Diabetes is associated with liver disease and risk of hepatocellular carcinoma. In this study, we evaluated the association between liver fibrosis measured by transient elastography and four glucose metabolism measures in the Cameron County Hispanic Cohort, a population-based, randomly selected cohort of Mexican American Hispanics with high rates of diabetes and liver cancer. We measured liver fibrosis (a risk factor for hepatocellular carcinoma) in 774 wellcharacterized cohort participants using transient elastography. We evaluated the association of liver fibrosis with glycated hemoglobin (HbA1c), fasting blood glucose, insulin, and insulin resistance using multivariable linear regression models. In multivariable models, log-transformed HbA1c had the strongest association with liver fibrosis (β = 0.37, 95% confidence interval [CI] 0.04-0.69, P = 0.038), after controlling for waist circumference, aspartate aminotransferase, alanine aminotransferase, liver fat, and other known confounders. The association was statistically significant among women (β = 0.33, 95% CI 0.10-0.56, P = 0.009) and similar but nonsignificant among men (β = 0.41, 95% CI −0.17 to 0.98, P = 0.593). Waist circumference, platelet count, aspartate transaminase, and liver steatosis were each associated with liver stiffness. Conclusions: Elevated HbA1c is associated with liver fibrosis, a key risk factor for HCC, particularly among women. Our results indicate that Mexican Americans with uncontrolled HbA1c may benefit from routine screening by liver elastography to identify individuals at risk of liver disease progression. (Hepatology Communications 2020;4:1793-1801).
COVID-19 vaccination is being rapidly rolled out in the US and many other countries, and it is crucial to provide fast and accurate assessment of vaccination coverage and vaccination gaps to make strategic adjustments promoting vaccine coverage. We reported the effective use of real-time geospatial analysis to identify barriers and gaps in COVID-19 vaccination in a minority population living in South Texas on the US-Mexico Border, to inform vaccination campaign strategies. We developed 4 rank-based approaches to evaluate the vaccination gap at the census tract level, which considered both population vulnerability and vaccination priority and eligibility. We identified areas with the highest vaccination gaps using different assessment approaches. Real-time geospatial analysis to identify vaccination gaps is critical to rapidly increase vaccination uptake, and to reach herd immunity in the vulnerable and the vaccine hesitant groups. Our results assisted the City of Brownsville Public Health Department in adjusting real-time targeting of vaccination, gathering coverage assessment, and deploying services to areas identified as high vaccination gap. The analyses and responses can be adopted in other locations.
To investigate practice patterns of use of IC amongst oncologists in treatment of head and neck cancer (HNC) patients. Materials/Methods: An IRB approved survey was sent using Red Cap software to oncologists registered on the American Society of Radiation Oncology (ASTRO) website. Variables were subjected to analysis with Fisher's exact test. Data analysis was considered significant at Bonferroni adjusted pZ0.05 threshold if the p-value was 0.001 and suggestive if p<0.05.The survey was sent to 6818 unique email addresses. Results: The response rate was 14.9% of US and 4.6% of international practitioners. 371 (98.4%) of participants were radiation oncologists. Participants identified as their practice type as Private Practice (23.9%), Academic (44.6%), Hospital Based (30.8%). Level of experience was "still in training" (15.4%), <1 year after completion of training (3.4%), 1-5 years (17.5%), 6-10 years (13.5%), 11-20 years (17.8%), 20-30 years (19.6%), and >30 years (12.7%). 56.8% participants treated >20 HNC patients yearly. 52.5% felt that there are some scenarios where IC improves cancer control and 57.8% felt that there were some scenarios where IC improves quality of life (QOL) outcomes for patients with locally advanced HNC. There was no difference between type of practice or level of training and feelings regarding IC in improving outcomes. Non US practitioners were more likely to feel that IC improved QOL (pZ0.03) and were more likely to use IC (pZ0.005). Increased volume of HNC patients treated was correlated with an increased use of IC (pZ0.001). HNC patient volume was correlated with use of IC in a borderline laryngeal preservation (pZ 0.006), bulky cervical lymph node (pZ0.0005), and optic structure impinging tumor (pZ0.007) case. Variability in use of IC was high. In a patient with a bulky lymph node, 30.5% of respondents rated their willingness to use IC at 0 of a 5 on a 5 point scale, 10.6% at 1, 8% at 2, 11.9% at 3, 15.1% at 4 and 19.9% at 5. In a case with tumor impinging on the optic structures, 25.2% of respondents rated their willingness to use IC at 0 of 5, 9.5% at 1, 12.7% at 2, 14.6% at 3, 17.5% at 4 and 16.7% at 5. After a complete response to IC, doses recommended were 70 Gy (54.6%), >60 but <70 Gy (34.1%), and 60 Gy (8.9%). For a patient with a partial response to IC with a decreased size of a lymph node mass, participants were divided on the dose to treat the areas that were previously involved with tumor, treating with <60 Gy (1.4%), 60 Gy (18%), >60 but <70 Gy (36.3%), 70 Gy (41.1%) and >70 Gy (3.5%). Conclusion: Practice patterns regarding the use of IC were highly varied. IC was most often recommended in patients with bulky cervical lymph node burden or a tumor impinging on the optic structures. Use of IC correlated with patient volume and country of practice.
