Faculty Bibliography

BACKGROUND: At Bellevue Hospital Center (BHC), we have a robust Unannounced Standardized Patient (USP) program, where trained actors portraying real patients in the clinical setting, incognito, assess the residents' skills following their visit. We sought to determine the relationship between USP ratings of residents' skills and clinical outcomes among the residents' continuity patient panels to define educationally sensitive patient outcomes. METHODS: We assembled a retrospective cohort of PGY 2 internal medicine residents with at least 2 USP visits between 7/1/14-6/30/15 and ambulatory care patient panels at BHC. The two outcome variables were the percentage of hypertensive patients in the residents' panel with blood pressure (BP) <140/90, and the average of the most recent glycosylated hemoglobin (HbA1C) result among the residents' patients with diabetes. The predictor variables included mean USP ratings of residents' clinical skills and mean faculty rating of the residents' clinic notes (scored for quality on a 0 to 3 scale). USPs used a behaviorally anchored checklist (not done, partly done, well done) for the following domains: communication, case specific assessment, patient education, physical examination, professionalism, management plan, patient satisfaction, and patient activation measure. We tested the correlations between USP scores with BP and HbA1C control, and then developed multivariate, linear regression models of USP scores on BP and HbA1C scores, respectively, each controlling for Avg. Chronic health score (ACHS, derived by scoring different clinical conditions by acuity and used to determine if the panel is getting sicker over time) and total number of patients in the panel (TNPP) because these variables were correlated with both the outcome and predictor variables. RESULTS: 29 PGY 2 residents had a mean of 2.5 (SD 1.0) USP visits during the study period. Residents' patient panels size varied (median 124, range 62- 171) and mean patient age was 48 years (SD 1.4). Patient Activation scores were correlated with Average Chronic Health Score (r = .482, p = .008) and Panel Average last A1c (r = -.311, p = .10). Patient activation scores explained 16% variance in the mean panel last HgA1c, (adjusted R2 .137, p = .08). Case specific Assessment & Patient Education skills across USP cases explained 21.5% of the variance and the Average Chart Note Score explained 14.4% of the variance in % of Hypertension controlled (adjusted R2.378, p < .009). CONCLUSIONS: This exploratory study suggests that learnable resident clinical skills are associated with quality of care indicators for HTN and DM control. In particular, being able to activate patients, assess and educate them and write high quality notes are pathways to quality care. Next steps are to confirm these findings in a larger dataset. Doing so will help align medical education with patient safety and care quality and provide guidance for educational and clinical research aimed at improving the health of populations served

BACKGROUND: Effective smoking cessation counseling improves smokers' health and quality of life. As part of our assessment program, an Unannounced Standardized Patient (USP) case was developed to measure residents' performance in a routine visit with a smoker. METHODS: The USP was a 40 year-old male new patient presenting with heartburn. He began smoking up to two packs/day at 22 years old; at the time of the visit, he reports having cut down to one pack/day and quitting cold turkey twice in the past only to return to smoking. If the resident engages him, he discusses his relationship with smoking and the possibility of quitting. TheUSP received 6 hours of character and checklist training to ensure standardized portrayal and evaluation. Data was collected using 2 forms of assessment: a post-visit USP checklist and a systematic review of the EMR (lab orders, prescriptions, and referrals). The 170- item USP checklist measured communication, patient education, assessment skills, and case-specific items. Each response option included descriptive behavioral anchors and was rated as not done, partly done, or well done. RESULTS: Data was examined from 73 USP visits from 2009-2015. Mean visit length = 37 min, SD = 15 min (range: 15 to 95 min). Overall communication scores ranged from 17 to 100% with an average of 62% (Cronbach's alpha = 0.75). All residents documented History of Tobacco Use or Tobacco Use Disorder in the EMR, and the majority (82%) prescribed smoking cessation medication. There was variation in the sophistication of smoking cessation-counseling approach. Whilemost residents (78%) discussed the risks of smoking and/or the benefits to quitting, significantly fewer (48%) explored the patient's view of the pros and cons of his smoking (p = 0.00). Residents who prescribed smoking cessation medication and discussed risks/benefits to smoking/quitting (N = 31) were compared to residents who did the same but also invited the patient to discuss his personal pros and cons of smoking (N = 29). Groups were not significantly different by PGY or gender. Patients who were asked to discuss their pros/cons rated the resident higher on patient activation questions (0-2 point scale), including "Helped you understand the importance of quitting smoking" (1.38 vs 0.90, p = 0.00), "Made you want to change your smoking" (1.10 vs 0.52, p = 0.00), and "Made you feel like you would be able to quit smoking" (1.07 vs 0.35, p = 0.00). There were no significant differences in labs ordered, referrals to a smoking cessation program, or quality of documentation. CONCLUSIONS: While all residents ask about tobacco use and most appropriately prescribe medication, fewer than half demonstrate the skills known to motivate patients to quit smoking. Curricula needs to reinforce the importance of a patient discussing their personal relationship with smoking in order to feel activated and willing to engage in cessation

