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.

OBJECTIVE: Positive airway pressure (PAP) compliance is important in treating obstructive sleep apnea. Previous studies have suggested that patients with economic burdens, discomfort using machines, and insufficient education have difficulty tolerating PAP machines. This study explored the factors affecting short-term adherence to PAP in a veterans medical center.
METHODS: The medical records of patients who underwent polysomnography at the Veterans Health Service Medical Center, Seoul, Republic of Korea, between July 2018 and January 2021 were reviewed retrospectively. Patients with an apnea-hypopnea index (AHI) ≥15 were included (n=579). PAP adherence was defined as continuous use for ≥21 days for ≥4 hours daily for 30 consecutive days for 90 days from the date of PAP prescription.
RESULTS: The PAP-adherent group (n=265, age 66.16±11.28 years) was younger and had more years of education, higher body mass indices, and lower scores in the Insomnia Severity Index and Beck Depression Inventory-II (BDI-II) than those of the PAP-nonadherent group (n=314, age 68.93±10.91 years). Patients who tolerated PAP had a higher AHI, longer duration of oxygen desaturation (less than 90%), and less dream enactment behavior (DEB) than that in those who did not. After adjusting for age, years of education, BDI-II, duration of oxygen desaturation, and presence of DEB, there were more patients with National Health Insurance (NHI) in the PAP-adherent group than in the PAP-nonadherent group (p<0.001).
CONCLUSIONS: We showed that patients with NHI recorded significantly higher adherence compared to that in patients without NHI, among other factors.

BACKGROUND: Dizziness/vertigo is one of the most common symptoms for which people seek healthcare. However, the healthcare expenditure attributable to dizziness/vertigo in South Korea remains poorly understood. We investigated the healthcare costs due to six major disorders causing dizziness/vertigo using claims data.
METHODS: The healthcare costs were evaluated using all the claims data submitted to the Health Insurance Review and Assessment Service from January 1 to December 31, 2022. The six major vestibular disorders included for analysis were benign paroxysmal positional vertigo (BPPV), psychogenic/persistent postural perceptual dizziness (PPPD), vascular vertigo/dizziness (VVD), vestibular migraine (VM), Meniere\'s disease (MD), and vestibular neuritis (VN).
RESULTS: During the 1-year study period, 4.1% of adults aged 20 or older visited hospitals due to dizziness/vertigo in South Korea. Compared to the general population, the patients with dizziness/vertigo were more often elderly, female, and residents of small towns. The total healthcare cost for the six major vestibular disorders was ₩547.8 billion (approximately $406.5 million). BPPV incurred the highest annual healthcare cost (₩183.5 billion, 33.5%), followed by VVD (₩158.8 billion, 29.0%), MD (₩82.2 billion, 15.0%), psychogenic/PPPD (₩60.3 billion, 11.0%), VN (₩32.9 billion, 6.0%), and VM (₩30.1 billion, 5.5%). The mean healthcare cost per hospital visit due to dizziness/vertigo was ₩96,524 (95% confidence interval, ₩96,194-₩96,855), 30% higher than the average (₩73,948) of the overall healthcare cost per hospital visit over the same period.
CONCLUSIONS: Owing to higher healthcare costs for dizziness/vertigo and increased prevalence of dizziness/vertigo in the aged population, healthcare costs due to dizziness/vertigo will increase rapidly in South Korea. Thus, a guideline for cost-effective management of dizziness/vertigo should be established to reduce the healthcare costs due to these common symptoms.

Cost-effectiveness analyses are required for therapies within Canada\'s universal healthcare system, leading to delays relative to U.S. healthcare. Patients with Hodgkin lymphoma (HL) generally have an excellent prognosis, but those who relapse after or are ineligible for transplant benefit from novel therapies, including brentuximab vedotin (BV). BV was FDA-approved in 2011 but not Canadian-funded until 2014. To assess the impact of access delays, we compared changes in survival for U.S. (by insurer) and Canadian patients in periods pre/post-U.S. approval. Patients were 16-64 years, diagnosed with HL in 2007-2010 (Period 1) and 2011-2014 (Period 2) from the U.S. SEER and Canadian Cancer Registries. Approval date (surrogate) was utilized as therapy was unavailable in registries. Kaplan-Meier survival curves and adjusted Cox regression models compared survival between periods by insurance category. Among 12,003 U.S. and 4210 Canadian patients, survival was better in U.S. patients (adjusted hazard ratio (aHR) 0.87 (95%CI 0.77-0.98)) between periods; improvement in Canadian patients (aHR 0.84 (95%CI 0.69-1.03) was similar but non-significant. Comparisons between insurers showed survival was significantly worse for U.S. uninsured and Medicaid vs. U.S. privately insured and Canadian patients. Given the increasingly complex nature of oncologic funding, this merits further investigation to ensure equity in access to therapy developments.

