Faculty Bibliography

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.

OBJECTIVE:To examine whether patient sociodemographic and clinical characteristics and prior interactions with the healthcare system were associated with opening patient portal messages related to cancer genetic services and beginning services. STUDY SETTING AND DESIGN/METHODS:The trial was conducted in the University of Utah Health (UHealth) and NYU Langone Health (NYULH) systems. Between 2020 and 2023, 3073 eligible primary care patients aged 25-60 years meeting family history-based criteria for cancer genetic evaluation were randomized 1:1 to receive a patient portal message with a hyperlink to a pretest genetics education chatbot or information about scheduling a pretest standard of care (SOC) appointment. DATA SOURCES AND ANALYTIC SAMPLE/UNASSIGNED:Primary data were collected. Eligible patients had a primary care visit in the previous 3 years, a patient portal account, no prior cancer diagnosis except nonmelanoma skin cancer, no prior cancer genetic services, and English or Spanish as their preferred language. Multivariable models identified predictors of opening patient portal messages by site and beginning pretest genetic services by site and experimental condition. PRINCIPAL FINDINGS/RESULTS:Number of previous patient portal logins (UHealth average marginal effect [AME]: 0.32; 95% CI: 0.27, 0.38; NYULH AME: 0.33; 95% CI: 0.27, 0.39), having a recorded primary care provider (NYULH AME: 0.15; 95% CI: 0.08, 0.22), and more primary care visits in the previous 3 years (NYULH AME: 0.09; 95% CI: 0.02, 0.16) were associated with opening patient portal messages about genetic services. Number of previous patient portal logins (UHealth AME: 0.14; 95% CI: 0.08, 0.21; NYULH AME: 0.18; 95% CI: 0.12, 0.23), having a recorded primary care provider (NYULH AME: 0.08; 95% CI: 0.01, 0.14), and more primary care visits in the previous 3 years (NYULH AME: 0.07; 95% CI: 0.01, 0.13) were associated with beginning pretest genetic services. Patient sociodemographic and clinical characteristics were not significantly associated with either outcome. CONCLUSIONS:As system-level initiatives aim to reach patients eligible for cancer genetic services, patients already interacting with the healthcare system may be most likely to respond. Addressing barriers to accessing healthcare and technology may increase engagement with genetic services.

BACKGROUND:E-cigarettes may serve as a safer alternative to combustible cigarettes and may be more effective than currently available nicotine replacement therapy (NRT). Little is known about the perceptions of using e-cigarettes as part of a smoking treatment program. The objective of this study was to gain insight into patient-level factors to consider when developing smoking treatment programs that incorporate e-cigarettes. METHODS:Qualitative analysis of in-depth interviews with 14 participants enrolled in the e-cigarette treatment arm of a tobacco treatment intervention pilot randomized trial comparing the impact of behavioral counseling paired with e-cigarettes or NRT on smoking outcomes. Participants were prompted to share their experiences with the products and the study overall. Transcripts were coded according to the principles of framework analysis for applied research. Codes were organized into themes using the principles of grounded theory. RESULTS:Themes suggest that while there is an eagerness to try e-cigarettes as a new tool for smoking cessation, there is apprehension regarding what it means to "quit" if switching to e-cigarettes. Reflecting on the transitional purpose of e-cigarettes and potential health concerns associated with their use, many participants differentiated between the short-term goal to quit combustible cigarettes and the long-term goal to quit e-cigarettes. CONCLUSIONS:Including e-cigarettes as an option in smoking treatment regimens may be an opportunity to re-engage people who smoke who have tried and failed to quit with other forms of treatment. Participants found it challenging to establish what it means to quit cigarettes with e-cigarettes due to addiction and other health concerns. Clear guidelines are needed for integrating e-cigarettes into smoking cessation programs. TRIAL REGISTRATIONS/BACKGROUND:ClinicalTrials.gov Identifier: NCT04465318.

