Multiple Insurance Research Articles

Multiple agricultural risks and insurance—issues, perspectives, and illustration for wine-growing

Multiple agricultural risks and insurance—issues, perspectives, and illustration for wine-growing

Blockchain Applications in Cyber Liability Insurance

Blockchain technology is revolutionizing cyber liability insurance (CLI) by addressing key challenges in underwriting, risk assessment, and claims management. As cyber-attacks become more frequent and complex, the demand for effective CLI solutions has surged. Traditional insurance practices often fall short in this rapidly evolving landscape. Blockchain offers a decentralized, secure, and transparent approach, enhancing the accuracy of risk assessments and preventing fraudulent claims. By maintaining an immutable ledger of historical claims, blockchain allows for better comparison of new claims against past data. Additionally, smart contracts within blockchain frameworks can automate claims processing, reducing administrative tasks and speeding up resolutions. Blockchain also enables decentralized, peer-to-peer insurance platforms, allowing multiple insurers to pool resources and share risks in a transparent, efficient manner. This study explores how blockchain can transform CLI, improving efficiency and security across the industry.

Correlation aversion and bivariate stochastic dominance with respect to reference functions

This paper introduces an extension of stochastic dominance, moving from univariate to bivariate analysis by incorporating a reference function. Our approach offers flexibility in reference function selection, improving upon previous studies cohesively. Bivariate orderings are invaluable tools in actuarial sciences, facilitating the assessment and management of dependencies between risks and lifelengths within multiple insurance contracts. These advancements hold promising practical implications, particularly within the actuarial sciences domain.

End of life (EOL) care in head and neck squamous cell carcinoma (HNSCC) compared to other solid tumors (OST) in Washington (WA) State.

11147 Background: Real world data describing EOL care in HNSCC is limited. We performed a retrospective study evaluating EOL in HNSCC vs OST in a population-based sample of patients in WA. Methods: We used a database linking WA state cancer registry records with claims records from Medicare, Medicaid, and two large commercial insurers. Patients with HNSCC (oral cavity, oropharynx, hypopharynx, or larynx) were compared to OST (any solid tumor diagnosis). Adults with AJCC stage II-IV or SEER stage Regional/Distant who died in 2011-2021 with continuous insurance enrollment 6 months before death were included. We compared proportions of patients with >1 ED visits in the last 30 days of life, ICU admission in the last 30 days of life, chemotherapy in the last 14 days of life, and hospice enrollment at least 3 days prior to death. We performed multivariate regression analysis to determine factors associated with hospice enrollment. Results: 1,389 patients with HNSCC and 41,412 patients with OST were identified. Demographics for HNSCC vs OST included median age 68 vs 73, white race 91.5% vs 90.1%, stage IV 57.5% vs 45.3%. Insurance types for HNSCC vs OST were commercial 8.4% vs 9.8%, Medicaid 16.6% vs 8.8%, Medicare 59.1% vs 65.5%, multiple 15.8% vs 15.9% (p<0.0001). HNSCC patients had lower rates of >1 ED visits compared to OST (14.1% vs 16.4%, p=0.02); there was no significant difference in ICU admission (25.1% vs 24.0%, p=0.3) or chemotherapy receipt (6.3% vs 5.1%, p=0.056). Hospice enrollment was significantly lower in HNSCC patients (49.0% vs 56.4%, p<0.0001). A stratified analysis limited to stage IV patients yielded consistent findings in all categories. HNSCC patients died more at home and less in hospice (20.2% vs 12.7% and 41.5% vs 52.0%, p<0.0001). In a multivariate regression analysis (Table) HNSCC, black race, living with a partner, or living in neighborhoods with higher area deprivation index (ADI) was associated with lower hospice enrollment. Patients with Medicare or multiple insurance types were more likely to enroll in hospice; AJCC stage was not significant. Conclusions: In this population-based sample, compared to OST, a greater proportion of HNSCC patients were insured by Medicaid at EOL and were less likely to enroll in hospice prior to death. The reasons driving these observed disparities in hospice enrollment warrant further study to optimize EOL care among patients with HNSCC. [Table: see text]

Application of multiple validated algorithms for identifying incident breast cancer among individuals with atopic dermatitis.

