Paul James Barr

BACKGROUND More than half of family caregivers assist a person living with dementia (PLWD) with medication management, including administration. Family caregivers report high rates of medication refusal behaviors as care recipients’ dementia advances, exacerbating caregiver overload and strain. While medication management challenges have been identified among clinicians, little is currently known about the challenges and strategies employed by family caregivers to manage medication refusals of PLWDs in the community setting. OBJECTIVE To describe medication management challenges and family caregiver responses, including utilized medication management strategies. METHODS We conducted a descriptive, qualitative study of family caregivers of PLWD recruited from two ongoing NIH funded R01 studies (R01AG074255; R01AG072569) between April 2024 and March 2025. Caregivers completed a sociodemographic questionnaire, the 10-item Short Version of the Burden Scale for Family Caregivers, and participated in a semi-structured, one-on-one qualitative interview focused on describing family caregiver medication management strategies. Interviews were analyzed by two coders using deductive content analysis. RESULTS Twelve family caregivers completed interviews. The majority were female (n=10; 83%) and reported high caregiver burden (n=10; 83%). Half were White and 42% were African American/Black. Medication management challenges, included 1) difficulties related to the steps of medication management itself (e.g., filling prescriptions and understanding, organizing, administering, monitoring, and sustaining medication regimens through maintenance tasks) and 2) the time and effort needed to manage medication refusals. Impacts on the caregiver included stress, fatigue, and frustration directed at themselves, the healthcare system, and the PLWD. Medication management strategies included: organizing medications, establishing a medication routine, promoting education and discussion of prescribed medications with the PLWD, monitoring the PLWD during the medication administration process for refusal behaviors and medication side effects, advocating for deprescription, and developing key behavior and motivation focused strategies with the PLWD. Less common strategies included covert administration and accepting the PLWD’s medication refusal. CONCLUSIONS This study highlights important contextual nuances of the challenges and chosen medication administration strategies family caregivers of PLWDs use in the community setting. Further description of family caregivers’ choice of medication administration strategies are needed, including the impact of PLWD’s disease stage on strategy success rates, to develop acceptable and effective medication management interventions for caregivers of PLWD who exhibit medication refusal behaviors. CLINICALTRIAL N/A

Objective: To explore the impact, barriers, and facilitators of routinely sharing clinic visit recordings with patients in diverse clinical settings. Materials and Methods: We conducted a multiple-case study of three early-adopter clinics in the U.S.: a primary care clinic in Michigan and an oncology clinic in Texas that shared audio recordings, and a neurology clinic in Arizona that shared video recordings. From March 2016 to January 2017, we conducted semi-structured interviews with clinicians, patients, care partners, and administrators (≥18 years, English-speaking), and direct observation of patients using their recordings. Transcripts were analyzed using framework analysis to identify cross-cutting themes. Three coders independently reviewed all transcripts, and a medical anthropologist audited key analytic stages. Results: We interviewed 67 stakeholders (32 patients, 10 care partners, 15 clinicians, and 10 administrators). Across sites, stakeholders reported that recordings improved patients’ recall, understanding, and communication. Patients also used recordings for reflection on their performance in visits and planning, while care partners described reduced anxiety and enhanced involvement. Clinicians reported improved visit interactions, and some used recordings for self-assessment. Key factors influencing implementation included clinic culture, institutional support, workflow logistics, data security, and patient characteristics. Concerns were limited and focused primarily on data privacy. A conceptual framework summarizing themes related to barriers, facilitators, use, and impact of routine recording in healthcare was developed. Discussion: Routinely sharing visit recordings can enhance patient-centered communication and care partner engagement while supporting clinician performance. Successful implementation depends on aligning institutional culture, privacy safeguards, and workflow integration. Conclusion: Sharing visit recordings was acceptable and beneficial across stakeholders. The practice of sharing recordings revealed that clinic visit interventions are more than just transactions of medical information—they promote emotional support, self-reflection, and family engagement.

Effective interpersonal communication is associated with improved health-related outcomes, yet it is unclear to what extent this occurs in triadic clinic v

Background: Family caregivers commonly help manage medications taken by persons living with dementia. Recent work has highlighted the importance of caregiver networks, which are multiple caregivers managing care for a single person, on managing care for persons living with dementia, especially medication management. However, less is known about the composition of caregiver networks. Objective: The objective of this analysis was to describe the composition of caregiver networks that manage medications, the factors associated with helping with medications within caregiver networks, and whether racial or ethnic differences exist in caregiver network composition. Methods: This cross-sectional secondary analysis used data from the National Health and Aging Trends Study (NHATS) “other person” files from 2011 to 2022. Descriptive statistics were calculated for caregivers who were identified as helping manage medications for a person with dementia. Mixed-effect logistic regression was used to determine factors associated with helping with medications among caregiver networks, with odds ratios converted to predicted probabilities using marginal standardization. A P value of .05 or less was considered statistically significant. Secondary analysis was stratified by race and ethnicity due to identified cultural differences in living situation and overall caregiver network composition. Results: A total of 15,809 caregivers were analyzed. Of those, 3048 (19.2%) managed medications for persons living with dementia. Caregiver networks that manage medications tend to include a spouse or partner and child, at least one of whom has a college degree. Every person with dementia reported at least 1 person who managed their medications. White persons with dementia had an average of 2.4 (range 1‐9) people who managed medications, while Black or African American persons with dementia had an average of 2.8 (range 1‐9) and Hispanic or Latino persons with dementia had an average of 2.9 (range 1‐8) people who managed medications. Spouses were most likely to manage medications across all racial and ethnic groups. In regression modeling, female gender (predicted probability [PP] 15%, 95% CI 13%-17%; P<.001), Black or African American race (PP 7%, 95% CI 4%-10%; P<.001), and Hispanic ethnicity (PP 4%, 95% CI 1%-9%; P=.04) were associated with an increased probability of helping with medications. Conclusions: The size and composition of caregiver networks that manage medications for persons living with dementia differ by race and ethnicity but typically includes at least 2 people, one of whom has a college degree. Helping with medications was more likely among non-White family caregivers, while White patients with dementia were more likely to use paid help to manage medications.

