Faculty Bibliography

Background/UNASSIGNED:Our objective was to characterize young adult patients hospitalized with coronavirus disease 2019 (COVID-19) and identify predictors of survival at 30 days. Methods/UNASSIGNED:This retrospective cohort study took place at 12 acute care hospitals in the New York City area. Patients aged 18-39 hospitalized with confirmed COVID-19 between March 1 and April 27, 2020 were included in the study. Demographic, clinical, and outcome data were extracted from electronic health record reports. Results/UNASSIGNED:= .002) were independent predictors of in-hospital 30-day mortality. Conclusions/UNASSIGNED:Obesity was identified as the strongest negative predictor of 30-day in-hospital survival in young adults with COVID-19.

OBJECTIVES/OBJECTIVE:Our discussant's thoughtful consideration of the patient's case allows for review of three maxims of medicine: Occam's razor (the simplest diagnosis is the most likely to be correct), Hickam's dictum (multiple disease entities are more likely than one), and Crabtree's bludgeon (the tendency to make data fit to an explanation we hold dear). CASE PRESENTATION/METHODS:A 66-year-old woman with a history of hypertension presented to our hospital one day after arrival to the United States from Guinea with chronic daily vomiting, unintentional weight loss and progressive shoulder pain. Her labs are notable for renal failure, nephrotic range proteinuria and normocytic anemia while her shoulder X-ray shows osseous resorption in the lateral right clavicle. Multiple myeloma became the team's working diagnosis; however, a subsequent shoulder biopsy was consistent with follicular thyroid carcinoma. Imaging suggested the patient's renal failure was more likely a result of a chronic, unrelated process. CONCLUSIONS:It is tempting to bludgeon diagnostic possibilities into Occam's razor. Presumption that a patient's signs and symptoms are connected by one disease process often puts us at a cognitive advantage. However, atypical presentations, multiple disease processes, and unique populations often lend themselves more to Hickam's dictum than to Occam's razor. Diagnostic aids include performing a metacognitive checklist, engaging analytic thinking, and acknowledging the imperfections of these axioms.

BACKGROUND: Clinical reasoning (CR) is a core component of medical training, yet residents often receive little feedback on their CR documentation. Here we describe the process of developing a machine learning (ML) algorithm for feedback on CR documentation to increase the frequency and quality of feedback in this domain.
METHOD(S): To create this algorithm, note quality first had to be rated by gold standard human rating. We selected the IDEA Assessment Tool-a note rating instrument across four domains (I=Interpretive summary, D=Differential diagnosis, E=Explanation of reasoning, A=Alternative diagnoses explained) that uses a 3-point Likert scale without descriptive anchors. To develop descriptive anchors we conducted an iterative process reviewing notes from the EHR written by medicine residents and validated the Revised-IDEA Assessment Tool using Messick's framework- content validity, response process, relation to other variables, internal structure, and consequences. Using the Hofstee standard setting method, cutoffs for high quality clinical reasoning for the IDEA and DEA scores were set. We then created a dataset of expertrated notes to create the ML algorithm. First, a natural language processing software was applied to the set of notes that enabled recognition and automatic encoding of clinical information as a diagnosis or disease (D's), a sign or symptom (E or A), or semantic qualifier (e.g. most likely). Input variables to the ML algorithm included counts of D's, E/A's, semantic qualifiers, and proximity of semantic qualifiers to disease/ diagnosis. ML output focused on DEA quality and was binarized to low or high quality CR. Finally, 200 notes were randomly selected for human validation review comparing ML output to human rated DEA score.
RESULT(S): The IDEA and DEA scores ranged from 0-10 and 0-6, respectively. IDEA score of >= 6.5 and a DEA score of >= 3 was deemed high quality. 252 notes were rated to create the dataset and 20% were rated by 3 raters with high intraclass correlation 0.84 (95% CI 0.74-0.90). 120 of these notes comprised the testing set for ML model development. The logistic regression model was the best performing model with an AUC 0.87 and a positive predictive value (PPV) of 0.65. 48 (40%) of the notes were high quality. There was substantial interrater reliability between ML output and human rating on the 200 note validation set with a Cohen's Kappa 0.64.
CONCLUSION(S): We have developed a ML algorithm for feedback on CR documentation that we hypothesize will increase the frequency and quality of feedback in this domain. We have subsequently developed a dashboard that will display the output of the ML model. Next steps will be to provide internal medicine residents' feedback on their CR documentation using this dashboard and assess the impact this has on their documentation quality. LEARNING OBJECTIVE #1: Describe the importance of high quality documentation of clinical reasoning. LEARNING OBJECTIVE #2: Identify machine learning as a novel assessment tool for feedback on clinical reasoning documentation