BACKGROUND/UNASSIGNED:Ecological momentary assessment (EMA) provides insight into the effectiveness and feasibility of smoking-related interventions. OBJECTIVE/UNASSIGNED:The objective of this paper was to assess adherence to an EMA protocol and compare EMA-derived responses with measures collected through multiple surveys. METHODS/UNASSIGNED:A subanalysis was conducted using data from a 12-week, open-label, and 2-arm pilot randomized clinical trial among adult smokers with chronic obstructive pulmonary disease, coronary artery disease, peripheral vascular disease, or asthma in the last 12 months (n=109). Participants were randomized to either electronic cigarette (EC) or nicotine replacement therapy (NRT) treatment arms. We compared EMA data collected through automated SMS text message prompts sent to participants 4 times daily for 12 weeks, including cigarettes smoked per day (CPD), craving, and satisfaction, to survey data collected at 12 weeks. Convergent validity between survey- and EMA-reported measures was evaluated using Pearson correlation and paired t tests. CPD was modeled using negative binomial regression. Relative rates (RRs) of reaching at least 50%, 75%, and 100% CPD reduction between two arms were calculated using both EMA and survey data. RESULTS/UNASSIGNED:The majority of participants were non-Hispanic White (63/109, 58%) and female (60/109, 55%), and had a median age of 60 (IQR 54-65) years. Among the 109 participants, 59.6% (n=65) were consistently adherent to the EMA protocol over the 12-week period. Median weekly EMA response rate remained high over the 12-week study period even though a modest decline was observed (week 1, 97.8% and week 12, 89.4%). The mean CPD declined significantly (week 1, mean 14.2, SD 9.9 and week 12, mean 4.6, SD 6.7; P<.001). EMA-derived and survey-based CPD measurements were positively correlated (r=0.73, 95% CI 0.6-0.82) as were measures of craving (r=0.38, 95% CI 0.17-0.56). No significant paired difference in CPD was observed between EMA measurements and surveys. A significant effect of time on CPD EMA data (incidence rate ratio [IRR] 1-week change 0.93; P<.01) and survey data was found (IRR 12-week change 0.36; P<.01). However, the treatment effect was not significant, which aligned with the RR results. An increase in the EC consumption was observed over time in the EC arm, with 12.1% (7/58) fully switched to EC (defined as CPD=0 and EC use>0) and 20.7% (12/58) mostly switched (defined as a reduction in CPD>75% and EC use>0) in week 12. CONCLUSIONS/UNASSIGNED:EMA is a suitable method to collect recall-based smoking-related data. Though results from mixed effect modeling and RR comparisons were similar using EMA or survey data, EMA provides unique advantages, namely greater granularity in the time and the capability to detect switching patterns in near real time. These findings provide the feasibility of using EMA in developing smoking cessation interventions in future tobacco harm reduction research.

OBJECTIVE:To evaluate trends in telemedicine utilization overall and across clinical specialties, providing insights into its evolving role in health care delivery. STUDY DESIGN/METHODS:This retrospective cross-sectional study analyzed 1.9 million telemedicine video visits from a large academic health care system in New York City between 2020 and 2023. The data, collected from the health care system's electronic health records, included telemedicine encounters across more than 500 ambulatory locations. METHODS:We used descriptive statistics to outline telemedicine usage trends and compared telemedicine utilization rates and evaluation and management characteristics across clinical specialties. RESULTS:Telemedicine utilization peaked during the COVID-19 pandemic, then declined and stabilized. Despite an overall decline, 2 non-primary care specialties (behavioral health and psychiatry) experienced continued growth in telemedicine visits. Primary care and urgent care visits were mainly characterized by low-complexity visits, whereas non-primary care specialties witnessed a rise in moderate- and high-complexity visits, with the number of moderate-level visits surpassing those of low complexity. CONCLUSIONS:The findings highlight a dynamic shift in telemedicine utilization, with non-primary care settings witnessing an increase in the complexity of cases. To address future demands from increasingly complex medical cases managed through telemedicine in non-primary care, appropriate resource allocation is essential.

BACKGROUND/UNASSIGNED:Usability testing is valuable for assessing a new tool or system's usefulness and ease-of-use. Several established methods of usability testing exist, including think-aloud testing. Although usability testing has been shown to be crucial for successful clinical decision support (CDS) tool development, it is often difficult to conduct across multisite development projects due to its time- and labor-intensiveness, cost, and the skills required to conduct the testing. OBJECTIVE/UNASSIGNED:Our objective was to develop a new method of usability testing that would enable efficient acquisition and dissemination of results among multiple sites. We sought to address the existing barriers to successfully completing usability testing during CDS tool development. METHODS/UNASSIGNED:We combined individual think-aloud testing and focus groups into one session and performed sessions serially across 4 sites (snowball group usability testing) to assess the usability of two CDS tools designed for use by nurses in primary and urgent care settings. We recorded each session and took notes in a standardized format. Each site shared feedback from their individual sessions with the other sites in the study so that they could incorporate that feedback into their tools prior to their own testing sessions. RESULTS/UNASSIGNED:The group testing and snowballing components of our new usability testing method proved to be highly beneficial. We identified 3 main benefits of snowball group usability testing. First, by interviewing several participants in a single session rather than individuals over the course of weeks, each site was able to quickly obtain their usability feedback. Second, combining the individualized think-aloud component with a focus group component in the same session helped study teams to more easily notice similarities in feedback among participants and to discuss and act upon suggestions efficiently. Third, conducting usability testing in series across sites allowed study teams to incorporate feedback based on previous sites' sessions prior to conducting their own testing. CONCLUSIONS/UNASSIGNED:Snowball group usability testing provides an efficient method of obtaining multisite feedback on newly developed tools and systems, while addressing barriers typically associated with traditional usability testing methods. This method can be applied to test a wide variety of tools, including CDS tools, prior to launch so that they can be efficiently optimized.

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.

