Faculty Bibliography

ObjectivesRemote patient monitoring (RPM), combining home blood pressure measurements with telehealth services, effectively manages hypertension. Successful implementation of RPM programs at scale requires understanding program costs and financial sustainability. We evaluated the financial performance of an RPM program.MethodsConducted from March to June 2024 in the Cardiology Division at New York University Langone Health, the study used field observation, surveys, and micro-costing methods. A costing tool was developed to quantify program costs in 2024 US dollars, including personnel, equipment, and supplies. RPM-related services reimbursement rates were estimated using Medicare billing information. The return-on-investment (ROI) ratio was calculated by dividing net return (profit) by the RPM program costs. Sensitivity analyses assessed the impact of varying parameters on the ROI of RPM.ResultsThe average RPM program cost was estimated at $330 per patient (range: $208-$452). Major expenses included data review by staff ($172 per patient), blood pressure devices ($48 per patient), and phone communications ($36 per patient). ROI varied based on patient compliance with home blood pressure monitoring (≥16 days per month), with an average estimate of 22.2% (range: -11.1%-93.3%) per patient at a 55% compliance rate. The ROI was most sensitive to changes in data-review costs, insurance reimbursement rates, patient compliance, device setup, and communication costs.ConclusionsThe RPM program achieved a positive ROI from the perspective of a clinical division in a large healthcare system. Successful implementation and financial sustainability of RPM require efforts to reduce human resource costs and enhance patient engagement.

INTRODUCTION/BACKGROUND:Colorectal cancer (CRC) screening rates among patients receiving care at multiple federally qualified health care centers (FQHCs) in New York city are low. Proactive outreach through mailed fecal immunochemical tests (FIT), reminders and navigation are evidence based interventions to improve CRC screening rates but remain untested in this study population. OBJECTIVE:To evaluate the effectiveness, implementation, and cost-effectiveness of a multilevel proactive outreach strategy to improve CRC screening rates among underserved adults in Brooklyn, New York. METHODS:This is a randomized controlled trial across five FQHCs serving predominantly Black and low-income populations. Adults aged 45-75 who are overdue for CRC screening are randomized to usual care or a multi-level proactive intervention. The intervention includes mailed education and FIT kits, patient navigation, and support for colonoscopy scheduling and follow-up. The primary outcome is CRC screening completion (FIT or colonoscopy) within six months. Secondary outcomes include colonoscopy follow-up after a positive FIT, implementation barriers and facilitators, and cost-effectiveness. RESULTS:A total of 1379 participants have been enrolled through May 2025. DISCUSSION/CONCLUSIONS:This trial addresses a critical gap in CRC prevention by testing a scalable, multilevel outreach model tailored to underserved populations. Findings will inform future strategies to enhance screening rates while reducing screening disparities through sustainable FQHC-based programs.

BACKGROUND:Medication nonadherence is a common issue among patients with hypertension. Healthcare professionals often overlook medication nonadherence due to limited tools, time constraints, and competing demands. Integrating pharmacy medication fill data into electronic health records (EHRs) presents an opportunity to enhance medication adherence measurement and monitoring in real-time. This study identified facilitators and barriers to addressing adherence to antihypertensive medications by Medical Assistants (MAs), Registered Nurses (RNs), and Primary Care Providers (PCPs) in primary care settings. METHODS:We conducted a qualitative study with, 15 healthcare professionals (5 MAs, 5 RNs, and 5 PCPs) caring for patients with hypertension. Semi-structured interviews, guided by the Consolidated Framework for Implementation Research (CFIR), explored barriers and facilitators related to screening and addressing medication non-adherence during primary care clinical encounters. Thematic analysis and deductive coding were used to analyze the data. RESULTS:Four major themes emerged: motivation, work infrastructure, capability, and opportunity. MAs and PCPs were motivated to discuss medication adherence and build relationships. Capability varied; RNs were confident in their counseling skills based on their training and patient trust, and PCPs described adherence counseling as part of their role, particularly through motivational interviewing. Work infrastructure presented structural hurdles due to RN workflow limitations and MA role constraints. Opportunity to address non-adherence were constrained by tight schedules and competing clinical demands during brief visits. CONCLUSIONS:RNs and PCPs felt capable in their ability to address medication adherence but cited time and competing demands as significant barriers; conversely, MAs reported motivation but were limited by their role. These findings suggest opportunities for effective management of medication adherence in practice settings through a more coordinated strategy across multiple healthcare professionals. TRIAL REGISTRATION/BACKGROUND:ClinicalTrials.gov; NCT05349422; https://clinicaltrials.gov/ct2/show/NCT05349422.