BACKGROUND: On the road to becoming competent, compassionate and ethical physicians, trainees need to reflect on their experiences, understand the clinical and social contexts, and integrate cognitive and affective reactions in ways that build resilience and a coherent professional identity. Using a qualitative approach, this study seeks to identify medical residents' stressors and challenges, and to understand their experience of the internal and external factors of such situations. Such information can guide educators to develop curricula that better meet residents' needs.
METHOD(S): Primary Care residents at NYU School of Med have ongoing Psychosocial Rounds (PSR) throughout their 3 years, facilitated by a faculty member and Chief Resident, where residents present challenging cases or situations, framed by a specific question. Semi-structured notes taken by facilitators, including question, case description, process of discussion and teaching points were compiled into a deidentified database of 119 cases spanning 2010-2019. These notes were coded by three coders using iterative thematic analysis.
RESULT(S): Seventy four of the 119 cases have been coded to date. Four general themes emerged, with each comprised of 2 to 4 main codes. These themes were 1) Self (S): including management of medical uncertainty, emotional reactions, roles and responsibilities, self-care; 2) Teams (T): including relationship with peers, supervisors, other health professionals; 3) Understanding Patient and Families (PF): including social and cultural context, mental health issues, patient/ family and provider disagreements; and 4) Hospital, Healthcare and Societal issues (HHS). There was a high co- occurrence of themes within cases, 60% had 2 themes present, 24% had 3, and only 16% had one theme. Cases with 3 themes most often included S, T and PF.
CONCLUSION(S): This analysis of PSR cases identifies issues for which residents seek help and support in a safe, case-oriented problem-solving discussion group, and allows for in-depth reflection and exploration. The cooccurrences of themes indicate the complexity of issues faced, and the importance of integrating multiple domains when beginning to understand these issues. LEARNING OBJECTIVE #1: Professionalism: Coping with challenges of becoming resilient physician with emotional and cognitive capacity to deal with complex situations LEARNING OBJECTIVE #2: Interpersonal and Communication Skills: Develop awareness and skills to negotiate interpersonal situations