Validated algorithms (VAs) in insurance claims databases are often used to estimate the prevalence and incidence of comorbidities and evaluate safety signals. However, although they are then used in different data sources or subpopulations from those in which they were developed the replicability of these VAs are rarely tested, making their application and performance in these settings potentially unknown. This paper describes testing multiple VAs used to identify incident breast cancer cases in a general population and in an indication-specific population, patients with atopic dermatitis (AD). Two algorithms were tested in multiple insurance claims databases and four cohorts were created. Modifications were made to account for the US insurance setting. The resulting incidence rates (IRs) were then compared across algorithms and against surveillance, epidemiology, and end results (SEER) estimates to assess reliability. Algorithm 1 produced low IRs compared to Algorithm 2. Algorithm 2 provided similar estimates to those of SEER. Individuals in the AD cohorts experienced lower incident breast cancer cases than those in the general population cohorts. Regardless of an algorithm's reported accuracy, the original study setting and targeted population for the VAs may matter when attempting to replicate the algorithm in an indication-specific subpopulation or varying data sources. Investigators should use caution and conduct sensitivity analyses or use multiple algorithms when attempting to calculate incidence or prevalence estimates using VAs.

A mean field game approach to optimal investment and risk control for competitive insurers

We consider an insurance market consisting of multiple competitive insurers with a mean field interaction via their terminal wealth under the exponential utility with relative performance. It is assumed that each insurer regulates her risk by controlling the number of policies. We respectively establish the constant Nash equilibrium (independent of time) on the investment and risk control strategy for the finite n-insurer game and the constant mean field equilibrium for the corresponding mean field game (MFG) problem (when the number of insurers tends to infinity). Furthermore, we examine the convergence relationship between the constant Nash equilibrium of finite n-insurer game and the mean field equilibrium of the corresponding MFG problem. Our numerical analysis reveals that, for a highly competitive insurance market consisting of many insurers, every insurer will invest more in risky assets and increase the total number of outstanding liabilities to maximize her exponential utility with relative performance.

A Cross-sectional Study on Awareness and Utilisation of Government Health Insurance Schemes among Patients at a Tertiary Level Hospital in Kolkata, India

Introduction: Despite the presence of multiple Government Health Insurance (GHI) schemes in West Bengal, the National Family Health Survey report (NFHS-5) has indicated that only 29.3% of households are covered by a health scheme. Awareness of health insurance schemes increases their utilisation. The absence of health insurance coverage results in increased out-of-pocket health expenditures, pushing families into debt. Therefore, there is a need to determine whether this lack of awareness among patients contributes to the issue. Aim: To estimate the awareness level, enrollment in GHI schemes, experiences of their utilisation, and to determine the contributory factors of awareness and enrollment among patients attending the Outdoor Patient Departments (OPDs) at a tertiary care hospital in Kolkata. Materials and Methods: An observational cross-sectional study was conducted from April 2023 to June 2023 at Medical College, Kolkata, West Bengal, India. A total of 390 respondents were chosen using a systematic random sampling technique and were interviewed using a predesigned, pretested, and semistructured questionnaire. Data were analysed using R Studio version 4.3.0. A p-value <0.05 was considered statistically significant. Results: Awareness about Swasthya Sathi was found to be present in 318 (81.54%) patients, but only 109 (34.28%) of them were enrolled. Awareness of Sishu Saathi and Rashtriya Bal Swasthya Karyakram (RBSK) was 12 (3.08%) and 10 (2.57%), respectively, and none were enrolled. The major source of information (11.03%) regarding health insurance among respondents was informal sources such as friends, relatives, and neighbours. The age of the respondents, type of family, occupation, and economic status were found to have a significant association with the right awareness (p=0.008, 0.012, 0.0005, and 0.029, respectively). The patient satisfaction level after utilising Swasthya Sathi was found to have a significant positive correlation with the right awareness (Spearman’s ρ=0.322, p-value <0.01). The determinants of enrollment in Swasthya Sathi were female gender, rural residence, and right awareness (p<0.001). The commonest reason for not enrolling in any GHI among the non subscribers was a lack of awareness (82.56%). Conclusion: Correct awareness was found to be a determinant of enrollment in GHI. In order to bridge the gap between awareness and utilisation of GHI, there is a need to focus on Information, Education, and Communication (IEC) activities involving mass media and frontline health workers.

