This study employed the Delphi method, an exploratory method used for group consensus building, to determine the benefits and challenges associated with community engagement in patient-centered outcomes research.

A series of email surveys were sent to the Patient-Centered Outcomes Research Institute (PCORI)-funded researchers (n = 103) in New England. Consensus was achieved through gathering themes and engaging participants in ranking their level of agreement over three rounds. In round one, participant responses were coded thematically and then tallied. In round two participants were asked to state their level of agreement with each of the themes using a Likert scale. Finally, in round three, the group was asked to rank the round two themes based on potential impact.

Results suggested the greatest benefit of community engagement is that it brings multiple perspectives to the table, with 92% ranking it as the first or second most important contribution. Time was ranked as the most significant barrier to engaging community. Strategies to overcome barriers to community engagement include engaging key stakeholders early in the research, being kind and respectful and spending time with stakeholders. The most significant finding was that no researchers reported having specific measures to evaluate community engagement.

Community engagement can enhance both research relevance and methodology when researchers are engaged in meaningful collaborations. Advancing the science of community engagement will require the development of evaluation metrics to examine the multiple domains of partnership.

The application of digital monitoring biomarkers in health, wellness and disease management is reviewed. Harnessing the near limitless capacity of these approaches in the managed healthcare continuum will benefit from a systems-based architecture which presents data quality, quantity, and ease of capture within a decision-making dashboard.

A framework was developed which stratifies key components and advances the concept of contextualized biomarkers. The framework codifies how direct, indirect, composite, and contextualized composite data can drive innovation for the application of digital biomarkers in healthcare.

The de novo framework implies consideration of physiological, behavioral, and environmental factors in the context of biomarker capture and analysis. Application in disease and wellness is highlighted, and incorporation in clinical feedback loops and closed-loop systems is illustrated.

The study of contextualized biomarkers has the potential to offer rich and insightful data for clinical decision making. Moreover, advancement of the field will benefit from innovation at the intersection of medicine, engineering, and science. Technological developments in this dynamic field will thus fuel its logical evolution guided by inputs from patients, physicians, healthcare providers, end-payors, actuarists, medical device manufacturers, and drug companies.

To identify potential participants for clinical trials, electronic health records (EHRs) are searched at potential sites. As an alternative, we investigated using medical devices used for real-time diagnostic decisions for trial enrollment.

To project cohorts for a trial in acute coronary syndromes (ACS), we used electrocardiograph-based algorithms that identify ACS or ST elevation myocardial infarction (STEMI) that prompt clinicians to offer patients trial enrollment. We searched six hospitals’ electrocardiograph systems for electrocardiograms (ECGs) meeting the planned trial’s enrollment criterion: ECGs with STEMI or > 75% probability of ACS by the acute cardiac ischemia time-insensitive predictive instrument (ACI-TIPI). We revised the ACI-TIPI regression to require only data directly from the electrocardiograph, the e-ACI-TIPI using the same data used for the original ACI-TIPI (development set n = 3,453; test set n = 2,315). We also tested both on data from emergency department electrocardiographs from across the US (n = 8,556). We then used ACI-TIPI and e-ACI-TIPI to identify potential cohorts for the ACS trial and compared performance to cohorts from EHR data at the hospitals.

Receiver-operating characteristic (ROC) curve areas on the test set were excellent, 0.89 for ACI-TIPI and 0.84 for the e-ACI-TIPI, as was calibration. On the national electrocardiographic database, ROC areas were 0.78 and 0.69, respectively, and with very good calibration. When tested for detection of patients with > 75% ACS probability, both electrocardiograph-based methods identified eligible patients well, and better than did EHRs.

Using data from medical devices such as electrocardiographs may provide accurate projections of available cohorts for clinical trials.

Computational analysis of genome or exome sequences may improve inherited disease diagnosis, but is costly and time-consuming.

We describe the use of iobio, a web-based tool suite for intuitive, real-time genome diagnostic analyses.

We used iobio to identify the disease-causing variant in a patient with early infantile epileptic encephalopathy with prior nondiagnostic genetic testing.

Iobio tools can be used by clinicians to rapidly identify disease-causing variants from genomic patient sequencing data.

The objective of this study was to systematically assess the literature regarding postnatal healthcare utilization and barriers/facilitators of healthcare in neonatal abstinence syndrome (NAS) children.

