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Background: The Covid Connected Care Center (C4), a low-barrier telephone nurse hotline, was developed at an academic medical center to increase access to healthcare information and services across the state of Oregon, including to those without a usual source of care. Other studies have demonstrated that telephone triage services can positively influence health behaviors, but it is not known how this effect is maintained across racial/ethnic groups. The objective of this study was to show that the C4 reached throughout the state of Oregon, was valuable to callers, and that recommendations given affected callers' subsequent health-related behaviors. Methods: This mixed-methods study, informed by the RE-AIM (Reach, Effectiveness, Addoption, Implementation and Maintenance) framework, assessed caller demographics and clinical care from March 30 2020 until September 8, 2021. Descriptive statistics, multivariable risk models and Zou's modified Poisson modeling were applied to electronic health record and call system data; An inductive approach was used for patient and staff experience surveys and semi-structured interviews. Approval was obtained from the OHSU Institutional Review Board (Study 00021413). Results: 145,537 telephone calls and 92,100 text-based contacts (61% and 39%, respectively) were included. Callers tended to not have a usual source of primary care and utilized recommended services. Emergency department utilization was minimal (1.5%). Racial or ethnic disparities were not detected in the recommendations, but Black (RR 0.92, CI 0.86–0.98) and Multiracial (RR 0.90 CI 0.81–0.99) callers were less likely than non-Hispanic white callers to receive a COVID-19 test. Participants in the post-call survey (n = 50) would recommend this service to friends or family. Interviews with callers (n = 9) revealed this was because they valued assistance translating general recommendations into a personalized care plan. C4 staff interviewed (n = 9) valued the opportunity to serve the public. The C4 was a trusted resource to the public and reached the intended audiences. However, disparities in access to COVID-19 testing persisted. Conclusions: Nursing triage hotlines can guide caller behavior and be an effective part of a robust public health information infrastructure. [ABSTRACT FROM AUTHOR]

Objective: To describe telemedicine use patterns and understand clinic's approaches to shifting care delivery during the COVID-19 pandemic. Methods: We used electronic health record data from 203 community health centers across 13 states between 01/01/2019 and 6/31/2021 to describe trends in telemedicine visit rates over time. Qualitative data were collected from 13 of those community health centers to understand factors influencing adoption and implementation of telemedicine. Results: Most clinics in our sample were in urban areas (n = 176) and served a majority of uninsured and publicly insured patients (12.8% and 44.4%, respectively) across racial and ethnic minority groups (16.6% Black and 29.3% Hispanic). During our analysis period there was a 791% increase in telemedicine visits from before the pandemic (.06% pre- vs 47.5% during). A latent class growth analysis was used to examine differences in patterns of adoption of telemedicine across the 203 CHCs. The model resulted in 6 clusters representing various levels of telemedicine adoption. A mixed methods approach streamlined these clusters into 4 final groups. Clinics that reported rapid adoption of telemedicine attributed this change to leadership prioritization of telemedicine, robust quality improvement processes (eg, using PDSA processes), and emphasis on training and technology support. Conclusions: In response to the COVID-19 pandemic, telemedicine adoption rates varied across clinics. Our study highlight that organizational factors contributed to the clinic's ability to rapidly uptake and use telemedicine services throughout the pandemic. These approaches could inform future non-pandemic practice change and care delivery. [ABSTRACT FROM AUTHOR]

Evidence-based strategies to decrease fall rates are well established. However, little is understood about how older people engage in fall prevention strategies. Motivational Interviewing (MI) sessions aimed to facilitate individuals' engagement in fall prevention can be analyzed to learn what it means for older people to engage in fall prevention. Thus, the purpose of this study was to explore how older people describe their engagement in fall prevention. Participants in our parent project, MI for Fall Prevention (MI-FP), who received MI sessions were purposively selected for maximum variation in age, sex, fall risks, and MI specialist assigned. The first (of 8) MI sessions from 16 participants were recorded, transcribed, and analyzed using qualitative content analysis. Three researchers first deductively analyzed fall prevention strategies that participants described using an evidence-based fall prevention guideline as a reference. Then, we inductively analyzed the characteristics of these strategies and how participants engaged in them. Finally, we used the Capability, Opportunity, Motivation, Behavior (COM-B) model to organize our results about factors influencing engagement. We found (1) older adults engage in unique combinations of fall prevention strategies and (2) decisions about engagement in fall prevention strategies were influenced by multiple factors that were personal (e.g., who I am, capability, motivation, and opportunities). This study highlighted how fall prevention can be a life-long lifestyle decision for older people. Understanding older people's perspectives about engaging in fall prevention is essential to develop interventions to promote evidence-based fall prevention strategies in real-world settings. [ABSTRACT FROM AUTHOR]

Data sharing, the act of making scientific research data available to others, can accelerate innovation and discoveries, and ultimately enhance public health. The National Cancer Institute Implementation Science Centers in Cancer Control convened a diverse group of research scientists, practitioners, and community partners in three interactive workshops (May-June 2022) to identify and discuss factors that must be considered when designing research for equitable data sharing with a specific emphasis on implementation science and social, behavioral, and population health research. This group identified and operationalized a set of seven key considerations for equitable data sharing-conceptualized as an inclusive process that fairly includes the perspectives and priorities of all partners involved in and impacted by data sharing, with consideration of ethics, history, and benefits-that were integrated into a framework. Key data-sharing components particularly important for health equity included: elevating data sharing into a core research activity, incorporating diverse perspectives, and meaningfully engaging partners in data-sharing decisions throughout the project lifecycle. As the process of data sharing grows in research, it is critical to continue considering the potential positive and adverse impact of data sharing on diverse beneficiaries of health data and research., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Society of Behavioral Medicine. Elements of this work have been written by employees of the US government.)