Faculty Bibliography

IMPORTANCE/UNASSIGNED:Remote patient monitoring (RPM), including self-measured blood pressure monitoring with clinician review and telehealth-supported feedback, can support hypertension management. However, RPM use and related care continuity after switching from Medicare fee-for-service (FFS) to Medicare Advantage (MA) remain unclear. OBJECTIVE/UNASSIGNED:To compare RPM adoption, clinician continuity, and hypertension-related acute care utilization among beneficiaries who remained in Medicare FFS vs switched to MA plans, categorized as value-based contract (VBC) proxy or non-VBC. DESIGN, SETTING, AND PARTICIPANTS/UNASSIGNED:This cohort study with an observational difference-in-differences design with propensity score matching used data from 2016 to 2022 Medicare enrollment, FFS claims, and MA encounter data. Beneficiaries were aged 65 years or older with prevalent diagnosed hypertension in 2018 and continuous enrollment in Parts A and B in 2018. Treated groups switched from FFS to MA in January 2019 and remained enrolled through 2022; comparators remained in FFS. Follow-up extended from January 1, 2019, through December 31, 2022. Data analysis was conducted from April to July 2025. EXPOSURE/UNASSIGNED:Switching from Medicare FFS to MA-VBC proxy or MA non-VBC in 2019. MAIN OUTCOMES AND MEASURES/UNASSIGNED:The primary outcome was annual RPM adoption during hypertension-related visits; secondary outcomes included clinician loss without replacement, clinician switching or substitution, and hypertension-related emergency department (ED) visits and hospitalizations. RESULTS/UNASSIGNED:Matched samples included 281 620 beneficiaries, with 46 833 MA-VBC proxy plan switchers and 46 833 FFS comparators (27 920 [59.6%] aged 71 years or older and 27 685 female [59.1%] in each group) and 93 977 MA non-VBC switchers and 93 977 FFS comparators (67 188 [71.5%] aged 71 years or older; 53 122 female [56.5%] in each group). Common comorbidities included diabetes, chronic kidney disease, and heart failure. Switching to MA was associated with lower RPM adoption in 2022 (MA-VBC proxy: odds ratio [OR], 0.55; 95% CI, 0.42-0.72; -0.63 percentage points; non-VBC: OR, 0.73; 95% CI, 0.54-0.99; -0.52 percentage points), greater clinician loss without replacement (MA-VBC proxy: OR, 1.27; 95% CI, 1.23-1.32; 3.41 percentage points; MA non-VBC: OR, 1.09; 95% CI, 1.06-1.12; 0.83 percentage points), and higher hypertension-related hospitalizations (MA-VBC proxy: OR, 1.75; 95% CI, 1.48-2.06; MA non-VBC: OR, 1.94; 95% CI 1.71-2.19; 1.56 percentage points in both comparisons). Event-study analyses showed postswitch divergence through 2022. CONCLUSIONS AND RELEVANCE/UNASSIGNED:In this cohort study of older Medicare beneficiaries with hypertension, switching from FFS to MA was associated with lower RPM adoption, greater clinician discontinuity, and higher hypertension-related acute care use. These findings suggest that continuity safeguards and clearer payment or quality incentives during MA transitions may support remote monitoring and clinician follow-up for hypertension.

Manufacturing and use of pharmaceuticals is responsible for nearly 20% of US health care's greenhouse gas footprint. As highly effective weight-loss medications such as incretin mimetics become widely prescribed, it is important to understand environmental implications. More than 33.5 million Americans have tried incretin mimetic medications (IMMs), and nearly 30 million are projected to be consistent users by 2030. This article examines the broader potential implications of glucagon-like peptide-1 and other IMMs on climate change. We conducted a preliminary and speculative carbon footprint of IMMs using a life cycle assessment approach. Our findings suggest widespread IMM use could reduce greenhouse gas emissions by decreasing caloric consumption, food production, and health care activities, leading to a maximum estimated reduction of 760 kg CO2e/person/year. This reduction would be greater than the environmental benefits of switching to electric vehicles or adopting a vegetarian diet. This study highlights the need for more research into potential environmental benefits of IMMs.

