decreased 1-year all-cause mortality in dialysis patients with ASCVD.

Rhea Davis, Nicy Sebastian

Statistical Physics, Diffusion Entropy Analysis and Information Theory commonly use Mathai's entropy which measures the randomness of probability laws, whereas welfare economics and the Social Sciences commonly use Gini index which measures the evenness of probability laws. Motivated by the principle of maximal entropy, we explore the maximization of Mathai's entropy subject to the conditions in the following scenarios: (i) the conditions of a density function and fixed mean; (ii) the conditions of a density function and fixed Generalized Gini index. We also maximizes the Mathai's entropy subject to the constraints of a given Gini mean difference index and the conditions of a density function. The obtained maximum entropy distribution is fitted to the loss ratios (yearly data) for earthquake insurance in California from 1971 through 1994 and its performance with some one-parameter distributions are compared.

Mathias Lindholm, Ronald Richman, Andreas Tsanakas et al.

In applications of predictive modeling, such as insurance pricing, indirect or proxy discrimination is an issue of major concern. Namely, there exists the possibility that protected policyholder characteristics are implicitly inferred from non-protected ones by predictive models, and are thus having an undesirable (or illegal) impact on prices. A technical solution to this problem relies on building a best-estimate model using all policyholder characteristics (including protected ones) and then averaging out the protected characteristics for calculating individual prices. However, such approaches require full knowledge of policyholders' protected characteristics, which may in itself be problematic. Here, we address this issue by using a multi-task neural network architecture for claim predictions, which can be trained using only partial information on protected characteristics, and it produces prices that are free from proxy discrimination. We demonstrate the use of the proposed model and we find that its predictive accuracy is comparable to a conventional feedforward neural network (on full information). However, this multi-task network has clearly superior performance in the case of partially missing policyholder information.

Francetic Igor

Selection on moral hazard represents the tendency to select a specific health insurance coverage depending on the heterogeneity in utilisation ''slopes''. I use data from the Swiss Household Panel and from publicly available regulatory data to explore the extent of selection on slopes in the Swiss managed competition system. I estimate responses in terms of (log) doctor visits to lowest and highest deductible levels using Roy-type models, identifying marginal treatment effects with local instrumental variables. The response to high coverage plans (i.e. plans with the lowest deductible level) among high moral hazard types is 25-35 percent higher than average.

Hind Mrabti, Catherine Sauvaget, Abdellatif Benider et al.

Guided by a national cancer plan (2010–19), Morocco made significant investments in improving breast cancer detection and treatment. A breast cancer pattern-of-care study was conducted to document the socio-demographic profiles of patients and tumour characteristics, measure delays in care, and assess the status of dissemination and impact of state-of-the-art management. The retrospective study conducted among 2120 breast cancer patients registered during 2008–17 at the two premier-most oncology centres (Centre Mohammed VI or CM-VI and Institut National d’Oncologie or INO) also measured temporal trends of the different variables.Median age (49 years) and other socio-demographic characteristics of the patients remained constant over time. A significant improvement in coverage of the state-financed health insurance scheme for indigent populations was observed over time. Median interval between onset of symptoms and first medical consultation was 6 months with a significant reduction over time. Information on staging and molecular profile were available for more than 90% and 80% of the patients respectively. Approximately 55% of the patients presented at stage I/II and proportion of triple-negative cancers was 16%; neither showing any appreciable temporal variation. Treatment information was available for more than 90% of the patients; 69% received surgery with chemotherapy and/or radiation. Treatment was tailored to stage and molecular profiles, though breast conservation therapy was offered to less than one-fifth. When compared using the EUSOMA quality indicators for breast cancer management, INO performed better than CM-VI. This was reflected in nearly 25% difference in 5-year disease-free survival for early-stage cancers between the centres.

Vahideh MoghaddamHosseini, Monika Gyuró, Alexandra Makai et al.