BACKGROUND:Laypeople have easy access to health information through large language models (LLMs), such as ChatGPT, and search engines, such as Google. Search engines transformed health information access, and LLMs offer a new avenue for answering laypeople's questions. OBJECTIVE:We aimed to compare the frequency of use and attitudes toward LLMs and search engines as well as their comparative relevance, usefulness, ease of use, and trustworthiness in responding to health queries. METHODS:We conducted a screening survey to compare the demographics of LLM users and nonusers seeking health information, analyzing results with logistic regression. LLM users from the screening survey were invited to a follow-up survey to report the types of health information they sought. We compared the frequency of use of LLMs and search engines using ANOVA and Tukey post hoc tests. Lastly, paired-sample Wilcoxon tests compared LLMs and search engines on perceived usefulness, ease of use, trustworthiness, feelings, bias, and anthropomorphism. RESULTS:In total, 2002 US participants recruited on Prolific participated in the screening survey about the use of LLMs and search engines. Of them, 52% (n=1045) of the participants were female, with a mean age of 39 (SD 13) years. Participants were 9.7% (n=194) Asian, 12.1% (n=242) Black, 73.3% (n=1467) White, 1.1% (n=22) Hispanic, and 3.8% (n=77) were of other races and ethnicities. Further, 1913 (95.6%) used search engines to look up health queries versus 642 (32.6%) for LLMs. Men had higher odds (odds ratio [OR] 1.63, 95% CI 1.34-1.99; P<.001) of using LLMs for health questions than women. Black (OR 1.90, 95% CI 1.42-2.54; P<.001) and Asian (OR 1.66, 95% CI 1.19-2.30; P<.01) individuals had higher odds than White individuals. Those with excellent perceived health (OR 1.46, 95% CI 1.1-1.93; P=.01) were more likely to use LLMs than those with good health. Higher technical proficiency increased the likelihood of LLM use (OR 1.26, 95% CI 1.14-1.39; P<.001). In a follow-up survey of 281 LLM users for health, most participants used search engines first (n=174, 62%) to answer health questions, but the second most common first source consulted was LLMs (n=39, 14%). LLMs were perceived as less useful (P<.01) and less relevant (P=.07), but elicited fewer negative feelings (P<.001), appeared more human (LLM: n=160, vs search: n=32), and were seen as less biased (P<.001). Trust (P=.56) and ease of use (P=.27) showed no differences. CONCLUSIONS:Search engines are the primary source of health information; yet, positive perceptions of LLMs suggest growing use. Future work could explore whether LLM trust and usefulness are enhanced by supplementing answers with external references and limiting persuasive language to curb overreliance. Collaboration with health organizations can help improve the quality of LLMs' health output.

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.

INTRODUCTION/BACKGROUND:E-cigarettes (ECs) may be an effective harm reduction strategy for individuals with conditions like chronic obstructive pulmonary disease (COPD), asthma, coronary artery disease (CAD), and peripheral arterial disease (PAD) who smoke combustible cigarettes (CCs). Our aim was to examine how individuals with chronic conditions transition from CCs to ECs and its impact on health outcomes. METHODS:In a pilot randomized controlled trial (RCT), patients with COPD, asthma, CAD/PAD who currently smoke CCs and have not used nicotine replacement therapy (NRT) or ECs in the past 14 days were randomized to receive ECs or combination NRT with behavioral counselling. Disease symptoms, acceptability/satisfaction (TSQM-9) and feasibility, and cigarettes per day (CPD), and/or EC use were collected at baseline, 3-, and 6-months. Descriptive statistics and a linear regression were conducted to explore changes in CPD and chronic condition-specific assessments (CAT, SAQ-7, ACT) that assess COPD, asthma, and CAD/PAD symptom change. RESULTS:At 3-months, the EC group (n=63, mean CPD=9±11) reduced their CPD by 54% vs. 60% in the NRT group (n=58, mean CPD=7±6), p=0.56. At 6-months, 17.5% had switched completely to ECs while 23% quit smoking in the NRT arm. CAT scores showed a significant 6-point reduction in the EC arm (p=0.03). Participants scored an average of 69±27 for EC effectiveness, 87±23 for convenience, and 75±27 for overall satisfaction. CONCLUSIONS:This pilot study suggests that ECs may be a safer alternative for chronic condition patients using CCs and warrants further research on expected smoking cessation/reduction among individuals who use ECs. IMPLICATIONS/CONCLUSIONS:The findings from this pilot RCT hold significant implications with chronic conditions such as COPD, asthma, CAD and PAD who smoke CCs. The observed reduction in cigarettes per day and improvement in respiratory symptoms suggest that switching to ECs appears feasible and acceptable among those with chronic diseases. These results suggest that ECs may offer an alternative for individuals struggling to quit CC smoking through existing pharmacotherapies. This study supports further exploration of switching to ECs as a harm reduction strategy among CC users who have been unsuccessful at quitting by other means.