BACKGROUND:Artificial intelligence (AI)-enabled "ambient" documentation may reduce clinician administrative burdens and improve care delivery, but implementation in clinical practice is complex. AIM/OBJECTIVE:To evaluate the implementation of commercially available ambient documentation tools in multi-specialty ambulatory clinical workflows at an academic medical center. SETTING/METHODS:A large urban academic health system in New York City. PARTICIPANTS/METHODS:Ninety-seven ambulatory clinicians across specialties. PROGRAM DESCRIPTION/METHODS:A multidisciplinary team conducted a 6-month proof-of-concept structured evaluation of two commercially available ambient documentation tools through initial vendor evaluations, technical review and integration with the electronic health record (EHR), clinician training and onboarding, implementation and technical support, and structured evaluation based on objective and key results (OKR) metrics. A single-group, pre-post evaluation of the impact of the tools on clinician EHR-based efficiency was conducted on a subset of participating clinicians. PROGRAM EVALUATION/RESULTS:Compared to the 3-month period immediately prior to initiating the ambient trial, clinicians experienced a 0.35-min-per-note and a 2.07-min-per-day reduction in documentation time. "Vendor B" showed higher utilization rates and superior user experience compared to "Vendor A." Implementation challenges included workflow integration, training resource requirements, data interoperability and analytics, and ongoing technical support needs. DISCUSSION/CONCLUSIONS:Ambient documentation shows promise in reducing documentation burden, but its success depends on technical stability and integration, product fit and support for clinicians, and adequate implementation resourcing. A multidisciplinary approach with clear metrics, strong vendor partnership and executive sponsorship, and ongoing technical support enables scalability.

IMPORTANCE/UNASSIGNED:Artificial intelligence (AI)-enabled scribes have been proposed to reduce electronic health record (EHR) burden and improve clinician satisfaction. There is limited evidence about their associated results across multiple sites and relative benefits for different clinician groups. OBJECTIVE/UNASSIGNED:To assess the association of AI scribe adoption with changes in EHR time expenditure and visit volume and how associations vary by clinician characteristics. DESIGN, SETTING, AND PARTICIPANTS/UNASSIGNED:Multisite, longitudinal cohort study of AI scribe adoption conducted at 5 US academic health care institutions that introduced AI scribes to their clinicians between June 2023 and August 2025. Participants were ambulatory clinicians. EXPOSURES/UNASSIGNED:AI scribe adoption, defined as receiving access to an AI scribe. This was determined by opt-in decisions by eligible physicians at 4 of the 5 sites. MAIN OUTCOME AND MEASURES/UNASSIGNED:Total time spent on the EHR, time spent on documentation, and time spent on the EHR outside scheduled hours or on unscheduled days, all normalized to 8 scheduled patient hours; weekly visit volume. RESULTS/UNASSIGNED:The sample comprised 8581 clinicians, including 1809 AI scribe adopters. Participants were 57.1% female and were split between primary care (24.4%), medical (62.4%), and surgical (13.2%) specialties. Most (74.1%) were attending physicians, with 18.1% advanced practice clinicians and 7.8% resident physicians. In a difference-in-differences analysis, AI scribe adoption was associated with 13.4 (95% CI, 9.1-17.7) fewer minutes of EHR time, 16.0 (95% CI, 13.7-18.3) fewer minutes of documentation time, and 0.49 (95% CI, 0.17-0.81) additional weekly visits delivered. Electronic health record time outside work hours did not change significantly. Changes associated with AI scribe adoption were greatest for primary care specialists, advanced practice clinicians, female clinicians, and clinicians who used AI scribes in 50% or more of visits. CONCLUSIONS AND RELEVANCE/UNASSIGNED:AI scribe adoption was associated with modest decreases in total EHR time and documentation time and with a modest increase in weekly visit volume.

BACKGROUND:Moral distress, which occurs when the ethically correct action cannot be taken because of internal or external constraints, is associated with depression, burnout, and the desire to leave the healthcare profession among healthcare workers. This study compares internal medicine (IM) residents’ experiences of moral distress while caring for patients with COVID-19 in the year prior to and during the first year of the COVID-19 pandemic. METHODS:This is a mixed methods prospective observational cohort study that enrolled IM residents on a rolling basis beginning December 2018. Moral distress was evaluated via the validated Moral Distress Score-Revised (MDS-R) and Measure of Moral Distress for Healthcare Professionals (MDD-HP) and open-ended questions every 4-months via online surveys and through five resident focus groups. The moral distress scores (MDS) before and during the COVID-19 pandemic were compared using paired t-tests. Transcripts and free text were independently coded by investigators and analyzed by major themes and sub-themes. RESULTS: < .05). Qualitive findings included the exacerbation of existing moral distress and the emergence of new drivers of moral distress, including personal protective equipment, visitor policies, lack of moral framework, and tension between protecting one’s own health and caring for others. CONCLUSIONS:The results of this preliminary analysis suggest that the COVID-19 pandemic exacerbated pre-existing experiences of moral distress and brought to light new and different morally distressing situations for trainees. This analysis of the impact of the pandemic is valuable not only for identifying leverage points for intervention, but also for informing future crisis preparedness and cultivating moral resilience in trainees and the healthcare workforce. SUPPLEMENTARY INFORMATION:The online version contains supplementary material available at 10.1186/s12910-025-01274-6.