STATEMENT OF PROBLEMOR QUESTION (ONE SENTENCE): To determine the feasibility and acceptability of using a virtual-only model for initiating and maintaining patients on PrEP (pre-exposure prophylaxis) for HIV prevention. LEARNING OBJECTIVES 1: Participants will be able to identify 3 key considerations in developing a clinical workflow for virtual PrEP initiation. LEARNING OBJECTIVES 2: Participants will be able to discuss 3-5 challenges associated with virtual PrEP initiation, and identify strategies to address these challenges. DESCRIPTION OF PROGRAM/INTERVENTION, INCLUDING ORGANIZATIONAL CONTEXT (E.G. INPATIENT VS. OUTPATIENT, PRACTICE OR COMMUNITY CHARACTERISTICS): The Family Health Centers at NYU Langone (FHC) is a federally qualified health center network with 8 clinical sites in Brooklyn, NY, primarily serving a low-income, immigrant community. Since 2016, FHC has operated a focused outreach program to promote PrEP to high-risk individuals, using targeted strategies to engage those not currently in PrEP care. Our intervention sought to expand on our successful outreach model by using tele health to remove geographic barriers to participation. We developed clinical and patient navigation workflows to enable patients to initiate and continue PrEP through virtual visits. For necessary labs, patients were supported in identifying a lab collection site convenient to their home. Patient navigation staff played a key role in risk reduction education, benefits navigation, and facilitating compliance with labs and virtual care. MEASURES OF SUCCESS (DISCUSS QUALITATIVE AND/OR QUANTITATIVEMETRICSWHICHWILL BEUSEDTOEVALUATE PROGRAM/INTERVENTION): The key measure of success is PrEP uptake and continuation among the virtual visits cohort. Additional evaluation measures include the referral source of patients for virtual PrEP initiation, patient demographics, and HIV risk-these measures will enable us to assess whether we are reaching a more diverse or higher risk population through this program. FINDINGS TO DATE (IT IS NOT SUFFICIENT TO STATE FINDINGS WILL BE DISCUSSED): The pilot project launched in October 2020. In the three months since project launch, 8 patients were served through this program. Six of the patients (75%) had been initially engaged with the FHC through the HIV prevention program, while two were existing FHC patients-one of whom had previously been in standard PrEP care, but struggled to make the in-person visits. Six patients were cisgender men who have sex with men, while two were transgender women. Virtual PrEP provided an opportunity to link patients to other needed healthcare services, including vaccination and STI treatment. KEY LESSONS FOR DISSEMINATION (WHAT CAN OTHERS TAKE AWAY FOR IMPLEMENTATION TO THEIR PRACTICE OR COMMUNITY): The tele health PrEP pilot program enabled us to reach a diverse group of high-risk patients, a majority of whom had not previously been engaged in care within our health system, and we anticipate continued growth this program as we expand our outreach to additional geographic areas. Navigation staff were key in overcoming some of the barriers associated with the virtual model by building relationships with the patients and serving as a reliable source of support for patients encountering logistical barriers. PrEP initiation by tele health must account for additional logistical considerations-most notably, ensuring patient compliance with labs-but it is a feasible approach for engaging high-risk patients in HIV prevention services

BACKGROUND: NYU uses the same 14-item checklist for assessing medical student communication skills across our curriculum, which includes highquality Objective Structured Clinical Skills Exams throughout the first three years of medical school: a 3-station Introductory Clinical Experience OSCE (ICE), a 3-station end-of-clinical skills OSCE (Practice of Medicine; POM); and an 8-station, high- stakes OSCE (Comprehensive Clinical Skills Exam; CCSE) after core clerkship. We describe how skills change throughout school and explore how patterns vary by cohort (class) in ways that could be explained by admissions criteria, measurement quality, and/or curriculum changes.
METHOD(S): Three domains are assessed: Info gathering (6 items), relationship development (5 items); and patient education & counseling (3 items). Checklist items use a 3-point scale (not done, partly, well done) with behavioral anchors. Internal consistency (Cronbach's alpha) exceeds .75 for all subdomains and across all years. Domains are supported by Confirmatory Factor Analysis. Mean average % well done was calculated across cases and individuals for each subdomain in an OSCE and compared over the OSCEs and between 8 classes of medical school students entering from 2009 to 2016 (graduating 2013 to 2020) (n=1569).
RESULT(S): Cohorts showed similar patterns communication skills trajectories - improvement over time. Despite changes in admissions criteria and processes, cohorts did not differ in terms of demographics, undergraduate GPA, or MCAT scores. Variability in scores decreased in all cohorts over time while communication improved. Patient education & counseling was significantly and substantially lower than other domains. In terms of cohort effects, communication scores for the entering class of 2013 at the start of medical school (ICE OSCE) were significantly higher than the previous 4. At the end of MS2, scores were similar for cohorts for info gathering and relationship development domains (and high, mean range=77-87% well done) but patient education & counseling varied: Improvement from the 1st to 3rd cohort and then decline for the last 5 cohorts. Within the CCSE (8-station pass/fail, MS3), communication scores increased steadily across entering classes, especially from cohort 4 on. These changes over time and between cohorts were mapped onto a priori descriptions of curricular, measurement and admission changes.
CONCLUSION(S): Our cohort data showed interesting and complex patterns. This study reinforces some limitations of linking curriculum to performance (e.g., no direct measures of the curriculum in terms of content, process and intensity over time, limited data on what makes cohorts different, variable measurement over time, and being unable to control for broader trends likely to influence both cohort and time effects) while also demonstrating the promise of longitudinal perspectives on the development of core competencies. LEARNING OBJECTIVE #1: Understand cohort performance in relation to curricular trends. LEARNING OBJECTIVE #2: Describe variation in performance

