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Introduction Population-level screening has been shown to reduce the incidence and mortality of colorectal cancer (CRC). Unfortunately, adherence to screening recommendations among eligible US adults remains below national goals. A relatively new non-invasive screening modality, the Food and Drug Administration–approved multi-target stool DNA (mt-sDNA) assay (commercialised as Cologuard), which combines the detection of haemoglobin and DNA abnormalities, has been completed by more than 3 million individuals. Given mt-sDNA’s recent availability, the effectiveness of mt-sDNA screening with respect to CRC incidence and mortality reduction has not yet been established. Methods and analysis Through an academic–industry collaboration, a prospective cohort study (Voyage) was designed with an initial enrolment target of 150 000 individuals with mt-sDNA ordered by their healthcare provider for CRC screening. Consented participants will be asked to complete a baseline questionnaire to collect sociodemographic and health information. Additional questionnaires will be provided after 1 year, and every 3 years thereafter, to collect data regarding CRC screening follow-up in order to estimate rates of CRC incidence and other health outcomes. Linkage to the National Death Index will be used to estimate mortality rates. Ethics and dissemination The Voyage study will be conducted in accordance with international guidelines and local regulatory requirements and laws. Data will be stored and retained at Mayo Clinic. Only limited data elements required for research purposes will be transmitted between Mayo Clinic and Exact Sciences Laboratories. Results of the Voyage study will be disseminated through scientific presentations and publications. Trial registration number NCT04124406.

Objective: During the past decade, the availability of health information online has increased dramatically. We assessed progress toward the Healthy People 2020 (HP2020) health communication and health information technology objective of increasing the proportion of health information seekers who easily access health information online. Methods: We used data from 4 administrations of the Health Information National Trends Survey (HINTS 2008-2017) (N = 18 103). We conducted multivariable logistic regression analysis to evaluate trends over time in experiences with accessing health information and to examine differences by sociodemographic variables (sex, age, race/ethnicity, education, income, metropolitan status) separately for those who used the internet (vs other information sources) during their most recent search for health information. Results: Among US adults who looked for health information and used the internet for their most recent search, the percentage who reported accessing health information without frustration was stable during the study period (from 37.2% in 2008 to 38.5% in 2017). Accessing information online without frustration was significantly and independently associated with age 35-49 (vs age 18-34) (odds ratio [OR] = 1.34; 95% confidence interval [CI], 1.03 -1.73), non-Hispanic black (vs non-Hispanic white) race/ethnicity (OR = 2.15; 95% CI, 1.55-2.97), and annual household income <$20 000 (vs >$75 000) (OR = 0.66; 95% CI, 0.47-0.93). The percentage of adults who used an information source other than the internet and reported accessing health information online without frustration ranged from 31.3% in 2008 to 42.7% in 2017. Survey year 2017 (vs 2008) (OR = 1.61; 95% CI, 1.09-2.35) and high school graduate education (vs college graduate) (OR = 0.69; 95% CI, 0.49-0.97) were significantly and independently associated with accessing health information without frustration from sources other than the internet. Conclusions: The percentage of online health information seekers reporting easily accessing health information did not meet the HP2020 objective. Continued efforts are needed to enable easy access to online health information among diverse populations.

Objective: Much has been written about the patients’ perspective concerning weight management in health care. The purpose of this survey study was to assess perspectives of primary care providers (PCPs) and nurses toward patient weight management and identify possible areas of growth. Patients and Methods: We emailed a weight management–focused survey to 674 eligible participants (437 [64.8%] nurses and 237 [35.2%] PCPs) located in 5 outpatient primary care clinics. The survey focused on opportunities, practices, knowledge, confidence, attitudes, and beliefs. A total of 219 surveys were returned (137 [62.6%] from nurses and 82 [34.4%] from PCPs). Results: Among 219 responders, 85.8% were female and 93.6% were white non-Hispanic. In this study, PCPs and nurses believed obesity to be a major health problem. While PCPs felt more equipped than nurses to address weight management ( P < .001) and reported receiving more training than nurses (50.0% vs 17.6%, respectively), both felt the need for more training on obesity (73.8% and 79.4%, respectively). Although, PCPs also spent more patient contact time providing weight management services versus nurses ( P < .001), the opportunity/practices score was lower for PCPs than nurses (−0.35 ± 0.44 vs −0.17 ± 0.41, P < .001) with PCPs more likely to say they lacked the time to discuss weight and they worried it would cause a poor patient-PCP relationship. The knowledge/confidence score also differed significantly between the groups, with nurses feeling less equipped to deal with weight management issues than PCPs (−0.42 ± 0.43 vs −0.03 ± 0.55, P < .001). Neither group seemed very confident, with those in the PCP group only answering with an average score of neutral. Conclusion: By asking nurses and PCP general questions about experiences, attitudes, knowledge, and opinions concerning weight management in clinical care, this survey has identified areas for growth in obesity management. Both PCPs and nurses would benefit from additional educational training on weight management.