Time-consistent reinsurance-investment games for multiple mean-variance insurers with mispricing and default risks

This paper studies a non-zero-sum stochastic differential game for multiple mean-variance insurers. Insurers can purchase proportional reinsurance and invest in a risk-free asset, a market index, a defaultable bond and multiple pairs of mispriced stocks. The dynamics of the mispriced stocks satisfy a “cointegrated system” where the expected returns follow the mean reverting processes, and the bond is defaultable with a recovering proportional value at default. In particular, we assume that the investment opportunities in mispriced stocks are only available for a few insurers, which is more realistic and in line with the superiority of information in the competitive market. Each insurer's objective is maximizing a function of her terminal wealth and competitors' relative wealth under the mean-variance criterion. Using techniques in stochastic control theory, we establish the extended Hamilton-Jacobi-Bellman equations and obtain the equilibrium strategies. Note that the derived solutions are analytical and time-consistent, and we verify the competitive advantages gained from investment opportunities in mispriced stocks. We represent our results in terms of the M-matrices, which help us prove the existence and uniqueness of the solutions and further explicitly analyze how the crucial arguments in the model affect the equilibrium strategies. Numerical examples with detailed sensitivity analyses are presented to support our conclusions.

A national survey of the antibiotic use, self-medication practices, and knowledge of antibiotic resistance among graduates of tertiary institutions in Nigeria

IntroductionAntimicrobial resistance (AMR) is a growing global public health concern that was directly responsible for 1.27 million deaths and indirectly associated with 4.95 million deaths in 2019. Antibiotic resistance (ABR) occurs naturally, but its prevalence has been accelerated broadly due to antibiotic misuse and overuse, poor infection control practices, and availability of substandard and falsified medicines. ObjectivesTo assess antibiotic use and knowledge of ABR among graduates of tertiary education in Nigeria and evaluate if tertiary education, academic background (science, social sciences, or the arts) and years post-graduation significantly impact antibiotic use and awareness of antibiotic resistance. ResultDespite having tertiary education, 47.7 % of respondents self-medicate with antibiotics, 54.9 % of respondents don't carry out laboratory investigations before using antibiotics, and 70.1 % reduce or stop taking antibiotics on feeling better. Inconvenience, limited access to doctors and financial constraint were the most common reasons for self-medication. Academic background, age, gender and years post-graduation had no statistically significant effect on self-medication practices (p-value>0.05). Inappropriate antibiotic use for viral-infections like sore throat, cold and flu, and diarrhoea was reported in 50.2, 42.6 and 40.2 % of respondents, respectively. Amoxicillin (54.2 %), metronidazole (48.2 %), and ciprofloxacin (45.6 %) were the most used antibiotics. Pharmacists were the most consulted health professionals before antibiotics were used, and the internet is the most common source of information on antibiotic resistance. Most-respondents, 85.5 %, correctly identified that antibiotic misuse contributes to ABR. ConclusionThe increased knowledge and awareness of ABR among respondents did not translate into proper antibiotic use, emphasizing the need for more stringent regulations on antibiotic dispensing and prescribing. Health sector reforms focused on utilizing technology like telemedicine to improve convenient access to health care, and multiple health insurance schemes to reduce out-of-pocket spending should be prioritized to improve health equity and universal health coverage (UHC).