BACKGROUND: Safe, high quality outpatient care often depends on the degree to which patients understand their situation and how to follow through on physician recommendations. However, we do not know enough about how often physicians focus on ensuring that their patients have achieved these understandings by the end of the visit and whether such end-of-visit practices are associated with physicians' communication, patient education and activating skills. METHODS: Two Unannounced Standardized Patient cases (highly trained actors who present as real patients) were delivered to 71 internal medicine residents in two clinics: one required the physician to identify a patient's depression and engage him in follow-up care, and the other required the physician to recognize a patient's failure to use her asthma medicine correctly and educate her in using it properly. End-of-visit practices were: reviewing the plan; asking if further questions; giving information about follow-up care and further contact; and helping the patient navigate the system in order to follow through on next steps. Each was assessed by the SP as not done, partly done, or well done. SPs also rated physicians' communication skills, patient activating skills, and case-specific education skills. Summary scores were calculated as% of items well done. RESULTS: Close to three-quarters of the physicians reviewed the plan with the patient and invited further questions in the depression case and slightly more than half did so in the asthma case (56 and 60%). Patients were given complete information about follow-up care and how to navigate the system in just under half of depression visits (49 and 47%) and just over half of asthma visits (58 and 58%). On average, residents were rated as performing 61% of these 8 items well (SD 28%) across both cases. Primary care residents performed significantly better than categorical internal medicine residents (67%vs 47%, p = .004). There were no differences by physician gender. End of visit scores were significantly positively correlated with both general and casespecific clinical skills, and after controlling for the variance contributed by the program (R2 = 12%, p = .004), case-specific education scores explained 10% of the variance in end of visit score (p = .005), patient activating skills 10% of the variance (p = .002) and communication skills 13% of the variance (p = .001). With all variables in the model, only the general communication domain of patient education and counseling was independently associated with end of visit scores (Std Beta = .35, p = .015). CONCLUSIONS: Had these patients been real patients, in one-quarter to onehalf of the visits, the patient would have left not fully understanding the plan or how to follow-through on care. Resident physicians with more effective communication and patient activating skills tended to provide safer end-of-visit care, suggesting that these may reflect an outpatient safety orientation or skillset

NEEDS AND OBJECTIVES: Standardized Patients (SPs) are integral to health care professions (HCPs) training. We must understand this workforce, make effective use of SPs' skills, and ensure they accurately portray cases and rate learners. To be authentic, simulation should reflect the demographics of the population served, while providing exposure to less commonly seen patients. We created an SP database to facilitate our work with SPs; review their demographic characteristics; and align information on SP performance -to better serve our educational mission. SETTING AND PARTICIPANTS: NYSIM (Simulation Center for NYU Langone and the City University of NY) serves hundreds of HCP training programs for learners at all levels. While sharing common resources, many programs independently recruit and train SPs. DESCRIPTION: We fielded a web-based survey for SPs and staff to populate the database. Survey items were iteratively reviewed by staff and SPs to ensure items elicited key information. Questions included basic demographics; SP experience/training; other professional background; and relevant physical findings (eg scars, cardiac findings). SPs also uploaded a headshot and resume. Staff separately input information about SPs' work on cases and programs; information about case portrayals; types of cases for which the SP is best suited, and other relevant information. EVALUATION: To date, we have 232 SP surveys, representing the majority of SPs at NYSIM. Demographics included gender (43% male, 56% female, 1% transgender), age range (x = 34.9 years, range teen to 75+) and selfidentified race (71% Caucasian, 17% African-American, 25.6% Asian/South Asian, 3.5% Middle Eastern, 3% Native American/Pacific Islander and 9% other). 22%are bilingual, with over 20 languages represented. SPs had a broad range of SP experience (x = 2.8 years, S.D. = 1.8, range 0-20 years). Almost all SPs were trained in basic case portrayal, with others being trained in aspects of the physical exam, emotional issues, giving feedback, and high stakes rating. SPs bring other skills to their work, including teaching (75%) or healthcare (12%). Survey information helps educators recruit SPs and identify (re)training needs. SPs who perform high stakes exams or are Unannounced Standardized Patients are shielded from general recruitment in order to maintain their anonymity. DISCUSSION/REFLECTION/LESSONS LEARNED: An SP database is useful for a high volume simulation center. Information in a searchable SP data base allows programs to understand the potential pool and expertise of SPs, and to track learners' exposure to specific SPs (this is relevant as our internal data reveal that SPs with more experience tend rate towards the middle of the scale). The demographic characteristics of our SPs broadly match the profile of our healthcare systems, and tracking the data allows us to maintain a good fit between SPs and our environment

