Characterizing geographic access depends on a broad range of methods available to researchers and the healthcare context to which the method is applied. Globally, travel time is one frequently used measure of geographic access with known limitations associated with data availability. Specifically, due to lack of available utilization data, many travel time studies assume that patients use the closest facility. To examine this assumption, an example using mammography screening data, which is considered a geographically abundant health care service in the United States, is explored. This work makes an important methodological contribution to measuring access—which is a critical component of health care planning and equity almost everywhere. We analyzed one mammogram from each of 646,553 women participating in the US based Breast Cancer Surveillance Consortium for years 2005–2012. We geocoded each record to street level address data in order to calculate travel time to the closest and to the actually used mammography facility. Travel time between the closest and the actual facility used was explored by woman-level and facility characteristics. Only 35 % of women in the study population used their closest facility, but nearly three-quarters of women not using their closest facility used a facility within 5 min of the closest facility. Individuals that by-passed the closest facility tended to live in an urban core, within higher income neighborhoods, or in areas where the average travel times to work was longer. Those living in small towns or isolated rural areas had longer closer and actual median drive times. Since the majority of US women accessed a facility within a few minutes of their closest facility this suggests that distance to the closest facility may serve as an adequate proxy for utilization studies of geographically abundant services like mammography in areas where the transportation networks are well established.

The COVID-19 (coronavirus disease 2019) pandemic has expanded telehealth utilization in unprecedented ways and has important implications for measuring geographic access to healthcare services. Established measures of geographic access to care have focused on the spatial impedance of patients in seeking health care that pertains to specific transportation modes and do not account for the underlying broadband network that supports telemedicine and e-health. To be able to measure the impact of telehealth on healthcare access, we created a pilot augmentation of existing methods to incorporate measures of broadband accessibility to measure geographic access to telehealth. A reliable measure of telehealth accessibility is important to enable policy analysts to assess whether the increasing prevalence of telehealth may help alleviate the disparities in healthcare access in rural areas and for disadvantaged populations, or exacerbate the existing gaps as they experience “double burdens.”

Racial disparities in breast reconstruction for breast cancer are documented. Place of service has contributed to disparities in cancer care; but the interaction of race/ethnicity and place of service has not been explicitly examined. We examined whether place of service modified the effect of race/ethnicity on receipt of reconstruction. We included women with a mastectomy for incident breast cancer in SEER-Medicare from 2005–2009. Using Medicare claims, we determined breast reconstruction within 6 months. Facility characteristics included: rural/urban location, teaching status, NCI Cancer Center designation, cooperative oncology group membership, Disproportionate Share Hospital (DSH) status, and breast surgery volume. Using multivariable logistic regression, we analyzed reconstruction in relation to minority status and facility characteristics. Of the 17,958 women, 14.2% were racial/ethnic women of color and a total of 9.3% had reconstruction. Caucasians disproportionately received care at non-teaching hospitals (53% v. 42%) and did not at Disproportionate Share Hospitals (77% v. 86%). Women of color had 55% lower odds of reconstruction than Caucasians (OR = 0.45; 95% CI 0.37-0.55). Those in lower median income areas had lower odds of receiving reconstruction, regardless of race/ethnicity. Odds of reconstruction reduced at rural, non-teaching and cooperative oncology group hospitals, and lower surgery volume facilities. Facility effects on odds of reconstruction were similar in analyses stratified by race/ethnicity status. Race/ethnicity and facility characteristics have independent effects on utilization of breast reconstruction, with no significant interaction. This suggests that, regardless of a woman’s race/ethnicity, the place of service influences the likelihood of reconstruction.

Purpose: To review the childhood risk factors for pediatric cancer (diagnosis before age 20). Methods: We conducted literature searches using Ovid Medline and Scopus to find primary research studies, review articles, and meta-analyses published from 2014 to 3 March 2021. Results: Strong evidence indicates that an array of genetic and epigenetic phenomena, structural birth defects, and chromosomal anomalies are associated with an increased risk of various childhood cancers. Increased risk is also associated with prior cancer, likely due to previous treatment agents and therapeutic ionizing radiation. Convincing evidence supports associations between several pediatric cancers and ionizing radiation, immunosuppression, and carcinogenic virus infection both in healthy children and in association with immune suppression following organ transplantation. Breastfeeding and a childhood diet rich in fruits and vegetables appears to reduce the risk of pediatric leukemia but the evidence is less strong. Childhood vaccination against carcinogenic viruses is associated with a lower risk of several cancers; there is less strong evidence that other childhood vaccinations more broadly may also lower risk. Ultraviolet (UV) radiation is associated with increased melanoma risk, although most melanomas following childhood UV exposure occur later, in adulthood. Evidence is weak or conflicting for the role of body mass index, other childhood infections, allergies, and certain treatments, including immunomodulator medications and human growth therapy.

Breast cancer in the U.S. - estimated at 232,670 incident cases in 2014 - has the highest aggregate economic burden of care relative to other female cancers. Yet, the amount of cost attributed to diagnostic/preoperative work up has not been characterized. We examined the costs of imaging and biopsy among women enrolled in Medicare who did and did not receive diagnostic/preoperative Magnetic Resonance Imaging (MRI). Using Surveillance, Epidemiology and End Results (SEER)- Medicare data, we compared the per capita costs (PCC) based on amount paid, between diagnosis date and primary surgical treatment for a breast cancer diagnosis (2005–2009) with and without diagnostic/preoperative MRI. We compared the groups with and without MRI using multivariable models, adjusting for woman and tumor characteristics. Of the 53,653 women in the cohort, within the diagnostic/preoperative window, 20 % (N = 10,776) received diagnostic/preoperative MRI. Total unadjusted median costs were almost double for women with MRI vs. without ($2,251 vs. $1,152). Adjusted costs were higher among women receiving MRI, with significant differences in total costs ($1,065), imaging costs ($928), and biopsies costs ($138). Costs of diagnostic/preoperative workups among women with MRI are higher than those without. Using these cost estimates in comparative effectiveness models should be considered when assessing the benefits and harms of diagnostic/preoperative MRI.