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UNASSIGNED: The COVID-19 pandemic led to unemployment and associated health insurance loss, prompting an unprecedented adoption of emergency policies, including economic relief efforts and health insurance coverage expansion. We sought to understand pandemic-related challenges for people with asthma and how emergency policies served families facing both chronic disease management and health insurance loss.
UNASSIGNED: Qualitative interview study.
UNASSIGNED: In 2021, we conducted semi-structured telephone interviews with 21 adults who had asthma and lost employment and employer-sponsored health insurance coverage during the COVID-19 pandemic. We used thematic analysis to assess how health and economic policies affected participants\' ability to access care and manage their asthma.
UNASSIGNED: Participants reported reduced access to care, as well as worry about heightened susceptibility to COVID-19 due to their asthma. While insurance loss exacerbated these challenges, participants indicated that economic relief efforts, including direct stimulus payments, helped them afford needed asthma care. Participants were more critical of enhancements to existing coverage policies such as the Affordable Care Act (ACA) Marketplace and Consolidated Omnibus Budget Reconciliation Act (COBRA) due to difficulty understanding, accessing, and affording such coverage.
UNASSIGNED: Our findings underscore that people affected by asthma and health insurance loss benefit from policies that provide flexible and easy-to-use assistance, such as direct payments, for meeting the diverse challenges posed by living with a chronic disease. Although policies that expand health insurance coverage are critical, more attention is needed to help people with chronic conditions access these programs in a timely way.

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.

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.

OBJECTIVE: The underreporting of occupational diseases in many countries significantly hampers the development of intervention programs, posing a significant public health problem. Our study aimed to contribute to the occupational diseases surveillance by examining the data of hospitals authorized to issue reports throughout Turkey.
METHODS: This cross-sectional study was conducted using medical diagnoses of occupational diseases reported to the General Directorate of Public Health from 81 provinces in Turkey between 1 January 2018 and 31 December 2022. The study evaluated hospitals that made medical diagnoses of occupational diseases and compared age groups, genders, occupational disease diagnosis groups and provinces of work regarding legal and medical diagnoses.
RESULTS: The top three disease groups in terms of medical diagnosis are musculoskeletal disorders with 38.8%, respiratory diseases with 14.4% and hearing defects with 10.9%. Regarding legal diagnoses, respiratory system diseases ranked first with 26.4%, followed by musculoskeletal disorders with 8.2% and hearing defects with 5.5%. While the provinces where most cases of medical occupational diseases are diagnosed share similarities, the majority of affected individuals in Karabük and Batman have not received a legal recognition of the occupational disease. Two-thirds of Turkey\'s medical occupational disease diagnoses were made in two hospitals.
CONCLUSIONS: This study is reflecting national data in Turkey and is the country\'s first nationwide study. The number of occupational diseases in Turkey is lower than expected. It would be more accurate to express the data in a way that includes medical diagnoses instead of using the number of compensated files corresponding to legal diagnoses.

BACKGROUND: Target systolic blood pressure (SBP) levels for older adults with hypertension vary across countries, leading to challenges in determining the appropriate SBP level.
OBJECTIVE: This study aims to identify the optimal SBP level for minimizing all-cause and cardiovascular disease (CVD) mortality in older Korean adults with hypertension.
METHODS: This retrospective cohort study used data from the National Health Insurance Service database. We included older adults aged 65 years or older who were newly diagnosed with hypertension and underwent a National Health Insurance Service health checkup in 2003-2004. We excluded patients who had a history of hypertension or CVD, were not prescribed medication for hypertension, had missing blood pressure or any other covariate values, and had fewer than 2 health checkups during the follow-up period until 2020. We categorized the average SBP levels into 6 categories in 10 mm Hg increments, from <120 mm Hg to ≥160 mm Hg; 130-139 mm Hg was the reference range. Cox proportional hazards models were used to examine the relationship between SBP and all-cause and CVD mortalities, and subgroup analysis was conducted by age group (65-74 years and 75 years or older).
RESULTS: A total of 68,901 older adults newly diagnosed with hypertension were included in this study. During the follow-up period, 32,588 (47.3%) participants had all-cause mortality and 4273 (6.2%) had CVD mortality. Compared to older adults with SBP within the range of 130-139 mm Hg, individuals who fell into the other SBP categories, excluding those with SBP 120-129 mm Hg, showed significantly higher all-cause and CVD mortality. Subgroup analysis showed that older adults aged 65-74 years had higher all-cause and CVD mortality rates according to SBP categories than those aged 75 years or older.
CONCLUSIONS: The SBP levels within the range of 120-139 mm Hg were associated with the lowest all-cause and CVD mortality rates among older Korean adults with hypertension. It is recommended to reduce SBP to <140 mm Hg, with 120 mm Hg as the minimum value for SBP, for older Korean adults with hypertension. Additionally, stricter SBP management is required for adults aged 65-74 years.

