Faculty Bibliography

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:The emergency department (ED) offers an opportunity to initiate palliative care for older adults with serious, life-limiting illness. OBJECTIVE/UNASSIGNED:To assess the effect of a multicomponent intervention to initiate palliative care in the ED on hospital admission, subsequent health care use, and survival in older adults with serious, life-limiting illness. DESIGN, SETTING, AND PARTICIPANTS/UNASSIGNED:Cluster randomized, stepped-wedge, clinical trial including patients aged 66 years or older who visited 1 of 29 EDs across the US between May 1, 2018, and December 31, 2022, had 12 months of prior Medicare enrollment, and a Gagne comorbidity score greater than 6, representing a risk of short-term mortality greater than 30%. Nursing home patients were excluded. INTERVENTION/UNASSIGNED:A multicomponent intervention (the Primary Palliative Care for Emergency Medicine intervention) included (1) evidence-based multidisciplinary education; (2) simulation-based workshops on serious illness communication; (3) clinical decision support; and (4) audit and feedback for ED clinical staff. MAIN OUTCOME AND MEASURES/UNASSIGNED:The primary outcome was hospital admission. The secondary outcomes included subsequent health care use and survival at 6 months. RESULTS/UNASSIGNED:There were 98 922 initial ED visits during the study period (median age, 77 years [IQR, 71-84 years]; 50% were female; 13% were Black and 78% were White; and the median Gagne comorbidity score was 8 [IQR, 7-10]). The rate of hospital admission was 64.4% during the preintervention period vs 61.3% during the postintervention period (absolute difference, -3.1% [95% CI, -3.7% to -2.5%]; adjusted odds ratio [OR], 1.03 [95% CI, 0.93 to 1.14]). There was no difference in the secondary outcomes before vs after the intervention. The rate of admission to an intensive care unit was 7.8% during the preintervention period vs 6.7% during the postintervention period (adjusted OR, 0.98 [95% CI, 0.83 to 1.15]). The rate of at least 1 revisit to the ED was 34.2% during the preintervention period vs 32.2% during the postintervention period (adjusted OR, 1.00 [95% CI, 0.91 to 1.09]). The rate of hospice use was 17.7% during the preintervention period vs 17.2% during the postintervention period (adjusted OR, 1.04 [95% CI, 0.93 to 1.16]). The rate of home health use was 42.0% during the preintervention period vs 38.1% during the postintervention period (adjusted OR, 1.01 [95% CI, 0.92 to 1.10]). The rate of at least 1 hospital readmission was 41.0% during the preintervention period vs 36.6% during the postintervention period (adjusted OR, 1.01 [95% CI, 0.92 to 1.10]). The rate of death was 28.1% during the preintervention period vs 28.7% during the postintervention period (adjusted OR, 1.07 [95% CI, 0.98 to 1.18]). CONCLUSIONS AND RELEVANCE/UNASSIGNED:This multicomponent intervention to initiate palliative care in the ED did not have an effect on hospital admission, subsequent health care use, or short-term mortality in older adults with serious, life-limiting illness. TRIAL REGISTRATION/UNASSIGNED:ClinicalTrials.gov Identifier: NCT03424109.

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.

Health care delivery is undergoing an accelerated period of digital transformation, spurred in part by the COVID-19 pandemic and the use of "virtual-first" care delivery models such as telemedicine. Medical education has responded to this shift with calls for improved digital health training, but there is as yet no universal understanding of the needed competencies, domains, and best practices for teaching these skills. In this paper, we argue that a "digital determinants of health" (DDoH) framework for understanding the intersections of health outcomes, technology, and training is critical to the development of comprehensive digital health competencies in medical education. Much like current social determinants of health models, the DDoH framework can be integrated into undergraduate, graduate, and professional education to guide training interventions as well as competency development and evaluation. We provide possible approaches to integrating this framework into training programs and explore priorities for future research in digitally-competent medical education.

With a renewed focus on health equity in the United States driven by national crises and legislation to improve digital healthcare innovation, there is a need for the designers of digital health tools to take deliberate steps to design for equity in their work. A concrete toolkit of methods to design for health equity is needed to support digital health practitioners in this aim. This narrative review summarizes several health equity frameworks to help digital health practitioners conceptualize the equity dimensions of importance for their work, and then provides design approaches that accommodate an equity focus. Specifically, the Double Diamond Model, the IDEAS framework and toolkit, and community collaboration techniques such as participatory design are explored as mechanisms for practitioners to solicit input from members of underserved groups and better design digital health tools that serve their needs. Each of these design methods requires a deliberate effort by practitioners to infuse health equity into the approach. A series of case studies that use different methods to build in equity considerations are offered to provide examples of how this can be accomplished and demonstrate the range of applications available depending on resources, budget, product maturity, and other factors. We conclude with a call for shared rigor around designing digital health tools that deliver equitable outcomes for members of underserved populations.

BACKGROUND:Large language models (LLMs) are computational artificial intelligence systems with advanced natural language processing capabilities that have recently been popularized among health care students and educators due to their ability to provide real-time access to a vast amount of medical knowledge. The adoption of LLM technology into medical education and training has varied, and little empirical evidence exists to support its use in clinical teaching environments. OBJECTIVE:The aim of the study is to identify and qualitatively evaluate potential use cases and limitations of LLM technology for real-time ward-based educational contexts. METHODS:A brief, single-site exploratory evaluation of the publicly available ChatGPT-3.5 (OpenAI) was conducted by implementing the tool into the daily attending rounds of a general internal medicine inpatient service at a large urban academic medical center. ChatGPT was integrated into rounds via both structured and organic use, using the web-based "chatbot" style interface to interact with the LLM through conversational free-text and discrete queries. A qualitative approach using phenomenological inquiry was used to identify key insights related to the use of ChatGPT through analysis of ChatGPT conversation logs and associated shorthand notes from the clinical sessions. RESULTS:Identified use cases for ChatGPT integration included addressing medical knowledge gaps through discrete medical knowledge inquiries, building differential diagnoses and engaging dual-process thinking, challenging medical axioms, using cognitive aids to support acute care decision-making, and improving complex care management by facilitating conversations with subspecialties. Potential additional uses included engaging in difficult conversations with patients, exploring ethical challenges and general medical ethics teaching, personal continuing medical education resources, developing ward-based teaching tools, supporting and automating clinical documentation, and supporting productivity and task management. LLM biases, misinformation, ethics, and health equity were identified as areas of concern and potential limitations to clinical and training use. A code of conduct on ethical and appropriate use was also developed to guide team usage on the wards. CONCLUSIONS:Overall, ChatGPT offers a novel tool to enhance ward-based learning through rapid information querying, second-order content exploration, and engaged team discussion regarding generated responses. More research is needed to fully understand contexts for educational use, particularly regarding the risks and limitations of the tool in clinical settings and its impacts on trainee development.