BRCA1/2 germline testing among eligible persons with breast cancer in Washington state: A retrospective study using state cancer registry and claims data.

154 Background: Clinical practice guidelines have recommended germline testing certain groups of breast cancer patients (men, younger women, and triple negative) for pathogenic BRCA1/2 mutations since 1996. We linked cancer registry records with enrollment and claims records from public and commercial insurers in Washington state to assess factors associated with BRCA1/2 testing among eligible persons with breast cancer. Methods: The database consisted of Washington SEER and state cancer registry records linked with claims records from commercial insurers (Premera Blue Cross, Regence Blue Shield), Medicare, Medicaid, and the Washington State Employee Benefit Plan. Eligible patients were diagnosed with breast cancer between 2017-2019 and were age <= 50 female, any age male, or with triple negative cancer. Other inclusion criteria included first primary cancer, alive at least 3 months following diagnosis, and continuous insurance enrollment from 2 months prior to 24 months following diagnosis. We used multivariable logistic regression to examine factors associated with BRCA1/2 testing. In a secondary analysis, we examined whether receipt of testing was associated with bilateral mastectomy. Results: The study population included 1,358 women and 43 men (80.2% were non-Hispanic White, 4.1% non-Hispanic Black, 11.7% non-Hispanic Asian, and 4.9% Hispanic.) The insurance composition was as follows: 56% commercial, 15% Medicare, 19% Medicaid; 10% multiple insurers. Overall, 63% received BRCA1/2 testing. Factors that were significantly associated with testing are shown in the table. In the secondary regression model, the association between BRCA1/2 testing and bilateral mastectomy was positive (OR 1.45, 95% CI 1.07-1.98). Conclusions: Despite a trend towards more testing over time, BRCA1/2 germline testing remains underutilized among persons who are eligible for testing, with significant disparities among Medicaid and Medicare enrollees. Testing may influence management, but further study is required. Patients would benefit from more effective integration of clinical guidelines into practice.[Table: see text]

Barriers Associated With Missed Palliative Care Telehealth Visits.

Background: The COVID-19 pandemic accelerated the adoption of telehealth in palliative care. While this technology showed efficiencies in healthcare delivery, it also unmasked inequalities affecting the socially disadvantaged. Objective: To identify factors associated with missed telehealth visits. Methods: We reviewed telehealth visits between April 1, 2020 and March 31, 2021 at a palliative care clinic. Disease-related and demographic information were recorded, including residency in community outreach zones (COZ)-zip code clusters known for healthcare underutilization. We categorized patients with at least one missed visit as "any miss" (AM), and those with at least three scheduled visits and missed at least 50% as "pattern miss" (PM). Results: Of 1225 scheduled telehealth (i.e., audiovisual) visits, there were 802 completed, 52 missed initial and 371 missed follow-up encounters. Among 505 unique patients, 363 (72%) were receiving cancer treatment, 170 (34%) had multiple insurance, 87 (17%) lived in COZ, 101 (20%) were AM, and 27 (5%) were PM. Patients in COZ had significantly higher risk of PM vs those outside (OR = 2.56, 95% CI: 1.06-5.78, P = .03). Patients with multiple insurance had significantly higher risk of PM vs those with single or no coverage (OR = 3.06, 95% CI: 1.40-6.93, P = .006). Patients on treatment had significantly higher risk of AM vs those not in treatment (OR = 1.75, 95% CI: 1.05-3.06, P = .04). Conclusion: We identified living in areas with healthcare underutilization, active cancer treatment, and multiple insurance coverage as barriers to telehealth visits. Measures are necessary to attenuate disparities in accessing palliative care via telehealth.

Real-world prevalence, time of diagnosis, and co-occurrence patterns of birth defects in live-born infants, 2014-2020: A health administrative database study in Japan.