BACKGROUND: Patients with heart failure (HF) are the most commonly readmitted group of adult patients in Germany. Most patients with HF are readmitted for noncardiovascular reasons. Understanding the relevance of HF management outside the hospital setting is critical to understanding HF and factors that lead to readmission. Application of machine learning (ML) on data from statutory health insurance (SHI) allows the evaluation of large longitudinal data sets representative of the general population to support clinical decision-making.
OBJECTIVE: This study aims to evaluate the ability of ML methods to predict 1-year all-cause and HF-specific readmission after initial HF-related admission of patients with HF in outpatient SHI data and identify important predictors.
METHODS: We identified individuals with HF using outpatient data from 2012 to 2018 from the AOK Baden-Württemberg SHI in Germany. We then trained and applied regression and ML algorithms to predict the first all-cause and HF-specific readmission in the year after the first admission for HF. We fitted a random forest, an elastic net, a stepwise regression, and a logistic regression to predict readmission by using diagnosis codes, drug exposures, demographics (age, sex, nationality, and type of coverage within SHI), degree of rurality for residence, and participation in disease management programs for common chronic conditions (diabetes mellitus type 1 and 2, breast cancer, chronic obstructive pulmonary disease, and coronary heart disease). We then evaluated the predictors of HF readmission according to their importance and direction to predict readmission.
RESULTS: Our final data set consisted of 97,529 individuals with HF, and 78,044 (80%) were readmitted within the observation period. Of the tested modeling approaches, the random forest approach best predicted 1-year all-cause and HF-specific readmission with a C-statistic of 0.68 and 0.69, respectively. Important predictors for 1-year all-cause readmission included prescription of pantoprazole, chronic obstructive pulmonary disease, atherosclerosis, sex, rurality, and participation in disease management programs for type 2 diabetes mellitus and coronary heart disease. Relevant features for HF-specific readmission included a large number of canonical HF comorbidities.
CONCLUSIONS: While many of the predictors we identified were known to be relevant comorbidities for HF, we also uncovered several novel associations. Disease management programs have widely been shown to be effective at managing chronic disease; however, our results indicate that in the short term they may be useful for targeting patients with HF with comorbidity at increased risk of readmission. Our results also show that living in a more rural location increases the risk of readmission. Overall, factors beyond comorbid disease were relevant for risk of HF readmission. This finding may impact how outpatient physicians identify and monitor patients at risk of HF readmission.

UNASSIGNED: This study was conducted to evaluate whether the type of insurance coverage is associated with missed appointments and to evaluate the effect of missed appointments on diabetes control.
UNASSIGNED: All patients with diabetes mellitus (DM) managed at a major academic medical center between Jan 2015 and Dec 2020 were included in analysis. Association between insurance coverage and the proportion of missed appointments was evaluated with adjustments for demographic variables and social determinants of health. The relationship between proportion of missed appointments and glycemic control was also evaluated.
UNASSIGNED: The dataset included 30,633 patients, out of which 14,064 (46%) reported commercial insurance, 13,376 (44%) reported Medicare and 3,193 (10%) reported Medicaid coverage. Proportion of missed appointments was 18.1 ± 18.1% among Medicaid covered patients,12.1 ± 15.3% among commercially insured and 10.2 ± 14.1% among Medicare covered patients (p < 0.001). Type of insurance was found to be a significant predictor of proportion of missed appointments after adjusting for age, race, language, marital status, smoking, BMI, HbA1c and type of diabetes (p < 0.001) in series regression analysis. Proportion of missed appointments was associated with HbA1c with partial correlation coefficient +0.104 (p < 0.005) after adjusting for age, race, gender, type of insurance coverage, BMI and type of diabetes.
UNASSIGNED: Medicaid covered patients with diabetes have higher proportion of missed clinic appointments and higher HbA1c. More research is needed to evaluate the root causes of inability to keep appointments in this population so that strategies for improved healthcare delivery can be designed.