IMPORTANCE:Artificial intelligence (AI)-assisted ambient documentation technologies that use audio from clinic visits to generate documentation are being deployed across hospital systems to optimize clinical note writing and reduce administrative burden. However, little is known about optimal approaches to engage patients in informed consent for these tools. OBJECTIVES:To explore clinician and patient experiences with consent processes and examine the association between the use of ambient documentation tools and the patient-clinician relationship. DESIGN, SETTING, AND PARTICIPANTS:This study was conducted from March 1 to December 31, 2024, in ambulatory practices across specialties in a large urban academic health center as part of an ongoing operational quality improvement initiative. Participants included clinicians and patients participating in an operational proof-of-concept exploration of ambient documentation technology. MAIN OUTCOMES AND MEASURES:A pragmatic, sequential, inductive-deductive qualitative evaluation was conducted of informed consent contexts, processes, and challenges among ambulatory clinicians and patients exposed to ambient documentation technology. Evaluation included site visits, clinical observations, clinician interviews, and patient surveys to explore perceptions and challenges related to consent. RESULTS:A total of 121 ambient documentation pilot users included 18 clinicians (mean [SD] years of practice, 18.6 [100]; 10 men [55.6%]) and 103 patients (mean [SD] age, 37 [12.5] years; 65 women [63.1%]). The most common consent approach was a verbal patient-clinician conversation prior to an individual encounter. Patients and clinicians had a spectrum of comfort with ambient technology; 77 patients (74.8%) reported being comfortable or very comfortable with their physician using ambient documentation. Patient trust, detail in the consent discussion, and intended tool use were associated with patient comfort and intent to consent. Technical understanding was associated with comfort with consent conversations: when provided basic information about the technology, 84 patients (81.6%) consented; this decreased to 57 patients (55.3%) when details about AI features, data storage, and corporate involvement were disclosed. Perceived benefits included reduced documentation burden, improved decision-making, and enhanced communication. Concerns included data security, legal liability, cognitive impacts, and equity. When asked about responsibility for medical errors linked to ambient documentation, 66 patients (64.1%) held physicians accountable; for data security breaches, 79 patients (76.7%) believed vendors should be responsible. Participants suggested a flexible consent model with digital touchpoints, education, nonclinical staff support, and opt-out options. CONCLUSIONS AND RELEVANCE:In this quality improvement study of 121 pilot users of AI-assisted ambient documentation technology, informed consent relied primarily on verbal conversations that varied based on time, knowledge, and the patient-clinician relationship. A flexible, multimodal approach-including education, time to discuss risks and benefits, digital resources, nonclinical staff involvement, and clear opt-out options-may improve consent processes and support broader acceptance of ambient documentation tools.

The COVID-19 pandemic catalyzed a rapid expansion of telemedicine across the United States, expanding access to video-based services but also raising concerns about equitable access, use, and experience among minority populations. This mixed-methods scoping review quantitatively describes patterns of video-based telemedicine utilization and qualitatively evaluates factors impacting utilization among racial/ethnic minorities in the United States during the COVID-19 pandemic. We conducted a comprehensive literature search across six databases for studies published between January 2020 and March 2023. Eligible studies reported on telehealth or telemedicine use, specifically video-based visit utilization among racial/ethnic minorities. Reviewers independently screened studies, extracted data, and synthesized findings using an integrated mixed-methods approach. Of 1801 studies, 77 studies met the inclusion criteria. Of these, a majority were published in metropolitan coastal areas, and most were heterogeneous in their definition of telemedicine and utilization. Quantitatively, 33 studies (42.9%) reported increased use of video-based telemedicine, 29 (37.7%) reported decreased use, and 15 (20%) reported variable use across racial/ethnic subgroups. Most studies assessed disparities among non-Hispanic Black and Hispanic/Latinx populations (73 and 66 studies, respectively), while fewer examined disparities among other minority populations (45 studies). Factors associated with telemedicine adoption included patient- and community-level digital access barriers, low organizational digital capacity and infrastructure, implicit bias, and inadequate provider education and training. Identified facilitators included trust and awareness of telemedicine, adequate provider training, cultural and linguistic adaptations, targeted internet subsidies, and telemedicine reimbursements. Video-based telemedicine utilization among racial/ethnic minorities during the COVID-19 pandemic was heterogeneous, influenced by individual, systemic, and implementation factors. Disparities were most pronounced among Asians and other minority populations. Despite increased attention and efforts to address access barriers, our findings highlight the need for more targeted, culturally and structurally tailored interventions to improve digital inclusion.

