Disparities in colorectal cancer time-to-treatment and survival time associated with racial and economic residential segregation surrounding the diagnostic hospital, Georgia 2010-2015.

PURPOSE: To evaluate patient-level colorectal cancer outcomes in relation to residential income and racial segregation and composition of the neighborhood surrounding the diagnosing hospitals, and characterize presence of cancer-relevant diagnosis and treatment modalities that might contribute to these associations. METHODS: We utilized Georgia state cancer registry data (2010-2015), matching diagnosis information to hospital technology provided by the American Hospital Association and spatial information to the US Census. We modeled time-to-treatment and survival time, using Cox proportional hazards models, stratified by segregation. Segregation was examined as residential economic and racial evenness (Atkinson index) and isolation (isolation index) and mean income at the Census tract level. To assess possible contributing factors, analysis of hospital diagnosis and treatment technologies in relation to segregation was conducted. RESULTS: Average income of the Census tract and racial residential segregation of the diagnosing hospital's neighborhood was generally unassociated with time-to-treatment or survival time. Higher income evenness around the diagnosing hospital was associated with shorter time-to-treatment, with no association with time-to-death. Higher income isolation for the diagnosing hospital, conversely, was associated with longer times to treatment, but also longer survival times. Hospitals in regions with higher level of residential income segregation were less likely to have a particular diagnosing or treatment technologies, such as virtual colonoscopy and chemotherapy. CONCLUSION: Hospital resources may be a function of their immediate economic environment, and this may have influence on cancer outcomes. Future work should evaluate patient outcomes in light of technologies or therapies utilized within particular economic environments.

Longer time-to-treatment but better survival for colorectal cancer patients presumptively not diagnosed in a hospital.

PURPOSE: To evaluate time-to-treatment and survival time in colorectal cancer (CRC) patients who presumptively were not diagnosed in a hospital. METHODS: Colorectal tumor-level data from Georgia Cancer Registry (GCR) was merged with American Hospital Association data for 2010-2015 using hospital identification number. Patients with tumors lacking a diagnosis hospital in the GCR were classified as presumptive non-hospital diagnosis (PNHD). Cox proportional hazard models were used to model PNHD and time-to-treatment and time-to-death following cancer diagnosis, stratified by race and controlling for personal and tumor characteristics. RESULTS: PNHD (n = 6,885, 29.6%) was associated with a lower likelihood of treatment at a given point in time (i.e., longer time-to-treatment), but did not differ for Black (HR = 0.77, 95% CI: 0.73, 0.82) and White (HR = 0.73, 95% CI: 0.71, 0.76) patients. Time-to-death was longer (i.e., better survival) with PNHD, which also did not differ for Black (HR = 0.70, 95% CI: 0.64, 0.76) and White (HR = 0.71, 95% CI: 0.67, 0.75) patients. These results were not explained by confounding factors or differences in tumor stage at diagnosis. CONCLUSIONS: These observations warrant further research to understand whether there are potentially modifiable factors associated with the diagnosing location that can be used to benefit patient treatment trajectory and survival.

Racial disparities in colorectal cancer time-to-treatment and survival time in relation to diagnosing hospital cancer-related diagnostic and treatment capabilities.

BACKGROUND: There is a need to understand structural issues, such as differential access to or utilization of technologies or capabilities, to better understand racial disparities in cancer outcomes. The objective of this work was to evaluate time-to-treatment and survival in relation to cancer-related diagnostic and treatment technologies of the diagnosing hospital. METHODS: Colorectal tumor-level data from George Cancer Registry was merged with hospital-level cancer technology data from the American Hospital Association (2010-2015). Cox proportional hazard models were used to model time-to-treatment and time-to-death following cancer diagnosis with cancer-related technologies for colon and rectosigmoid/rectal tumors, stratified by race and controlling for personal and tumor characteristics. RESULTS: Black individuals experienced lower likelihood of treatment (HR: 0.92, 95 % CI: 0.89, 0.96) for colon tumors, but not significantly different survival (HR: 1.03, 95 % CI: 0.98, 1.09). Larger capacity or size indicators (total surgical operations, emergency room visits, and licensed beds) were associated with higher likelihood of treatment in whites, but not blacks. Higher counts of treatment related technologies were associated with better survival in whites (HR = 0.92, 95 % CI: 0.85, 0.99), but not blacks (HR: 1.07, 95 % CI: 0.95, 1.19). Virtual colonoscopy emerged as a technology related to survival favorably in whites (HR: 0.84, 95 % CI: 0.77, 0.92) and blacks (HR: 0.89, 95 % CI: 0.79, 1.00). Overall results were similar for rectosigmoid/rectal tumors as observed for colon tumors. CONCLUSION: The role of cancer-related technologies presence or utilization for colorectal cancer outcomes and potential racial disparities warrants further research.

Cyber security risk management: public policy implications of correlated risk, imperfect ability to prove loss, and observability of self-protection.

The correlated nature of security breach risks, the imperfect ability to prove loss from a breach to an insurer, and the inability of insurers and external agents to observe firms' self-protection efforts have posed significant challenges to cyber security risk management. Our analysis finds that a firm invests less than the social optimal levels in self-protection and in insurance when risks are correlated and the ability to prove loss is imperfect. We find that the appropriate social intervention policy to induce a firm to invest at socially optimal levels depends on whether insurers can verify a firm's self-protection levels. If self-protection of a firm is observable to an insurer so that it can design a contract that is contingent on the self-protection level, then self-protection and insurance behave as complements. In this case, a social planner can induce a firm to choose the socially optimal self-protection and insurance levels by offering a subsidy on self-protection. We also find that providing a subsidy on insurance does not provide a similar inducement to a firm. If self-protection of a firm is not observable to an insurer, then self-protection and insurance behave as substitutes. In this case, a social planner should tax the insurance premium to achieve socially optimal results. The results of our analysis hold regardless of whether the insurance market is perfectly competitive or not, implying that solely reforming the currently imperfect insurance market is insufficient to achieve the efficient outcome in cyber security risk management.