The Role of Imaging in Health Screening: Overview, Rationale of Screening, and Screening Economics

Prevalence and clinical significance of incidental findings in chest and abdominopelvic CT scans of trauma patients; A cross-sectional study

BACKGROUND

Imaging may inadvertently reveal pathologies unrelated to their performing purpose, known as incidental findings (IF). This study aimed to assess the prevalence, clinical significance, and documentation of IFs in chest and abdominopelvic computed tomography (CT) scans of trauma patients.

METHODS

This observational study was conducted at two urban level-1 trauma centers from March 2019 through April 2022. Official radiology reports of trauma patients who underwent chest and/or abdominopelvic CT scans at the emergency department (ED) were explored, and IF were extracted. Predictive factors of the presence of IFs and their documenting were investigated.

RESULTS

Out of 656 chest and 658 abdominopelvic CT scans, 167 (25.37%) and 212 (32.31%) scans harbored at least one IF, respectively. Patients with IFs tended to be of higher age and female in both chest (age: 48 [IQR: 35-62] vs. 34 [IQR: 25-42.5]; female: 31.14% vs 14.66%, p < 0.001 for both) and abdominopelvic CT scans (age: 41 [IQR: 30-57.5] vs 33 [IQR: 25-43], female: 26.42% vs. 13.96%, p < 0.001 for both). As for documentation of significant IFs, only 49 of 112 chest IFs (43.8%) and 55 of 176 abdominopelvic IFs (31.3%) were documented. Investigating factors associated with documentation of clinically significant IFs, shorter length of hospital stay (1.5 (IQR: 0-4) vs. 3 (IQR: 2-8), p = 0.003), and discharging by ED physicians (documentation rate: 13.2% vs 42.6%, p < 0.001) were associated with poorer documentation of IFs only in abdominopelvic scans.

CONCLUSION

CT imaging in ED trauma patients often reveals incidental findings, especially in older patients. Over 50% of these findings are clinically significant, yet they are frequently ignored and not documented. Physicians need to be more vigilant in recognizing and documenting these incidental findings and informing patients of the need for further evaluation.

Health Systems Science - A Primer for Radiologists

Health systems science (HSS) is an educational framework designed to promote improved care through enhanced citizenship and the training of systems-fluent individuals trained in the science of health care delivery.  HSS education in residency builds upon foundations established during medical school, emphasizing practical skills development, and fostering a growth mindset among trainees.  The HSS framework organizes elements of system-based practice for radiology trainees, promoting practice-readiness for providing safe, timely, effective, efficient, equitable and patient centered radiological care. This paper serves as a primer for radiologists to understand and apply the HSS framework. Additionally, we highlight radiology-specific curricular elements aligned with the HSS framework, and provide teaching resources both for classroom education and for resident self-study.

Health Demand: Empirical Study of Effective Urban Households Demand in Indonesia

BACKGROUND: Grossman's health demand model recognizes medical price as a determinant of the estimation model. This article aims to examine the role of medical expenses in health demand by utilizing the number of sick and disturbed days obtained from Susenas, a survey on the expenditure of household food and non-food consumption conducted by the Central Bureau of Statistics to measure health demand and health insurance as a medical price in a reduction model. Health insurance can replace medical expenses because those who have health insurance face relatively low medical costs and face lower medical prices than those without health insurance.   METHODS: Using the Ordinary Least Squares (OLS) estimation technique, sebuah teknik estimasi model regresi for 6,642 households this was obtained through three stages: First, using 71,932 sample households of susenas that relied fully on the Susenas sampling method by BPS; Second, find households that have experienced health problems during the last 6 months; Third, find households that have health expenditures of 24,341. Furthermore, the estimation model is based on 6,642 households identified to be in urban areas using the Ordinary Least Squares (OLS) estimation method.   FINDINGS: The health demand estimation model that can be used to determine the behavior of health demand among urban households is limited to households with formal primary school (SD) education levels. Taking advantage of certain wages, age, cigarette expenditure, and sports expenses, it was found that the number of sick days and felt disturbed in the household group that had health insurance was 5.68 days relatively greater than those without health insurance. However, expanding to higher education and older age was found to be 1.47 days and 1.57 days. Aging tends to decrease good health and health insurance tends to increase it.   CONCLUSION: It was found that health stocks differed between insured households and households without health insurance in those with aging.

Lung Cancer Screening with Low-Dose CT in Smokers: A Systematic Review and Meta-Analysis

Lung cancer continues to be one of the main causes of cancer death in Europe. Low-dose computed tomography (LDCT) has shown high potential for screening of lung cancer in smokers, most recently in two European trials. The aim of this review was to assess lung cancer screening of smokers by LDCT with respect to clinical effectiveness, radiological procedures, quality of life, and changes in smoking behavior. We searched electronic databases in April 2020 for publications of randomized controlled trials (RCT) reporting on lung cancer and overall mortality, lung cancer morbidity, and harms of LDCT screening. A meta-analysis was performed to estimate effects on mortality. Forty-three publications on 10 RCTs were included. The meta-analysis of eight studies showed a statistically significant relative reduction of lung cancer mortality of 12% in the screening group (risk ratio = 0.88; 95% CI: 0.79-0.97). Between 4% and 24% of screening-LDCT scans were classified as positive, and 84-96% of them turned out to be false positive. The risk of overdiagnosis was estimated between 19% and 69% of diagnosed lung cancers. Lung cancer screening can reduce disease-specific mortality in (former) smokers when stringent requirements and quality standards for performance are met.