A systematic search was performed in PubMed, Cochrane Database of Systematic Reviews, PsychINFO, Cumulative Index to Nursing and Allied Health Literature (CINAHL), and Web of Science to identify peer-reviewed research. Eligible studies were peer-reviewed articles reporting on broad aspects of primary and specialty healthcare utilization and access in NAS children. Three investigators independently reviewed all articles and extracted data. Study bias was assessed using the Newcastle–Ottawa Assessment Scale and the National Institute of Health Study Quality Assessment Tool.

This review identified 14 articles that met criteria. NAS children have poorer outpatient appointment adherence and have a higher rate of being lost to follow-up. These children have overall poorer health indicated by a significantly higher risk of ER visits, hospital readmission, and early childhood mortality compared with non-NAS infants. Intensive multidisciplinary support provided through outpatient weaning programs facilitates healthcare utilization and could serve as a model that could be applied to other healthcare fields to improve the health among this population.

This review investigated the difficulties in accessing outpatient care as well as the utilization of such care for NAS infants. NAS infants tend to have decreased access to and utilization of outpatient healthcare following hospital birth discharge. Outpatient weaning programs have proven to be effective; however, these programs require intensive resources and care coordination that has yet to be implemented into other healthcare areas for NAS children.

Little is known about designing research recruitment campaigns that connect with underserved, geographically isolated rural populations. A theoretically informed process is needed to assist research teams and practitioners in their evaluation of Facebook’s feasibility as a recruitment tool and development of online materials for recruiting rural adults into healthcare delivery intervention development studies.

We drew from research and theory in communication and incorporated process analysis techniques to develop replicable procedures for designing and evaluating Facebook campaigns for rural recruitment. We describe our process and illustrate using two case studies.

Campaigns received approximately 1000 link clicks from the target rural demographic and successfully enrolled participants using Facebook as a primary method of recruitment. The rural tobacco intervention development study received a total of 477 link clicks, cost only $155.80, and enrolled three (23%) of its 13 participants from Facebook. The rural mental health intervention development study received a total of 518 link clicks, cost only $233.28, and enrolled 178 participants.

Our process yielded two successful recruitment campaigns. Facebook was an affordable and efficacious strategy for enrolling adults in behavioral research studies on tobacco and mental health. Future work should apply these theoretical techniques to additional study topics and evaluate specific message features associated with recruitment.

Prior studies indicate greater disease burden for obesity among rural compared with urban residents but no differences for mood disorder based on geographic location. Recent attention has focused on the need to examine regional rural–urban disparities in disease burden. We focused on mood disorders and obesity prevalence within three southeastern Minnesota counties served by the Mayo Clinic Center for Translational Science Award, in Rochester, Minnesota, as these were top priorities identified in community health needs assessments.

Cross-sectional study to assess the association of rural–urban locality on 5-year (2009–2014) prevalence of mood disorder and obesity obtained using the Rochester Epidemiological Project medical records linkage system, among subjects residing in three mixed rural–urban counties on April 1, 2014. Multivariable analyses adjusted for demographics, socioeconomic status using an individual housing-based measure, and counties.

The study cohort (percent rural location) included 91,202 (15%) for Olmsted, 10,197 (51%) in Dodge, and 10,184 (57%) in Wabasha counties. On multivariate analysis, 5-year prevalence of mood disorders and obesity was significantly greater for urban compared with rural residents, after adjusting for confounders; odds ratios (95% confidence intervals): 1.21 (1.17–1.26), P < 0.001, and 1.05 (1.01–1.10), P = 0.016, respectively. Observed effects were not modified in additional models adjusted for health care utilization (HCU; ≥1 general medical examination visit and flu vaccination).

Rural–urban health disparities for burden of mood disorders and obesity are independent of socioeconomic status and HCU in a Midwestern community. It is important to assess potential regional heterogeneity of rural–urban disparities on health outcomes.

Researchers have explored using the internet and social media to recruit participants to specific research projects. Less systematic work has been done to inform the engagement of large populations in virtual communities to advance clinical and translational science. We report on our first step to use social media to engage Minnesota residents by studying the willingness of participants to engage in a virtual (Facebook) community about the concepts of health and health-related research.

Data were collected at the 2018 Minnesota State Fair using a cross-sectional, 46-item survey with assessment including sociodemographics and willingness to engage in a Facebook group for health-related research. Quantitative analysis included univariate, bivariate, and multivariate analyses. Content analysis was used to generate themes from open-ended survey responses.

