Adverse neighborhood conditions play an important role beyond individual characteristics. There is increasing interest in identifying specific characteristics of the social and built environments adversely affecting health outcomes. Most research has assessed aspects of such exposures via self-reported instruments or census data. Potential threats in the local environment may be subject to short-term changes that can only be measured with more nimble technology. The advent of new technologies may offer new opportunities to obtain geospatial data about neighborhoods that may circumvent the limitations of traditional data sources. This overview describes the utility, validity and reliability of selected emerging technologies to measure neighborhood conditions for public health applications. It also describes next steps for future research and opportunities for interventions. The paper presents an overview of the literature on measurement of the built and social environment in public health (Google Street View, webcams, crowdsourcing, remote sensing, social media, unmanned aerial vehicles, and lifespace) and location-based interventions. Emerging technologies such as Google Street View, social media, drones, webcams, and crowdsourcing may serve as effective and inexpensive tools to measure the ever-changing environment. Georeferenced social media responses may help identify where to target intervention activities, but also to passively evaluate their effectiveness. Future studies should measure exposure across key time points during the life-course as part of the exposome paradigm and integrate various types of data sources to measure environmental contexts. By harnessing these technologies, public health research can not only monitor populations and the environment, but intervene using novel strategies to improve the public health.

Background: Delayed medical care may result in adverse health outcomes and increased cost. Our purpose was to identify factors associated with delayed medical care in a primarily rural state. Methods: Using a stratified random sample of 5,300 Nebraska households, we conducted a cross-sectional mailed survey with online response option (27 October 2020 to 8 March 2021) in English and Spanish. Multiple logistic regression models calculated adjusted odds ratios (aOR) and 95% confidence intervals. Results: The overall response rate was 20.8% (n = 1,101). Approximately 37.8% of Nebraskans ever delayed healthcare (cost-related 29.7%, transportation-related 3.7%), with 22.7% delaying care in the past year (10.1% cost-related). Cost-related ever delay was associated with younger age [< 45 years aOR 6.17 (3.24–11.76); 45–64 years aOR 2.36 (1.29–4.32)], low- and middle-income [< $50,000 aOR 2.85 (1.32–6.11); $50,000-$74,999 aOR 3.06 (1.50–6.23)], and no health insurance [aOR 3.56 (1.21–10.49)]. Transportation delays were associated with being non-White [aOR 8.07 (1.54–42.20)], no bachelor’s degree [≤ high school aOR 3.06 (1.02–9.18); some college aOR 4.16 (1.32–13.12)], and income < $50,000 [aOR 8.44 (2.18–32.63)]. Those who did not have a primary care provider were 80% less likely to have transportation delays [aOR 0.20 (0.05–0.80)]. Conclusions: Delayed care affects more than one-third of Nebraskans, primarily due to financial concerns, and impacting low- and middle-income families. Transportation-related delays are associated with more indicators of low socio-economic status. Policies targeting minorities and those with low- and middle-income, such as Medicaid expansion, would contribute to addressing disparities resulting from delayed care.

BACKGROUND: Debate exists regarding the role of robotic-assisted surgery in colorectal cancer. Robotic-assisted surgery has been promoted as a strategy to increase the availability of minimally invasive surgery, which is associated with improved short-term morbidity; however, robotic-assisted surgery is much more expensive than laparoscopic surgery. OBJECTIVE: We aimed to understand hospital and patient trends in the adoption of robotic-assisted surgery. DESIGN: The study used cross-sectional and longitudinal designs. SETTINGS: The study included 2010 and 2012 American Hospital Association surveys, as well as the 2010–2012 Nationwide Inpatient Sample. PATIENTS: US hospitals responding to the American Hospital Association survey were included to measure patients with colorectal cancer who were undergoing elective minimally invasive surgery or open resection. MAIN OUTCOME MEASURES: Robotic-assisted surgery adoption by US hospitals was measured, regarding specifically patients with colorectal cancer who were treated with robotic surgery. RESULTS: In 2010, 20.1% of hospitals adopted robotic-assisted surgery, increasing to 27.4% by 2012. Hospitals more likely to adopt robotic-assisted surgery included teaching hospitals, those with more advanced imaging services, those in metropolitan rather than rural areas, and those performing the highest inpatient surgery volume. Robotic-assisted surgery only accounted for 1.3% of colorectal cancer operations during 2010–2012, but patient probability of robotic-assisted surgery ranged from 0.1% to 15.2%. The percentage of patients with colorectal cancer who were treated robotically among those undergoing minimally invasive surgery increased over time (2010, 1.5%; 2012, 3.6%). Robotic-assisted surgery is increasing more rapidly for patients with rectal cancer with minimally invasive surgery (2010, 5.5%; 2012, 13.3%) versus patients with colon cancer treated with minimally invasive surgery (2010, 1.3%; 2012, 3.3%). LIMITATIONS: The study was limited by its observational study design. CONCLUSIONS: Robotic-assisted surgery uptake remains low for colon cancer but higher for rectal cancer surgery, suggesting a more thoughtful adoption of robotic-assisted surgery for colorectal cancer by focusing its use on more technically challenging cases.