STATEMENT OF PROBLEM OR QUESTION (ONE SENTENCE): In order to describe quality improvement (QI) methods for health systems, we report on 10-years of using Unannounced Standardized Patient (USP) visits as the core of a program of education, training, and improvement in a system serving vulnerable patients in partnership with an academic medical center. LEARNING OBJECTIVES 1: Consider methods for supporting learning healthcare systems LEARNING OBJECTIVES 2: Identify performance data to improve care DESCRIPTION OF PROGRAM/INTERVENTION, INCLUDING ORGANIZATIONAL CONTEXT (E.G. INPATIENT VS. OUTPATIENT, PRACTICE OR COMMUNITY CHARACTERISTICS): The IOM defines a Learning Healthcare System (LHCS) as one in which science, informatics, incentives and culture are aligned for continuous improvement and innovation and where best practices are seamlessly embedded in the delivery process and new knowledge is captured as an integral by-product of the delivery experience. As essential as electronic health records are to LHCS, such data fail to capture all actionable information needed to sustain learning within complex systems. USPs are trained actors who present to clinics, incognito, to portray standardized chief complaints, histories, and characteristics. We designed and delivered USP visits to two urban, safety net clinics, focusing on assessing physician, team, and clinical micro system functioning. MEASURES OF SUCCESS (DISCUSS QUALITATIVE AND/OR QUANTITATIVEMETRICSWHICHWILL BE USEDTOEVALUATE PROGRAM/INTERVENTION): Behaviorally anchored assessments are used to assess core clinical skills (e.g., communication, information gathering, patient education, adherence to guidelines, patient centeredness, and patient activation). Team functioning assessments include professionalism and coordination. Micro system assessment focuses on safety issues like identity confirmation, hand washing, and navigation. Data from these visits has been provided to the residency, primary care teams, and to leadership and have been used to drive education, team training, and QI. FINDINGS TO DATE (IT IS NOT SUFFICIENT TO STATE FINDINGS WILL BE DISCUSSED): 1111 visits have been sent to internal medicine and primary care residents and their teams/clinics. At the resident level, needs for additional education and training in depression management, opioid prescribing, smoking cessation, and patient activation were identified and informed education. Chart reviews found substantial variation in ordering of labs and tests. At the team level, USPs uncovered needs for staff training, enhanced communication, and better processes for eliciting and documenting Social Determinants of Health (SDoH). Audit/feedback reports on provider responses to embedded SDoH combined with targeted education/resources, were associated with increased rates of eliciting and effectively responding to SDoH. In the early COVID wave, USPs tested clinic response to a potentially infectious patient. Currently, USPs are being deployed to understand variability in patients' experience of telemedicine given the rapid transformation to this modality. Finally, generalizable questions about underlying principles of medical education and quality improvement are being asked & answered using USP data to foster deeper understanding of levers for change. KEY LESSONS FOR DISSEMINATION (WHAT CAN OTHERS TAKE AWAY FOR IMPLEMENTATION TO THEIR PRACTICE OR COMMUNITY): A comprehensive USP program can provide unique insights for driving QI and innovation and help sustain a LHCS