Five hundred people completed the survey; after data cleaning, 418 participant responses informed this report. A majority were younger than age 50 (73%), female (66%), and married/partnered (54%). Overall, 46% of participants agreed/strongly agreed they are willing to join the Facebook group. Multivariate logistic regression identified social media use over the past 6 months as the sole variable independently associated with willingness to join the Facebook group (once a day vs. never or rarely OR = 1.82 (0.86, 3.88), several hours a day vs. never or rarely OR = 2.17 (1.17, 4.02, overall p-value 0.048).

Facebook holds potential for reaching a broader community, democratizing access to and engagement with clinical and translational research. Social media infrastructure and content could be disseminated to other institutions with Clinical and Translational Science Awards.

Opioids are more commonly prescribed for chronic pain in rural settings in the USA, yet little is known about how the rural context influences efforts to improve opioid medication management.

The Six Building Blocks is an evidence-based program that guides primary care practices in making system-based improvements in managing patients using long-term opioid therapy. It was implemented at 6 rural and rural-serving organizations with 20 clinic locations over a 15-month period. To gain further insight about their experience with implementing the program, interviews and focus groups were conducted with staff and clinicians at the six organizations at the end of the 15 months and transcribed. Team members used a template analysis approach, a form of qualitative thematic analysis, to code these data for barriers, facilitators, and corresponding subcodes.

Facilitators to making systems-based changes in opioid management within a rural practice context included a desire to help patients and their community, external pressures to make changes in opioid management, a desire to reduce workplace stress, external support for the clinic, supportive clinic leadership, and receptivity of patients. Barriers to making changes included competing demands on clinicians and staff, a culture of clinician autonomy, inadequate data systems, and a lack of patient resources in rural areas.

The barriers and facilitators identified here point to potentially unique determinants of practice that should be considered when addressing opioid prescribing for chronic pain in the rural setting.

The NIH Inclusion Across the Lifespan policy has implications for increasing older adult (OA) participation in research. This study aimed to understand influential factors and facilitators to rural OA research participation.

Thirty-seven rural adults aged ≥66 years participated in focus groups in community centers in four Oregon “non-metro” counties. Transcribed discussions were coded using open-axial coding by an interdisciplinary analytical team.

Ages were 66–96 (mean 82.2) years. Majority were women (64%) and white (86%). Primary, interrelated discussion themes were Motivation and Facilitators, Perceptions of Research, and Barriers to Research Participation. Participants were motivated to engage in research because they believed research had implications for improved longevity and quality of life and potentially benefited future generations. Motivational factors influencing participation included self-benefit and improving others’ lives, opportunities to socialize and learn about current research, research transparency (funding, time commitment, and requirements), and financial compensation. Perceptions influencing trustworthiness in research included funding source (industry/non-industry) and familiarity with the research institution. Barriers to research participation included transportation and concern about privacy and confidentiality. Suggestions for making research participation easier included researchers coming to rural communities and meeting participants in places where OAs gather and providing transportation and hotel accommodations.

Lessons learned offer practical guidance for research teams as they address the new NIH Inclusion Across the Lifespan policy. Including OAs in research in ways that motivate and facilitate participation will be critical for a robust representation across the lifespan and in tailoring treatments to the specific needs of this population.

Arkansans have some of the worst breast cancer mortality to incidence ratios in the United States (5th for Blacks, 4th for Whites, 7th overall). Screening mammography allows for early detection and significant reductions in mortality, yet not all women have access to these life-saving services. Utilization in Arkansas is well below the national average, and the number of FDA-approved screening facilities has decreased by 38% since 2001. Spatial accessibility plays an important role in whether women receive screenings.

We use constrained optimization models within a geographic information system (GIS) to probabilistically allocate women to nearby screening facilities, accounting for facility capacity and patient travel time. We examine accessibility results by rurality derived from rural–urban commuting area (RUCA) codes.

Under most models, screening capacity is insufficient to meet theoretical demand given travel constraints. Approximately 80% of Arkansan women live within 30 minutes of a screening facility, most of which are located in urban and suburban areas. The majority of unallocated demand was in Small towns and Rural areas.