UNASSIGNED: Addressing social determinants of health (SDOH) is fundamental to improving health outcomes. At a student-run free clinic, we developed a screening process to understand the SDOH needs and resource utilization of Milwaukee\'s uninsured population.
UNASSIGNED: In this cross-sectional study, we screened adult patients without health insurance (N = 238) for nine traditional SDOH needs as well as their access to dental and mental health care between October 2021 and October 2022. Patients were surveyed at intervals greater than or equal to 30 days. We assessed correlations between SDOH needs and trends in patient-reported resource usefulness.
UNASSIGNED: Access to dental care (64.7%) and health insurance (51.3%) were the most frequently endorsed needs. We found significant correlations (P ≤ 0.05) between various SDOH needs. Notably, mental health access needs significantly correlated with dental (r = 0.41; 95% CI = 0.19, 0.63), medications (r = 0.51; 95% CI = 0.30, 0.72), utilities (r = 0.39; 95% CI = 0.17, 0.61), and food insecurity (r = 0.42; 95% CI = 0.19, 0.64). Food-housing (r = 0.55; 95% CI = 0.32, 0.78), housing-medications (r = 0.58; 95% CI = 0.35, 0.81), and medications-food (r = 0.53; 95% CI = 0.32, 0.74) were significantly correlated with each other. Longitudinal assessment of patient-reported usefulness informed changes in the resources offered.
UNASSIGNED: Understanding prominent SDOH needs can inform resource offerings and interventions, addressing root causes that burden under-resourced patients. In this study, patient-reported data about resource usefulness prompted the curation of new resources and volunteer roles. This proof-of-concept study shows how longitudinally tracking SDOH needs at low-resource clinics can inform psychosocial resources.

OBJECTIVE: To investigate potential differences in new patient appointment wait times for otolaryngology care based on insurance types and explore factors influencing these wait times.
METHODS: A cross-sectional audit study, using a \"mystery caller\" approach, analyzed with a linear mixed Poisson model to adjust for confounding factors.
METHODS: A total of 612 physicians across 49 states and the District of Columbia, representing 6 otolaryngology subspecialties, were included.
METHODS: Otolaryngology physicians were contacted by mystery callers via telephone with scripted clinical vignettes as patients with either Medicaid or Blue Cross/Blue Shield (BCBS) insurance. Callers requested next available appointment. Wait times for new patient appointments were recorded and analyzed in R using a generalized linear mixed Poisson model.
RESULTS: A total of 1183 of 1224 calls reached a representative. Medicaid patients waited 5.73% longer (P < .001) compared to BCBS patients (IRR: 1.06; confidence interval [CI]: 1.03-1.09; P < .001), with respective mean wait times of 36.8 days (SE ± 1.6) and 32.4 days (SE ± 1.6). Longer waiting times were also associated with physicians affiliated with universities (P = .001) and certain subspecialties, such as pediatric otolaryngology (P < .001) and neurotology (P = .008). Regional differences were also observed, with specific AAO-HNS regions showing shorter wait times. The model achieved a conditional R-squared value of 0.947.
CONCLUSIONS: This study reveals disparities in wait times for otolaryngology care based on insurance type, with extended wait times for Medicaid beneficiaries. The findings highlight a potential access to care disparity, which begets the need for strategies that ensure equitable access to otolaryngology care and further research to understand the underlying reasons for these potential disparities.

BACKGROUND: 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.
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]).
CONCLUSIONS: 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.