BACKGROUND The COVID-19 pandemic uncovered the dearth of resources and experience to respond effectively in local health departments, particularly in smaller communities. Publicly available surveillance data, the key information for local health departments, was not sufficiently timely or granular for targeted interventions. The City of Brownsville (COB) is located in a low-income south Texas border county plagued with severe health disparities. The COB, public health department shared local COVID-19 surveillance data weekly with academic partners that produced near real-time weekly geospatial maps of these data. Census tract level case maps were used to strategically target an educational outreach intervention named “Boots on the Ground” (BOG), and application of novel statistical methods were used to evaluate its impact. OBJECTIVE To evaluate the slope (sustained) and intercept (immediate) change in COVID-19 daily test counts 2 weeks pre and post BOG delivery. METHODS Using an interrupted time series design we evaluated the COB census tracts that received targeted BOG between April 21-June 8, 2020. A piece-wise Poisson regression analysis was used to quantify the sustained and immediate change between pre and post BOG COVID-19 daily test count trends. A sensitivity analysis of tracts that did not receive targeted BOG was conducted for comparison purposes. RESULTS During the intervention period, 18 of 48 COB census tracts received targeted BOG. Among these census tracts, significant difference in the slope coefficients from pre- and post-BOG daily test counts was observed in 5 tracts, with 2 tracts having a significant difference in the intercept. Additionally, 80% (4/5) of the significant slope changes showed an increase in pre- and post-slopes. This means the testing trend two weeks post BOG had a sustained increase from the trend two weeks pre-BOG. In the sensitivity analysis of the 30 census tracts not receiving BOG, the opposite was observed. In these tracts, 80% (8/10) of those with significant slope changes had a decrease in the pre- and post-BOG COVID-19 testing slopes. CONCLUSIONS Targeting and evaluation of public health interventions is necessary and possible, particularly in small communities. This report highlights how collaboration between a school of public health and a local health department established and evaluated the impact of a real-time, targeted intervention delivering precision public health to a small community.
e18305 Background: The cost of a full cycle of radiation therapy at MD Anderson Cancer Center has not been determined using a bottom-up measurement approach. Due to the complexity and variation in clinical processes, typical costing strategies do not provide the level of detail necessary to evaluate the value equation, defined as outcomes over cost. To address this limitation, we designed and implemented a practice-wide Time-Driven Activity-Based Costing (TDABC) strategy to capture our total direct cost of care for all treatment modalities within each of 9 disease site-specific services. Methods: Process maps were created for each of the 9 disease site-specific services. Care delivery times were captured by treatment modality for each service as determined by multidisciplinary teams routinely performing each step of the process. The data were entered into a standardized tool, which calculated step costs based upon capacity cost rates for each human resource. The costing tool also calculated total direct labor costs for specific treatment plans based on modality, complexity, and fractionation. Results: The analysis took six months to complete and required the use of approximately 1,000 administrative hours, 250 physician hours, 250 clinical staff hours and 100 medical physics hours. Approximately 17 process maps were created for each of the 9 services with each process map receiving further analysis based upon radiation treatment modality. As a result of observed variation in costs between disease-site services, best practices were identified and 15 standardization opportunities were discovered. Additionally, the cost-benefit analysis between high profile modalities within each disease-site service, such as Proton Therapy and Intensity Modulated Radiation Therapy (IMRT) on the Head and Neck service, were easier to complete. Conclusions: Time-Driven Activity-Based Costing is a valid method for calculating direct costs in a large academic radiation oncology practice. Standardized clinical outcome data can be used to complete the value equation and ultimately provide insight for better clinical and administrative decision making.
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