Background: Assessing prenatal health-related quality of life (HRQoL) by parity using a comprehensive consistent instrument with the transient nature of pregnancy is still under investigation. Objective: To assess HRQoL and specify its predictors among expectant women in Hungary through Patient Reported Outcomes Measurement Information System (PROMIS-43). Method: s: 477 healthy pregnant women were asked to fill the Hungarian version of PROMIS-43 and further instruments in late pregnancy.The PROMIS-43 investigates seven parameters, including anxiety, ability to participate in social roles and activities, depression, fatigue, sleep disturbance, physical function, and pain interference. Results: While physical function and fatigue subscales obtained the highest proportion in the mild and moderate range, respectively, other subscales were felled into the normal range in all participants. A comparison of parity showed that the mean T-score of subscale “Anxiety” was significantly higher in nulliparous than that of in multiparous women (p = 0.02). The assessments indicated that the predictors, including parity, anxiety, and depression were the most common predictors for the poor HRQoL domains in both the nulliparous and multiparous women. In nulliparous, social support was a significant predictor for better HRQoL in depression, fatigue, and pain intensity domains. In multiparous, the strongest predictors included social support for lower depression, wanted pregnancy for lower pain intensity, and previous emergency cesarean section for higher pain intensity subscale. Conclusion: The results of PROMIS-43 support the fact that the screening and continuous assessment of physical function and psychological status at early and over pregnancy is still on demand to optimize the outcomes of maternity care.

Benjamin Avanzi, Gregory Clive Taylor, Melantha Wang et al.

Recent years have seen rapid increase in the application of machine learning to insurance loss reserving. They yield most value when applied to large data sets, such as individual claims, or large claim triangles. In short, they are likely to be useful in the analysis of any data set whose volume is sufficient to obscure a naked-eye view of its features. Unfortunately, such large data sets are in short supply in the actuarial literature. Accordingly, one needs to turn to synthetic data. Although the ultimate objective of these methods is application to real data, the use of synthetic data containing features commonly observed in real data is also to be encouraged. While there are a number of claims simulators in existence, each valuable within its own context, the inclusion of a number of desirable (but complicated) data features requires further development. Accordingly, in this paper we review those desirable features, and propose a new simulator of individual claim experience called `SynthETIC`. Our simulator is publicly available, open source, and fills a gap in the non-life actuarial toolkit. The simulator specifically allows for desirable (but optionally complicated) data features typically occurring in practice, such as variations in rates of settlements and development patterns; as with superimposed inflation, and various discontinuities, and also enables various dependencies between variables. The user has full control of the mechanics of the evolution of an individual claim. As a result, the complexity of the data set generated (meaning the level of difficulty of analysis) may be dialled anywhere from extremely simple to extremely complex.

Jong Wook Seo, In Ok Lee, Jung Cheol Kim et al.

ObjectiveTo investigate the role of port-site bupivacaine hydrochloride injection in laparoendoscopic single-site surgery (LESS) as a means of postoperative umbilical pain alleviation.MethodsA total of 200 consecutive patients who underwent LESS from October 2018 to February 2019 were included in this randomized prospective case control study. The patients were alternatively assigned to either the study group (0.25% 10-mL bupivacaine hydrochloride injection at the 1.5-cm umbilical incision site after surgery) or the control group (no injection). All patients underwent surgery at the National Health Insurance Service Ilsan Hospital under the same operational setting by 3 board-certified gynecologists. Postoperative umbilical pain scores assessed using the visual analog scale were compared between the 2 groups as the primary outcome. Student's t-test, χ2 test, and a linear mixed model were used for the statistical analysis. A P-value of <0.05 was considered to be statistically significant.ResultsThe patients' age, body mass index, and menopausal status; type of surgery performed; and need for additional trocar insertion exhibited a significant difference between the bupivacaine injection and non-injection groups. After adjusting for various confounding variables, the postoperative umbilical pain scores measured at postoperative 2–3 hours, 6–10 hours, 1 day, and 3 days did not exhibit a significant difference between the 2 groups.ConclusionPort-site bupivacaine injection in LESS did not show any additive effect in alleviation of postoperative umbilical pain.