BACKGROUND:The design and integration of technology within inpatient hospital rooms has a critical role in supporting nursing workflows, enhancing provider experience, and improving patient care. As health care technology evolves, there is a need to design "future-proofed" physical environments that integrate technology in ways that support workflows and maintain clinical performance. Assessing how current technologies affect nursing workflows can help inform the development of these future environments. OBJECTIVE:We assessed the current challenges nursing staff face in inpatient rooms, gather insights on technology, and build environment interactions to envision the design of a technology-integrated "Inpatient Room of the Future." METHODS:A qualitative study was conducted involving semistructured interviews, shadowing, and focus groups among nursing staff in the inpatient setting. Methods including horizon scanning, scenario analysis, technology assessment, and backcasting facilitated a comprehensive qualitative analysis of current technology use and needs in inpatient nursing workflows to inform exploratory design considerations for technology-integrated envisioned futures solutions. RESULTS:In total, 26 nursing staff across 4 inpatient hospital units participated in this study. Analysis identified four major themes considered central to designing a technology-integrated inpatient room that enhances nursing workflow and experience: (1) the need for seamless integration of technologies advocating for a unified system that minimizes fragmented technology use and enhances efficiency; (2) the potential for technology to reduce cognitive load, alleviate mental strain, and streamline complex workflows; (3) a focus on enhancing interpersonal communication with specific emphasis on tools that facilitate clear and efficient communication among clinicians and with patients; and (4) the importance of improved staff well-being with design considerations aimed at promoting both physical and mental health for health care workers in the inpatient setting. Envisioned future solutions included enhanced patient monitoring with automated measurements and actions through computer vision and data triangulation, a smart electronic health record-integrated supply management system using computer vision to detect supply shortages and auto-delivery of needed supplies, and a personal tech smart assistant capable of real-time patient monitoring and escalation, task prioritization, and hands-free clinical documentation and communication. CONCLUSIONS:While current technologies address specific tasks, there are significant opportunities for better technology integration, reducing cognitive load, enhancing communication, and promoting the physical and mental well-being of nursing staff. Future research should focus on seamless technology integration aligned with clinical workflows and implementing supportive technologies that do not interfere with clinician judgment and critical thinking. Policy recommendations include oversight mechanisms for evaluating artificial intelligence-enabled devices, safeguarding patient information, and ensuring nurses are actively involved at every stage of technology development and implementation. Future inpatient unit designs should actively engage input from both nursing professionals and technologists in developing future-proofed clinical spaces to ensure the creation of integrated systems that foster a cohesive and harmonious user experience.

IMPORTANCE/UNASSIGNED:Rapid digitalization of health care and a dearth of digital health education for medical students and junior physicians worldwide means there is an imperative for more training in this dynamic and evolving field. OBJECTIVE/UNASSIGNED:To develop an evidence-informed, consensus-guided, adaptable digital health competencies framework for the design and development of digital health curricula in medical institutions globally. EVIDENCE REVIEW/UNASSIGNED:A core group was assembled to oversee the development of the Digital Health Competencies in Medical Education (DECODE) framework. First, an initial list was created based on findings from a scoping review and expert consultations. A multidisciplinary and geographically diverse panel of 211 experts from 79 countries and territories was convened for a 2-round, modified Delphi survey conducted between December 2022 and July 2023, with an a priori consensus level of 70%. The framework structure, wordings, and learning outcomes with marginal percentage of agreement were discussed and determined in a consensus meeting organized on September 8, 2023, and subsequent postmeeting qualitative feedback. In total, 211 experts participated in round 1, 149 participated in round 2, 12 participated in the consensus meeting, and 58 participated in postmeeting feedback. FINDINGS/UNASSIGNED:The DECODE framework uses 3 main terminologies: domain, competency, and learning outcome. Competencies were grouped into 4 domains: professionalism in digital health, patient and population digital health, health information systems, and health data science. Each competency is accompanied by a set of learning outcomes that are either mandatory or discretionary. The final framework comprises 4 domains, 19 competencies, and 33 mandatory and 145 discretionary learning outcomes, with descriptions for each domain and competency. Six highlighted areas of considerations for medical educators are the variations in nomenclature, the distinctiveness of digital health, the concept of digital health literacy, curriculum space and implementation, the inclusion of discretionary learning outcomes, and socioeconomic inequities in digital health education. CONCLUSIONS AND RELEVANCE/UNASSIGNED:This evidence-informed and consensus-guided framework will play an important role in enabling medical institutions to better prepare future physicians for the ongoing digital transformation in health care. Medical schools are encouraged to adopt and adapt this framework to align with their needs, resources, and circumstances.