A study evaluating the real-world prevalence of birth defects (BDs), including co-occurrence patterns, will provide the information required to estimate Japan's true BD prevalence and monitor it. Information such as when infants are diagnosed with BDs is crucial for defining the study population and data collection period in future administrative database studies. This study utilized the DeSC database, a large claims database comprising multiple health insurance schemes. The prevalence of major BDs, including structural congenital malformations (CMs) and chromosomal abnormalities, was determined in infants born between 2014 and 2020 and continuously insured for ≥1 year. The time of the first BD diagnosis and multiple BD patterns were also evaluated. Among 43,147 infants, 3050 (7.07%) were diagnosed with major BDs, and 3002 (6.96%) with major CMs. The circulatory system (2.95%) was the most frequent organ system affected by CMs, followed by CMs and deformations of the musculoskeletal system (1.94%). The cumulative diagnostic rates of BDs and CMs at month 6 were 85.9% and 85.6%, respectively. The EUROCAT BD subgroups diagnosed in more than 1.0% of the infants were atrial septal defects (1.47%) and patent ductus arteriosus (1.07%). Among the 2997 infants with EUROCAT BDs, 241 (8.04%) were classified as having multiple BDs. A large claims database is a valuable resource for evaluating and monitoring the prevalence of BDs, including multiple patterns. At least 1 year since birth should be considered in future administrative database studies evaluating BDs as outcomes.

Valuing Equity-Linked Death Benefits on Multiple Life with Time until Death following a K n Distribution

The purpose of this paper is to investigate the valuation of equity-linked death benefit contracts and the multiple life insurance on two heads based on a joint survival model. Using the exponential Wiener process assumption for the stock price process and a K n distribution for the time until death, we provide explicit formulas for the expectation of the discounted payment of the guaranteed minimum death benefit products, and we derive closed expressions for some options and numerical illustrations. We investigate multiple life insurance based on a joint survival using the bivariate Sarmanov distribution with K n (i.e., the Laplace transform of their density function is a ratio of two polynomials of degree at most) marginal distributions. We present analytical results of the joint-life status.

Analysis of Premium Reserve Using Zillmer Method and Canadian Method for Endowment Joint Life Insurance

Several life insurance companies are unable to compensate policyholder prompting financial losses, the situation can be foreseen if the insurance company has a properly established and calculated reserve value. Endowment life insurance is one types of life insurance. Life insurance provides protection for one person (single life) or two or more people (multiple life). According to the insured death status, there are two terminologies used in multiple life insurance: joint life and last survivor. The Zillmer Method and Canadian Method used in this study for 3 age cases for a couple of husband and wife whereas a husband is older than wife, a husband has the same age as wife, and a husband is younger than wife to determine the amount of reserves adjusted for endowment joint life insurance. Researchers first determine the benefits, then calculate the annuity, and finally calculate the annual premium in order to compute reserves. The Zillmer Method premium reserve value is minus in the beginning year to cover cost for the company, meanwhile Canadian Method is not. According to the result of this study, the case that the age of wife is same as the husband have lesser reserve than any cases which represent this is beneficial for the company to cover several costs for the policy in the beginning of period. Based on data analysis, the period of the insurance contract and the age of the insured define the reserve value. The older the insurance participant, the lesser the value of reserve.

Optimal reinsurance contract and investment strategy for multiple competitive-cooperative insurers and a reinsurer

Abstract Accepted by: Giorgio Consigli In this article, we consider a reinsurance contract design by taking into account the joint interests of multiple insurers and a reinsurer. The reinsurance contract consists of optimal reinsurance strategies and reinsurance prices. The former are chosen by the competitive–cooperative insurers and the latter are determined by a reinsurer. Both insurers and the reinsurer can invest in the common risk-free asset and one different risky asset. The optimal time-consistent reinsurance–investment strategies of the insurers and the optimal reinsurance prices and investment strategy of the reinsurer are derived analytically. Numerical experiments are carried out to illustrate the influences of model parameters on the optimal reinsurance contract and optimal investment strategies. We find that the establishment of the reinsurance contract is affected by the correlation between the claim sizes of insurers as well as that of claim numbers. The results reveal that competition and cooperation will lead to a decrease and increase of the reinsurance price, respectively, showing the importance of opting for cooperation among insurers. Both competition and cooperation are beneficial to insurers, especially for those with high risk aversion.