BACKGROUND/UNASSIGNED:With rising patient volumes and a focus on quality, our health system had the objective to create a more efficient way to ensure accurate documentation of colorectal cancer (CRC) screening intervals from inbound colonoscopy reports to ensure timely follow-up. We developed an integrated end-to-end workflow solution using machine learning (ML) and robotic process automation (RPA) to extract and update electronic health record (EHR) follow-up dates from unstructured data. OBJECTIVE/UNASSIGNED:This study aimed to automate data extraction from external, free-text colonoscopy reports to identify and document recommended follow-up dates for CRC screening in structured EHR fields. METHODS/UNASSIGNED:As proof of concept, we outline the process development, validity, and implementation of an approach that integrates available tools to automate data retrieval and entry within the EHR of a large academic health system. The health system uses Epic Systems as its EHR platform, and the ML model used was trained on health system patient colonoscopy reports. This proof-of-concept process study consisted of six stages: (1) identification of gaps in documenting recommendations for follow-up CRC screening from external colonoscopy reports, (2) defining process objectives, (3) identification of technologies, (4) creation of process architecture, (5) process validation, and (6) health system-wide implementation. A chart review was performed to validate process outcomes and estimate impact. RESULTS/UNASSIGNED:We developed an automated process with 3 primary steps leveraging ML and RPA to create a fully orchestrated workflow to update CRC screening recall dates based on colonoscopy reports received from external sources. Process validity was assessed with 690 scanned colonoscopy reports. During process validation, the overall automated process achieved an accuracy of 80.7% (557/690, 95% CI 77.8%-83.7%) for correctly identifying the presence or absence of a valid follow-up date and a follow-up date false negative identification rate of 32.9% (130/395, 95% CI 29.4%-36.4%). From the organization-wide implementation to go-live until December 31, 2024, the system processed 16,563 external colonoscopy reports. Of these, 35.3% (5841/16,563) had a follow-up date meeting the relevant ML model threshold and thus were identified as ready for RPA processing. CONCLUSIONS/UNASSIGNED:Implementation of an automated workflow to extract and update CRC screening follow-up dates from colonoscopy reports is feasible and has the potential to improve accuracy in patient recall while reducing documentation burden. By standardizing data ingestion, extending this approach to various unstructured data types can address deficiencies in structured EHR documentation and solve for a lack of data integration and reporting for quality measures. Automated workflows leveraging ML and RPA offer practical solutions to overcome interoperability challenges and the use of unstructured data within health care systems.

BACKGROUND:Nonadherence to antihypertensive medications is common. Mobile health (mHealth)-based behavioral economic interventions may improve adherence, but remain largely untested, especially in vulnerable populations. OBJECTIVE:The study sought to test whether an mHealth incentive lottery would lower systolic blood pressure (SBP) and improve adherence. METHODS:BETTER-BP (Behavioral Economics Trial To Enhance Regulation of Blood Pressure) was a randomized trial conducted in 3 safety-net clinics in New York City. Eligible participants were adults with hypertension prescribed at least 1 antihypertensive medication, with SBP >140 mm Hg, and poor self-reported adherence. In the intervention arm, an incentive lottery was administered via SMS messaging. All participants received passive adherence monitoring. The intervention lasted 6 months, with continued monitoring until 12 months. The primary clinical endpoint was change in SBP at 6 months. The primary process endpoint was adequate antihypertensive medication adherence (≥80% days adherent) from baseline to 6 months. RESULTS:Four-hundred participants (265 intervention:135 control) were enrolled with median age 57 years, 60.5% women, 61.5% Hispanic, and 20.3% non-Hispanic Black. Over 70% had Medicaid or no insurance. At 6 months, intervention arm participants were twice as likely to achieve adequate adherence (71% vs 34%; adjusted risk ratio: 2.04; 95% CI: 1.58-2.63), but there was no significant change in mean SBP (-6.7 mm Hg intervention vs -5.8 mm Hg control; P = 0.62). From 6 to 12 months, adherence was similar (31% intervention vs 26% control; adjusted risk ratio: 1.17; 95% CI: 0.83-1.65). CONCLUSIONS:In a diverse safety-net population, the BETTER-BP intervention doubled the rate of adequate antihypertensive medication adherence but did not reduce SBP at 6 months.