Geographic disparities in screening mammography accessibility exist across Arkansas, but women living in Rural areas have particularly poor spatial access. Mobile mammography clinics can remove patient travel time constraints to help meet rural demand. More broadly, optimization models and GIS can be applied to many studies of healthcare accessibility in rural populations.

Given the significant health effects, we assessed geospatial patterns of adverse events (AEs), defined as physical or sexual abuse and accidents or poisonings at home, among children in a mixed rural–urban community.

We conducted a population-based cohort study of children (<18 years) living in Olmsted County, Minnesota, to assess geographic patterns of AEs between April 2004 and March 2009 using International Classification of Diseases, Ninth Revision codes. We identified hotspots by calculating the relative difference between observed and expected case densities accounting for population characteristics ($$Relative\;Difference = {\rm{ }}{{Observed\;Case\;Density - Expected\;Case\;Density} \over {Expected\;Case\;Density}}$$; hotspot ≥ 0.33) using kernel density methods. A Bayesian geospatial logistic regression model was used to test for association of subject characteristics (including residential features) with AEs, adjusting for age, sex, and socioeconomic status (SES).

Of the 30,227 eligible children (<18 years), 974 (3.2%) experienced at least one AE. Of the nine total hotspots identified, five were mobile home communities (MHCs). Among non-Hispanic White children (85% of total children), those living in MHCs had higher AE prevalence compared to those outside MHCs, independent of SES (mean posterior odds ratio: 1.80; 95% credible interval: 1.22–2.54). MHC residency in minority children was not associated with higher prevalence of AEs. Of addresses requiring manual correction, 85.5% belonged to mobile homes.

MHC residence is a significant unrecognized risk factor for AEs among non-Hispanic, White children in a mixed rural–urban community. Given plausible outreach difficulty due to address discrepancies, MHC residents might be a geographically underserved population for clinical care and research.

Sudden unexpected infant death is the leading cause of infant mortality with black: white infant mortality remaining at 2:1 for the last decade. Smartphone technology provides a convenient and accessible tool for injury prevention anticipatory guidance among at-risk communities.

A convenience sample of pregnant teen mothers who own a smartphone. During a 1-month postnatal home visit, a safe sleep environment survey was administered, infant sleep practices were observed, and mothers trained to take and submit standard infants’ sleep environment photographs. Photographs were independently assessed for inter-rater reliability (IRR) across five sleep safety domains (primary outcome): sleep location, surface, position, presence of soft items, and hazards near the sleep area. Expert and novice coders IRR was measured using Cohen’s kappa coefficient (K). Sleep safety correlation between photographs and observation, and parent report and observation was determined.

Sixteen (57.1%) mothers completed the home visit. Most parents reported infants sleeping supine (78.5) in parents’ bedroom (85.9%). Photographs demonstrated sleep position, soft items without the baby present, and hanging toys had perfect agreement across all three coder pairs. Safe sleep experts’ IRR demonstrated perfect agreement for sleep location, position, and soft items. While 83.8% of parents were observed putting their infants down to sleep on their back, 78.5% of parents reported doing the same and 82.4% of the photographs demonstrated supine infant sleep position.

Using photographs, coders can reliably categorize some key infant sleep safety aspects, and photograph sleep safety is comparable to parent report and direct observation.

Pregnant women living in rural locations in the USA have higher rates of maternal and infant mortality compared to their urban counterparts. One factor contributing to this disparity may be lack of representation of rural women in traditional clinical research studies of pregnancy. Barriers to participation often include transportation to research facilities, which are typically located in urban centers, childcare, and inability to participate during nonwork hours.

POWERMOM is a digital research app which allows participants to share both survey and sensor data during their pregnancy. Through non-targeted, national outreach a study population of 3612 participants (591 from rural zip codes and 3021 from urban zip codes) have been enrolled so far in the study, beginning on March 16, 2017, through September 20, 2019.

On average rural participants in our study were younger, had higher pre-pregnancy weights, were less racially diverse, and were more likely to plan a home birth compared to the urban participants. Both groups showed similar engagement in terms of week of pregnancy when they joined, percentage of surveys completed, and completion of the outcome survey after they delivered their baby. However, rural participants shared less HealthKit or sensor data compared to urban participants.

Our study demonstrated the feasibility and effectiveness of enrolling pregnant women living in rural zip codes using a digital research study embedded within a popular pregnancy app. Future efforts to conduct remote digital research studies could help fill representation and knowledge gaps related to pregnant women.