BACKGROUND: Surgical resection is the primary treatment for colon cancer, but use of laparoscopic approaches varies widely despite demonstrated short- and long-term benefits. OBJECTIVE: The purpose of this study was to identify characteristics associated with laparoscopic colon cancer resection and to quantify variation based on patient, hospital, and geographic characteristics. DESIGN: Bayesian cross-classified, multilevel logistic models calculated adjusted ORs and CIs for patient, surgeon, hospital, and geographic characteristics and unexplained variability (predicted vs. observed values) using adjusted median odds ratios for hospitals and counties. SETTINGS: The Surveillance, Epidemiology, and End Results–Medicare claims database (2008–2011) supplemented with county-level American Community Survey (2008–2012) demographic data was used. PATIENTS: A total of 10,618 patients ≥66 years old who underwent colon cancer resection were included. MAIN OUTCOME MEASURES: Nonurgent/nonemergent resections for colon cancer patients ≥66 years old were classified as laparoscopic or open procedures. RESULTS: Patients resided in 579 counties and used 950 hospitals; 47% of patients underwent laparoscopic surgery. Medicare/Medicaid dual enrollment, age ≥85 years, and higher tumor stage and grade were negatively associated with laparoscopic surgery receipt; proximal tumors and increasing hospital size and surgeon caseload were positively associated. Significant unexplained variability at the hospital (adjusted median OR = 3.31; p < 0.001) and county levels (adjusted median OR = 1.28; p < 0.05) remained after adjustment. LIMITATIONS: This was an observational study lacking generalizability to younger patients without Medicare or those with Health Maintenance Organization coverage and data set did not reflect national hospital studies or hospital volume. In addition, we were unable to account for specific types of comorbidities, such as obesity, and had broad categories for surgeon caseload. CONCLUSIONS: Determining sources of hospital-level variation among poor insured patients may help increase laparoscopic resection to maximize health outcomes and reduce cost. See Video Abstract at http://links.lww.com/DCR/A363.

Purpose: Rural (vs urban) patients experience poorer cancer outcomes and are less likely to be engaged in cancer prevention, such as screening. As part of a community needs assessment, we explored rural cancer survivors’ and caregivers’ experiences, perceptions, and attitudes toward cancer care services.Methods: We conducted 3 focus groups (N = 20) in Spring 2021 in rural Nebraska.Findings: Three patterns of cancer diagnosis were regular care/screening without noticeable symptoms, treatment for symptoms not initially identified as cancer related, and symptom self‐identification. Most participants, regardless of how diagnosis was made, had positive experiences with timely referral for testing (imaging and biopsy) and specialist care. Physician interpersonal skills set the tone for patient‐provider communication, which colored the perception of overall care. Participants with physicians and care teams that were perceived as “considerate,” “compassionate,” and “caring” had positive experiences. Participants identified specific obstacles to care, including financial barriers, transportation, and lack of support groups, as well as more general cultural barriers. Survivors and caregivers identified organization‐based supports that helped them address such barriers.Conclusions: Rural populations have unique perspectives about cancer care. Our results are being used by the state cancer coalition, state cancer control program, and the National Cancer Institute‐designated cancer center to prioritize outreach and interventions aimed to reduce rural cancer disparities, such as revitalizing lay cancer navigator programs, conducting webinars for primary care and cancer specialty providers to discuss these findings and identify potential interventions, and collaborating with national and regional cancer support organizations to expand reach in rural communities.