Objective: To understand the interaction of multimorbidity and functional limitations in determining health-care utilization and survival in older adults. Methods: Olmsted County, Minnesota, residents aged 60–89 years in 2005 were categorized into four cohorts based on the presence or absence of multimorbidity (≥3 chronic conditions from a list of 18) and functional limitations (≥1 limitation in an activity of daily living from a list of 9), and were followed through December 31, 2016. Andersen–Gill and Cox regression estimated hazard ratios (HRs) for emergency department (ED) visits, hospitalizations, and death using persons with neither multimorbidity nor functional limitations as the reference (interaction analyses). Results: Among 13,145 persons, 34% had neither multimorbidity nor functional limitations, 44% had multimorbidity only, 4% had functional limitations only, and 18% had both. Over a median follow-up of 11 years, 5906 ED visits, 2654 hospitalizations, and 4559 deaths occurred. Synergistic interactions on an additive scale of multimorbidity and functional limitations were observed for all outcomes; however, the magnitude of the interactions decreased with advancing age. The HR (95% confidence interval) for death among persons with both multimorbidity and functional limitations was 5.34 (4.40–6.47) at age 60–69, 4.16 (3.59–4.83) at age 70–79, and 2.86 (2.45–3.35) at age 80–89 years. Conclusion: The risk of ED visits, hospitalizations, and death among persons with both multimorbidity and functional limitations is greater than additive. The magnitude of the interaction was strongest for the youngest age group, highlighting the importance of interventions to prevent and effectively manage multimorbidity and functional limitations early in life.

Background: Previous studies have indicated that living in a rural or non-urban area may be associated with poor health outcomes. However, data on rurality and death in heart failure (HF) are scarce. Methods: Residents from 11 southeast MN counties with a first-ever code for HF (including codes ICD-9 428 and ICD-10 I50) between 1/1/2013 and 12/31/2016 were identified. Resident address was geo-coded and classified according to the Rural-Urban Commuting Area (RUCA) codes, which classifies US census tracts to measure population density, urbanization and daily commuting. Rurality was defined as living in a non-metropolitan area. Cox proportional hazards regression was used to determine the association between living in a rural vs. urban area and death. Results: Among 6,996 patients (mean age 73 years, 52% male), 54% of patients lived in a rural area. These patients were older and had a lower level of educational attainment and comorbidity burden (p<0.001). After a mean (SD) follow-up of 2.9 (1.3) years, 1,856 deaths occurred. Living in a rural area was univariately associated with a higher risk of death (HR 1.20, 95% CI: 1.09-1.31; Table). After adjustment for age, sex, education status and comorbidity burden, rurality remained associated with an increased risk of death (HR 1.15; 95% CI: 1.04-1.27). Conclusions: Among patients with HF, living in a rural area is associated with an increased risk of death. Further study to identify and address the mechanisms through which rural residence influences mortality in patients with HF is needed.

Background: In 2012, updated cervical cancer screening recommendations were released with consensus on Papanicolaou (Pap) testing every 3 years for women age 21–65 years or Pap–human papillomavirus (HPV) cotesting at 5-year intervals for women age 30–65 years. Primary study aims: Assess current use of Pap-HPV cotesting and describe local population trends over time in Pap and Pap-HPV cotesting. Secondary aim: Assess sociodemographic factors correlating with screening. Methods: We assessed Rochester Epidemiology Project data for Pap and Pap-HPV cotesting among women age 16 years and older living in Olmsted County, Minnesota, yearly from 2005 (study population n = 47,203) through 2016 (study population n = 49,510). We calculated 3-year (Pap) and 5-year (Pap-HPV) moving prevalence rates of screening as proportion of eligible population. Multivariable logistic regression was used to assess factors potentially associated with screening. Results: In 2016, 64.6% of 27,418 eligible 30- to 65-year-old women were up to date with cervical cancer screening; 60.8% had received Pap-HPV cotest screening. Significant declines in Pap completion rates over time were observed in all age groups, including an unexpected decline in 21- to 29-year-old women. Coincident with decreasing Pap screening rates, Pap-HPV cotesting significantly increased among women age 30–65 years, from 10.0% in 2007 to 60.8% in 2016. Conclusions: This suggests increasing adoption of 2012 screening recommendations in the 30- to 65-year-old population. However, decline in Pap screening among 21- to 29-year-old women is concerning. Disparities by race, ethnicity, smoking status, and comorbidity level were observed. Results suggest need for multilevel patient and clinician interventions to increase cervical cancer screening adherence.