BACKGROUND:Health equity is receiving increased attention in medical education. However, guidance is often lacking on how to integrate health equity into routine medical education. Journal club presents an opportunity to deepen medical educators' and learners' understanding of health equity principles and use it as a lens through which to critically appraise the literature. AIM/OBJECTIVE:We present a health equity framework, iteratively co-created by faculty and learners, that can be applied in a journal club setting. SETTING/METHODS:Academic medical center in New York City, USA. PARTICIPANTS/METHODS:Faculty, residency program directors, medical students, and residents. PROGRAM DESCRIPTION/METHODS:Authors developed the health equity journal club framework during a medical student selective course. Learner and faculty applied the framework to journal club articles; their feedback informed revisions. Framework domains included authorship, ethics, methodology, language, peer review, and references. PROGRAM EVALUATION/RESULTS:Learner evaluations were overall positive, and 86% (n = 13) of responding residency program directors (n = 15) across 15 departments who were surveyed plan to use the framework moving forward. DISCUSSION/CONCLUSIONS:A health equity journal club framework applied to critical appraisal of the literature may facilitate health equity as a routine part of medical education. Co-creating the framework proved vital to inclusion of learner voices.

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.

BACKGROUND:Glaucoma Research Foundation's third Catalyst for a Cure team (CFC3) was established in 2019 to uncover new therapies for glaucoma, a leading cause of blindness. In the 2021 meeting "Solving Neurodegeneration," (detailed in Mol Neurodegeneration 17(1), 2022) the team examined the failures of investigational monotherapies, issues with translatability, and other significant challenges faced when working with neurodegenerative disease models. They emphasized the need for novel, humanized models and proposed identifying commonalities across neurodegenerative diseases to support the creation of pan-neurodegenerative disease therapies. Since then, the fourth Catalyst for a Cure team (CFC4) was formed to explore commonalities between glaucoma and other neurodegenerative diseases. This review summarizes outcomes from the 2023 "Solving Neurodegeneration 2" meeting, a forum for CFC3 and CFC4 to share updates, problem solve, plan future research collaborations, and identify areas of unmet need or opportunity in glaucoma and the broader field of neurodegenerative disease research. MAIN BODY/METHODS:We summarize the recent progress in the field of neurodegenerative disease research and present the newest challenges and opportunities moving forward. While translatability and disease complexity continue to pose major challenges, important progress has been made in identifying neuroprotective targets and understanding neuron-glia-vascular cell interactions. New challenges involve improving our understanding of the disease microenvironment and timeline, identifying the optimal approach(es) to neuronal replacement, and finding the best drug combinations and synergies for neuroprotection. We propose solutions to common research questions, provide prescriptive recommendations for future studies, and detail methodologies, strategies, and approaches for addressing major challenges at the forefront of neurodegenerative disease research. CONCLUSIONS:This review is intended to serve as a research framework, offering recommendations and approaches to validating neuroprotective targets, investigating rare cell types, performing cell-specific functional characterizations, leveraging novel adaptations of scRNAseq, and performing single-cell sorting and sequencing across neurodegenerative diseases and disease models. We focus on modeling neurodegeneration using glaucoma and other neurodegenerative pathologies to investigate the temporal and spatial dynamics of neurodegenerative disease pathogenesis, suggesting researchers aim to identify pan-neurodegenerative drug targets and drug combinations leverageable across neurodegenerative diseases.