Evolution of Government-funded health insurance for universal health coverage in India.

India has run multiple Government-Funded Health Insurance schemes (GFHIS) over the past decades to ensure affordable healthcare. We assessed GFHIS evolution with a special focus on two national schemes - Rashtriya Swasthya Bima Yojana (RSBY) and Pradhan Mantri Jan Arogya Yojana (PMJAY). RSBY suffered from a static financial coverage cap, low enrollment, inequitable service supply, utilization, etc. PMJAY expanded coverage and mitigated some of RSBY's drawbacks. Investigating equity in PMJAY's supply and utilization across geography, sex, age, social groups, and healthcare sectors depicts several systemic skews. Kerala and Himachal Pradesh with low poverty and disease burden use more services. Males are more likely to seek care under PMJAY than females. Mid-age population (19-50 years) is a common group availing services. Scheduled Caste and Scheduled Tribe people have low service utilization. Most hospitals providing services are private. Such inequities can lead the most vulnerable populations further into deprivation due to healthcare inaccessibility.

Association between patient, clinic, and geographical-level factors and 1-year surveillance colonoscopy adherence.

Surveillance colonoscopy 1-year after surgical resection for patients with stages I-III colorectal cancer (CRC) is suboptimal and data on factors associated with lack of adherence are limited. Using surveillance colonoscopy data from Washington state, we aimed to determine the patient, clinic, and geographical factors associated with adherence. Using administrative insurance claims linked to Washington (WA) cancer registry data we conducted a retrospective cohort study of adult patients diagnosed with stage I-III CRC between 2011 and 2018 with continuous insurance for at least 18 months after diagnosis. We determined the adherence rate to 1-year surveillance colonoscopy and conducted logistic regression analysis to identify factors associated with completion. Of 4,481 stage I-III CRC patients identified, 55.8% completed a 1-year surveillance colonoscopy. The median time to colonoscopy completion was 370 days. On multivariate analysis, older age, higher stage CRC, Medicare insurance or multiple insurance carriers, higher Charlson Comorbidity Index score and living without a partner were significantly associated with decreased adherence to 1-year surveillance colonoscopy. Among 29 eligible clinics, 51% (n=15) reported lower than expected surveillance colonoscopy rates based on patient mix. Surveillance colonoscopy 1-year after surgical resection is sub-optimal in WA state. Patient and clinic factors, but not geographic factors (Area Deprivation Index), were significantly associated with surveillance colonoscopy completion. This data will inform the development of patient and clinic level interventions to address an important quality of care issue across Washington.

Confluence of Blockchain and Artificial Intelligence Technologies for Secure and Scalable Healthcare Solutions: A Review

Blockchain (BC) and Artificial Intelligence (AI) technologies have independent applications in multiple industries, including banking, finance, health care, construction, transportation, hospitality, manufacturing, and insurance, to name a few. Moreover, these two technologies can be integrated seamlessly, thanks to their complementary and mutually-supportive features. AI algorithms can make the medical blockchain storage efficient by their processing algorithms, also playing the role of knowledgeable gatekeepers. Blockchain can support AI models by providing secure, sizeable, traceable, diverse, and immutable healthcare data for the training purpose. The integration of BC and AI has multiple use cases in the healthcare industry ranging from disease prediction to pandemic management. Previously, researchers have reviewed the applications of each of these technologies in health care independently. Although the integration of BC and AI has been fruitful, to the best of our knowledge, there has been no work in the past reviewing the confluence of these two technologies in the health care sector. We have classified the works based on two different classification schemes: application-based and AI-training paradigm-based classification. We have also provided a compilation of tools used in the integrated systems of BC and AI for healthcare. We identified that the integration of BC and AI technologies had been applied in quite different areas of healthcare ranging from biomedical research to pandemic management. It is also noted that the supervised learning algorithms and federated learning paradigm for secure decentralized AI model training are often used in the integration. Our findings reveal that majority of the reviewed works use blockchain as a secure database for AI models. Further, we also have pointed out the potential applications of these two technologies in health care.