BACKGROUND: The Family Physician Programme is a key health reform in Iran that faces significant challenges in urban areas, particularly in Mazandaran and Fars provinces The study aims to critically evaluate the challenges encountered in the Urban Family Physician Program, with a particular focus on the perspectives of insurance organizations.
METHODS: A qualitative approach was adopted, involving semi-structured interviews with 22 experts and managers from basic health insurance funds. Snowball sampling facilitated participant selection, and interviews proceeded until saturation. Data analysis utilized content analysis and Atlas-T software, adhering to COREQ criteria.
RESULTS: Implementation problems of the urban family physician program were categorized into ten Categories and 22 Subcategories, including financing, stewardship, human resources, structure, culture, information system, payment, monitoring and control, the function of insurance organizations, and implementation.
CONCLUSIONS: The urban family physician program\'s implementation challenges, as viewed by health insurance organizations, underscore the necessity for strategic decision-making in financing, payment models, electronic system integration, structural adjustments, comprehensive monitoring, evaluation, cultural considerations, and appropriate devolution to insurance entities.

The Philippines is a source of labor for many countries. Roughly 10 million overseas Filipinos are working and living outside of the Philippines. This paper examines the association between sociodemographic characteristics (sex, age, educational level, and income) and self-rated physical and mental health, access to healthcare, and health habits among immigrant Filipinos living in Santa Cruz de Tenerife, Spain. Through convenience sampling, Filipino migrants (n = 103) aged 18 years and above participated in the online survey between October 2022 and March 2023. The data were analyzed using descriptive statistical analysis and chi-square. Almost all respondents self-rated their health as excellent and very good. Female respondents are more affected by mental health. Most are enrolled in the Universal Health System of Spain (public insurance). There is more utilization of private health insurance among respondents aged 60 years and above and high-wage earners. Cigarette smoking and alcohol drinking are associated with males. More than half of the respondents perform weekly exercise occasionally or never. These findings suggest a potential need for targeted interventions with an emphasis on the practice of preventive health and the promotion of healthy lifestyles, especially among financially disadvantaged migrants with lesser health access.

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.

BACKGROUND: Depression significantly impacts the quality of life and medical care in patients with coronary heart disease (CHD). This study assesses the burden of depression in adults aged 40 years and above with CHD and evaluates predictors of depression in this population. It has been reported that approximately 17-44% of persons with CHD have a major depression diagnosis and that nearly 27% of individuals undergoing coronary artery bypass graft operation suffer depression following the procedure.  Methods: Data from the 2022 National Health Interview Survey was used. The sample was made up of adults 40 years and above with CHD. A chi-square analysis was used to identify differences between those who were depressed and those who were not. Logistic and ordinal regression analyses were used to identify predictors of depression and severe depression, respectively.
RESULTS: The proportion of adults 40 years and above with CHD who reported having depression was 863/1700 (50.5%). Among those who were ≥65, the proportion of those who reported depression and those who did not were similar (49.3% vs. 50.7%). Most women reported having depression (57.4% vs. 42.6%), while fewer men reported having depression (46.3% vs. 53.7%). The positive predictors of depression include being insured (odds ratio (OR) 1.26 (1.05-1.53), p = 0.016), college degree (OR 1.09 (1.01-1.18), p = 0.040), diabetes mellitus (OR 1.28 (1.15-1.42), p < 0.001), and hypertension (OR 1.34 (1.24-1.44), p < 0.001). The negative predictors of being depressed were age ≥65 (OR 0.74 (0.69-0.80), p < 0.001), male sex (OR 0.54 (0.50-0.58), p < 0.001), and ratio of family income (RFI) ≥1 (OR 0.68 (0.61-0.77), p < 0.001). The positive predictors of severe depression include diabetes mellitus (OR 1.38 (1.06-1.81), p = 0.019) and current cigarette use (OR 2.10 (1.44-3.07), p < 0.001).
CONCLUSIONS: A significant proportion of adults 40 years and above with CHD have depression, and socioeconomic and cardiovascular risk factors are associated with a high likelihood of depression. Cardiovascular risk factors alone predict the likelihood of severe depression. Interventions to address depression in CHD should target specifically these high-risk individuals.