BACKGROUND: New York City became the epicenter of the COVID-19 pandemic in the US, reporting its first case of SARS-CoV-2 on March 1, 2020. Patients with co-morbid conditions such as hypertension and diabetes are disproportionately impacted by COVID-19. Hospital systems have been burdened nationwide, including community and safety-net hospitals who serve medically underserved populations, placing them at risk from a resource-needs standpoint. Our study aim is to describe the clinical presentation and outcomes of hospitalized patients with COVID-19, and to highlight the burden on community hospitals, in order to guide health policy and resource allocation in future crises.
METHOD(S): We conducted a retrospective case series of patients admitted to NYU Langone Hospital - Brooklyn between March 13th and April 4th, 2020. Reverse-transcriptase polymerase chain reaction nasopharyngeal swab confirmed infection with the SARS-CoV-2 virus. Clinical demographics were obtained from the electronic health record (Epic Hyperspace, Madison, WI). The primary outcome was time-to-event, defined as transfer to an intensive care unit, mechanical ventilation or death from time of admission. Statistical analysis was performed using Stata SE 16 (StataCorp, College Station, TX).
RESULT(S): There were 561 patients admitted with a median age of 61 years(IQR 48-74). See Table 1. The median time to composite event was 4.13 days(IQR: 2.23-7.97).
CONCLUSION(S): Our results show that the impact of COVID-19 on a community hospital is similar to what has been reported in the literature for tertiary centers, implying that safety-net hospitals can play an integral role in future impact mitigation. These implications hold true as the pandemic continues to disproportionately affect those with chronic diseases. As cases of COVID-19 near 20 million, our experience positions us as harbingers who can provide insight for resource allocation across the US. LEARNING OBJECTIVE #1: Patient Care: Identify the characteristics in patients with COVID-19 associated with increased risk for hospitalization LEARNING OBJECTIVE #2: Medical Knowledge: Understand the outcomes related to COVID-19 in a diverse population

BACKGROUND: A core responsibility of medical educators is to foster a strong sense of medical professional identity (PI). Few studies specifically examine the qualities that constitute the PI of physicians recognized for exemplary professionalism. We describe those qualities based on an assessment of PI to inform educational efforts and support learners' development of PI.
METHOD(S): We used Colby and Damon's criteria for selection of moral exemplars (1992) to invite nominations of exemplary faculty physicians at NYUGSOM from faculty and trainees. Participants completed the Professional Identity Essay (PIE), a 9-question reflective writing measure based on a wellknown model of adult development that explores meaning making on PI (Bebeau & Lewis, 2004; Kegan, 1982, 1994). Two raters with extensive training and experience in adult developmental theory rated PIE responses for stage or transition phase. PI stages include independent operator, teamoriented idealist, self-defining, and self-transforming. These stages reflect increasing complexity and internalization of PI. We also gathered information on specialty, years in practice, gender, and race/ethnicity.
RESULT(S): Two hundred and twelve faculty were nominated; 35 were invited to participate (based on number of nominations, diversity of ages, backgrounds and career stage), and 21 completed scorable PIEs. They were from 13 specialties; mean career length was 21.5 years (range 6-45), and 35% were female. All but 2 were Caucasian. PIE scores ranged from 3 to 4.5 (Table 1), demonstrating differing and increasingly complex and internalized ways faculty understand their PI, and that not all nominated exemplars share a singular view of professionalism.
CONCLUSION(S): Physicians nominated as exemplars of professionalism embody a range of professional identities and professionalism world-views. Our study provides rich descriptions of multiple pathways to strengthening a physician's professionalidentities, of critical importance to faculty and physician development in a milieu of challenges to recruitment and retention of physicians. This approach can also inform educators' efforts to support PI development in learners and support the development of learning communities that foster a growth mindset. LEARNING OBJECTIVE #1: Recognize importance of strong role models for MPI. LEARNING OBJECTIVE #2: Describe the varying levels of MPI in a cohort of exemplar physicians