A new competency-based job framework was implemented for clinical research professionals at a large, clinical research-intensive academic medical center. This study evaluates the rates of turnover before and after implementation of the new framework. Turnover in this workforce (as with most) is costly; it contributes to wasted dollars and lost productivity since these are highly specialized positions requiring extensive training, regardless of experience in the field.

Trends in employee turnover for 3 years prior to and after the implementation of competency-based job framework for clinical research positions were studied using human resources data. Employee demographics, turnover rates, and comparisons to national statistics are summarized.

Employee turnover within the clinical research professional jobs has decreased from 23% to 16%, a 45% reduction, since the implementation of competency-based job framework.

The new jobs and career ladders, both of which are centered on a competency-based framework, have decreased the overall turnover rate in this employee population. Since little is known about the rates of turnover in clinical research, especially in the academic medical setting, the results of this analysis can provide important insights to other academic medical centers on both employee turnover rate in general and the potential impact of implementing large-scale competency-based job changes.

Shared patient–clinician decision-making is central to choosing between medical treatments. Decision support tools can have an important role to play in these decisions. We developed a decision support tool for deciding between nonsurgical treatment and surgical total knee replacement for patients with severe knee osteoarthritis. The tool aims to provide likely outcomes of alternative treatments based on predictive models using patient-specific characteristics. To make those models relevant to patients with knee osteoarthritis and their clinicians, we involved patients, family members, patient advocates, clinicians, and researchers as stakeholders in creating the models.

Stakeholders were recruited through local arthritis research, advocacy, and clinical organizations. After being provided with brief methodological education sessions, stakeholder views were solicited through quarterly patient or clinician stakeholder panel meetings and incorporated into all aspects of the project.

Participating in each aspect of the research from determining the outcomes of interest to providing input on the design of the user interface displaying outcome predications, 86% (12/14) of stakeholders remained engaged throughout the project. Stakeholder engagement ensured that the prediction models that form the basis of the Knee Osteoarthritis Mathematical Equipoise Tool and its user interface were relevant for patient–clinician shared decision-making.

Methodological research has the opportunity to benefit from stakeholder engagement by ensuring that the perspectives of those most impacted by the results are involved in study design and conduct. While additional planning and investments in maintaining stakeholder knowledge and trust may be needed, they are offset by the valuable insights gained.

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.

To enhance the performance evaluation of Clinical and Translational Science Award (CTSA) hubs, we examined the utility of advanced bibliometric measures that go beyond simple publication counts to demonstrate the impact of translational research output.

The sampled data included North Carolina Translational and Clinical Science Institute (NC TraCS)-supported publications produced between September 2008 and March 2017. We adopted advanced bibliometric measures and a state-of-the-art bibliometric network analysis tool to assess research productivity, citation impact, the scope of research collaboration, and the clusters of research topics.

Totally, 754 NC TraCS-supported publications generated over 24,000 citation counts by April 2017 with an average of 33 cites per article. NC TraCS-supported research papers received more than twice as many cites per year as the average National Institute of Health-funded research publications from the same field and time. We identified the top productive researchers and their networks within the CTSA hub. Findings demonstrated the impact of NC TraCS in facilitating interdisciplinary collaborations within the CTSA hub and across the CTSA consortium and connecting researchers with right peers and organizations.

Both improved bibliometrics measures and bibliometric network analysis can bring new perspectives to CTSA evaluation via citation influence and the scope of research collaborations.

Poor clinical trial (CT) recruitment is a significant barrier to translating basic science discoveries into medical practice. Improving support for primary care provider (PCP) referral of patients to CTs may be an important part of the solution. However, implementing CT referral support in primary care is not only technically challenging, but also presents challenges at the person and organization levels.

The objectives of this study were (1) to characterize provider and clinical supervisor attitudes and perceptions regarding CT research, recruitment, and referrals in primary care and (2) to identify perceived workflow strategies and facilitators relevant to designing a technology-supported primary care CT referral program. Focus groups were conducted with PCPs, directors, and supervisors.

Analysis indicated widespread support for the intrinsic scientific value of CTs, while at the same time deep concerns regarding protecting patient well-being, perceived loss of control when patients participate in trials, concern about the impact of point-of-care referrals on clinic workflow, the need for standard processes, and the need for CT information that enables referring providers to quickly confirm that the burdens are justified by the benefits at both patient and provider levels. PCP suggestions pertinent to implementing a CT referral decision support system are reported.

The results from this work contribute to developing an implementation approach to support increased referral of patients to CTs.

The updated common rule, for human subjects research, requires that consents “begin with a ‘concise and focused’ presentation of the key information that will most likely help someone make a decision about whether to participate in a study” (Menikoff, Kaneshiro, Pritchard. The New England Journal of Medicine. 2017; 376(7): 613–615.). We utilized a community-engaged technology development approach to inform feature options within the REDCap software platform centered around collection and storage of electronic consent (eConsent) to address issues of transparency, clinical trial efficiency, and regulatory compliance for informed consent (Harris, et al. Journal of Biomedical Informatics 2009; 42(2): 377–381.). eConsent may also improve recruitment and retention in clinical research studies by addressing: (1) barriers for accessing rural populations by facilitating remote consent and (2) cultural and literacy barriers by including optional explanatory material (e.g., defining terms by hovering over them with the cursor) or the choice of displaying different videos/images based on participant’s race, ethnicity, or educational level (Phillippi, et al. Journal of Obstetric, Gynecologic, & Neonatal Nursing. 2018; 47(4): 529–534.).

We developed and pilot tested our eConsent framework to provide a personalized consent experience whereby users are guided through a consent document that utilizes avatars, contextual glossary information supplements, and videos, to facilitate communication of information.

The eConsent framework includes a portfolio of eight features, reviewed by community stakeholders, and tested at two academic medical centers.

Early adoption and utilization of this eConsent framework have demonstrated acceptability. Next steps will emphasize testing efficacy of features to improve participant engagement with the consent process.

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.