Neighborhood Incarceration Rates and Adverse Birth Outcomes in New York City, 2010-2014

The US has high rates of adverse birth outcomes, with substantial racial disparities augmented by stress and neighborhood disadvantage. Black people are more likely to live in neighborhoods with high rates of incarceration, which is a source of both stress and neighborhood disadvantage and, thus, may contribute to adverse birth outcomes. To determine whether neighborhoods with high incarceration rates also have higher rates of adverse birth outcomes compared with neighborhoods with lower rates. This cross-sectional study used publicly available data from the New York City Department of Health (2010-2014). Censored Poisson regression, with the US Census tract as the unit of analysis, was used to examine the association of neighborhood incarceration rate and birth outcomes. Multivariable models included percentage of births aggregated to the Census tract by maternal factors (age, parity, singleton vs multiple birth, insurance, and race) and neighborhood factors (poverty, education, and violent crime). Analyses were performed between May 2021 and October 2022. Neighborhood incarceration rate, categorized into quintiles. The primary outcome was the incidence rate ratio (IRR) of preterm birth and low birth weight. Secondary outcomes were IRRs of very preterm birth, extremely preterm birth, and very low birth weight. Hypotheses were formulated before data collection. Among 2061 Census tracts with 562 339 births, incarceration rates varied from 0 to 4545 people incarcerated per 100 000, and high-incarceration neighborhoods had more residents of Black race (54.00% vs 1.90%), living in poverty (32.30% vs 10.00%), and without a general educational development equivalent (28.00% vs 12.00%) compared with low-incarceration neighborhoods. In fully adjusted models, high-incarceration neighborhoods had a 13% higher IRR of preterm birth (IRR, 1.13; 95% CI, 1.08-1.18), 45% higher IRR of very preterm birth (IRR, 1.45; 95% CI, 1.24-1.71), 125% higher IRR of extremely preterm birth (IRR, 2.25; 95% CI, 1.59-3.18), 10% higher IRR of low birth weight (IRR, 1.10; 95% CI, 1.05-1.16), and 52% higher IRR of very low birth weight compared with low-incarceration neighborhoods (IRR, 1.52; 95% CI, 1.28-1.81). Neighborhood incarceration rate was positively associated with adverse birth outcomes, particularly those associated with infant mortality. Black people were significantly more likely to live in high-incarceration neighborhoods, suggesting that mass incarceration may contribute to racial disparities in birth outcomes.

The hard way from the Beveridge to the Bismarck model of health finance: Expectations and reality in Russia.

Most post-Soviet countries have introduced mandatory health insurance (MHI) systems which completely or partially replaced national health systems known as budgetary models. In Russia, an attempt was made to introduce a competitive MHI model with multiple health insurers. The current MHI system has, however, acquired an increasing number of features inherent in the previous budgetary model. This study analyzes the institutional characteristics and the outcomes of a new mixed model. A combination of two analytical approaches is used as follows: (1) considering three functions of the financing system (revenue collection, pooling funds, and purchasing healthcare) and (2) exploring three types of the model regulation (state, societal, and market). We analyze the types of regulation that are used to implement each of the three financial functions. The model has contributed to more sustainable health funding, its geographical equalization, and service delivery restructuring, while the implementation of its purchasing function has many unsolved problems. We highlight the dilemma of the further development of the model by (a) continuing to replace the remaining market and societal regulatory mechanisms with state regulations or (b) developing market mechanisms and thereby strengthening the impact of health insurers on the health system performance. Lessons for countries considering the transformation of their budgetary health finance model to the MHI model are presented.