Objective: We aimed to understand what patients, caregivers and clinicians identified as the most important information from their audio‐recorded clinic visits and why.Methods: We recruited patients, caregivers and clinicians from primary and speciality care clinics at an academic medical centre in New Hampshire, U.S. Participants reviewed a recording or transcript of their visit, identifying meaningful moments and the reasons why. Two researchers performed a summative content analysis of the data.Results: Sixteen patients, four with caregivers, from six clinicians participated. Patients, caregivers and clinicians identified a median of 7.5 (3–20), 12.5 (6–50) and 18 (4–31) meaningful visit moments, respectively. Moments identified were similar across stakeholders, including patient education, symptoms, recommendations and medications. Four themes emerged as a rationale for finding visit information meaningful: providing and receiving information, sharing the patient experience, forming a care plan, and providing emotional support. Clinicians rarely identified patient statements as important.Conclusion: There was considerable agreement between patients, clinicians and caregivers regarding visit information that is most valuable. Patient contributions may be undervalued by clinicians.Practice Implications: These findings can be used to improve patient‐centred visit communication by focusing visit summaries and decision support on information of the most value to participants.

Introduction: Operationalizing multi-site Community Engagement (CE) Studios to inform a research program is valuable for researchers. We describe the process and outcomes of hosting three CE Studios with Community Experts aged 65 years or older with chronic conditions and care partners of older adults. Experts gave feedback about processes for testing the feasibility, efficacy, effectiveness, and implementation of audio recording clinic visits and sharing recordings with patients who have multimorbidity and their care partners. Methods: The CE Cores of the Clinical and Translational Science Awards Programs at three academic health science centers created a joint CE Studio guide. Studios were conducted iteratively by site. Following receipt of the final reports, responses were compared to find themes, similarities, and differences on four topics in addition to overall commentary: Recruitment and Retention, Study Protocol, Study Reminders and Frequency, and Recording Technology. Results: Eighteen older adults and care partners in three states provided valuable feedback to inform multi-site trials. Feedback influenced multiple aspects of trials in process or subsequently funded. Experts provided critique on the wording of study invitations, information sheets, and reminders to engage in study procedures. Experts were concerned for participants being disappointed by randomization to a control arm and advised how investigators should prepare to address that. Conclusions: Multi-site CE Studios should be consecutive, so each team can learn from the previous teams. Using the CES Toolkit ensures that final reports were easily comparable and utilized to develop a research program that now includes three federally funded clinical trials.

Background: Integrating artificial intelligence (AI) in healthcare settings has the potential to benefit clinical decision-making. Addressing challenges such as ensuring trustworthiness, mitigating bias, and maintaining safety is paramount. The lack of established methodologies for pre- and post-deployment evaluation of AI tools regarding crucial attributes such as transparency, performance monitoring, and adverse event reporting makes this situation challenging. Objectives: This paper aims to make practical suggestions for creating methods, rules, and guidelines to ensure that the development, testing, supervision, and use of AI in clinical decision support (CDS) systems are done well and safely for patients. Materials and Methods: In May 2023, the Division of Clinical Informatics at Beth Israel Deaconess Medical Center and the American Medical Informatics Association co-sponsored a working group on AI in healthcare. In August 2023, there were 4 webinars on AI topics and a 2-day workshop in September 2023 for consensus-building. The event included over 200 industry stakeholders, including clinicians, software developers, academics, ethicists, attorneys, government policy experts, scientists, and patients. The goal was to identify challenges associated with the trusted use of AI-enabled CDS in medical practice. Key issues were identified, and solutions were proposed through qualitative analysis and a 4-month iterative consensus process. Results: Our work culminated in several key recommendations: (1) building safe and trustworthy systems; (2) developing validation, verification, and certification processes for AI-CDS systems; (3) providing a means of safety monitoring and reporting at the national level; and (4) ensuring that appropriate documentation and end-user training are provided. Discussion: AI-enabled Clinical Decision Support (AI-CDS) systems promise to revolutionize healthcare decision-making, necessitating a comprehensive framework for their development, implementation, and regulation that emphasizes trustworthiness, transparency, and safety. This framework encompasses various aspects including model training, explainability, validation, certification, monitoring, and continuous evaluation, while also addressing challenges such as data privacy, fairness, and the need for regulatory oversight to ensure responsible integration of AI into clinical workflow. Conclusions: Achieving responsible AI-CDS systems requires a collective effort from many healthcare stakeholders. This involves implementing robust safety, monitoring, and transparency measures while fostering innovation. Future steps include testing and piloting proposed trust mechanisms, such as safety reporting protocols, and establishing best practice guidelines.