Insurance status and high-volume surgical cancer: Access to high-quality cancer care

Beyond the sarcoma center: establishing the Sarcoma HASM network-a Hub and Spoke Model network for global integrated and precision care

The landscape of sarcoma treatment has evolved significantly, transitioning from amputations to limb-sparing surgeries, underpinned by advancements in multidisciplinary strategies. The establishment of specialized sarcoma centers has been pivotal, though challenges in accessibility and expertise persist. This manuscript proposes the Sarcoma Hub and Spoke Model (HASM) network to address these issues, enhancing coordination and expanding access to specialized care. The HASM network centralizes complex case management at hubs while peripheral spokes manage routine diagnostics and treatments, optimizing resource use and ensuring patient-centered care. Integration with digital interoperable platforms facilitates real-time/real-world data exchange, supports multidisciplinary team meetings, and enables advanced predictive analytics such as Sarcoma Digital Twins and causal machine learning for personalized treatment. The Sarcoma Care Data Warehouse further enhances this model by aggregating comprehensive patient data, supporting quality assessment and continuous improvement. This innovative approach aims to set a new standard for sarcoma care, leveraging technology and collaborative expertise to improve outcomes globally.

Identifying Populations at Risk for Lung Cancer Mortality from the National Health and Nutrition Examination Survey (2001-2018) Using the 2021 USPSTF Screening Guidelines

Lung cancer (LC) is the leading cause of cancer mortality in the United States. To combat this predicament, early screening and critically assessing its risk factors remain crucial. The aim of this study was to identify the value of specific factors from the National Health and Nutrition Examination Survey (NHANES) from 2001-2018, as they relate to lung cancer mortality in the US Preventive Services Task Force (USPSTF)-eligible population. A total of 3545 adults who met USPSTF criteria were extracted from 81,595 NHANES participants. The LC Death Risk Assessment Tool was used to calculate the number of deaths per 1000 individuals. The Mann-Whitney U test and one-way ANOVA determined the statistical significance of the factors involved in LC mortality. Male sex, African and Hispanic ethnicity, lower education attainment, and secondhand exposure to cigarette smoke correlated with an increased risk of LC mortality. Additionally, the factor of emotional support from NHANES data was analyzed and did not show any benefit to reducing risk. By identifying individuals at high-risk, preventative measures can be maximized to produce the best possible outcome.

Influence of Health Insurance Types on Clinical Cancer Care Accessibility and Quality Using All of Us Database

Background and Objectives: Cancer, as the second leading cause of death in the United States, poses a huge healthcare burden. Barriers to access to advanced therapies influence the outcome of cancer treatment. In this study, we examined whether insurance types affect the quality of cancer clinical care. Materials and Methods: Data for 13,340 cancer patients with Purchased or Medicaid insurance from the All of Us database were collected for this study. The chi-squared test of proportions was employed to determine the significance of patient cohort characteristics and the accessibility of healthcare services between the Purchased and Medicaid insurance groups. Results: Cancer patients who are African American, with lower socioeconomic status, or with lower educational attainment are more likely to be insured by Medicaid. An analysis of the survey questions demonstrated the relationship between income and education level and insurance type, as Medicaid cancer patients were less likely to receive primary care and specialist physician access and more likely to request lower-cost medications. Conclusions: The inequities of the US healthcare system are observed for cancer patient care; access to physicians and medications is highly varied and dependent on insurance types. Socioeconomic factors further influence insurance types, generating a significant impact on the overall clinical care quality for cancer patients that eventually determines treatment outcomes and the quality of life.