BACKGROUND: At NYU, as part of a comprehensive objective structured clinical skills exam, experienced medical educators judge clinical knowledge, decision-making, and clinical reasoning skills of trainees based on their patient notes. Despite being rubric-driven, this task requires tremendous time and effort to establish consistent scoring, delaying and limiting individualized feedback. We conducted pilot machine learning text classification studies to establish if accurate automated scoring of clinical notes is possible. METHODS: As a use case, we tested 100 student written clinical notes from7 standardized patient cases (Vision Loss, Tel Diarrhea, Difficulty Sleeping, Shoulder Pain, Failure To Thrive, Abdominal, Pain, Palpitations) that had been scored for quality of clinical reasoning by faculty on a 1-4 scale. In order to assess performance of NLP strategies to categorize students in meaningful groups we dichotomized students based on their faculty given scores by case into "failing" (score of 1, 5-18 students per case) and "passing" (score 2,3,4). We treated each task as a binary classification task in a text classification pipeline. First, we treated each note as a bag of tokens and weight each token with term frequency-inverse document frequency (TFIDF) a numerical statistic that reflects howimportant aword is to a document. We then applied 3 different classification algorithms (random forests, support vector machines, and Bayesian logistic regression) and measured discriminatory performance using Area Under Curve (AUC) in a cross validation evaluation design. RESULTS: TFDIF performed with AUCs between 0.669 and 0.905. Logistic regression provided the highestAUC in four cases: Difficulty Sleeping (0.905), Shoulder Pain (0.618), Failure To Thrive (0.717) and Abdominal Pain (0.892). As we observed the highest AUCs in Difficulty Sleeping and Abdominal Pain cases, we have begun to refine the algorithm for these two cases by identifying the importance features that lead faculty to give students to a higher grade and improve the accuracy of NLP based scoring. Promising features include the presence and sequence of certainwords in the problem representation, sentence length in the management section, ranking of the differential diagnosis, sequence between key words (e.g. rule out appendicitis), and evidence of "thinkingness" or what many call semantic qualifiers. CONCLUSIONS: With additional effort to build targeted case specific classifiers for clinical content and reasoning, a validated machine-learning model may achieve partial or full automation of grading of the notes. This work, which builds on decades of clinical decision-making and critical reasoning research, may provide medical trainees with more and potentially better feedback; facilitating learning of clinical reasoning, freeing faculty to coach this process, and in the long run impacting healthcare quality and patient safety

BACKGROUND: The AAMC has identified 13 Entrustable Professional Activities (EPAs) that all entering residents should be expected to perform on day 1 of residency without direct supervision regardless of specialty choice. We developed an immersive, Night on call (NOC) simulation to understand the measure of entrustment of all 13 Core EPAs from the perspective of patients, nurses, attendings, and peers. METHODS: NOC is a 4-hour simulation, during which a medical student rotates through a series of authentic clinical coverage scenarios including: 4 standardized patient (SP) cases with varying degrees of complexity, each of which require first answering a call from a standardized nurse, (SN), then evaluating a SP with the SN in the room, making immediate management decisions and writing a coverage note; a phone call to an attending (Attn, an experienced clinician) to orally present (OP), and discuss the case, formulation of a clinical question and finding a best answer using digital library resources (EBM), a test of ability to recognize a pre-entrustable peer, and a handoff of 4 cases to a peer (HOff, portrayed by an senior medical student). Competency assessments were based on validated tools where available. Each rater provided an entrustment judgment. This included 9 raters providing a total of 16 entrustment judgments: 4 SPs and 3 SNs (1 rating competency and 1 rating communication each), 1 Attn based on OP, 1 peer rating based on the HOff (1 item each). Raters were trained in both case portrayal and rating reliability. This study is IRB approved. After exploring the relationships among competency measures and entrustment judgements, to test the hypothesis that NOC measures trustworthiness of our near graduates, we conducted a one-factor (entrustment) confirmatory factor analysis (CFA) with the 16-entrustment items allowing the ratings from the same raters and between raters on the same case to correlate. The CFA was conducted with a means and variance adjusted weighted-least squares estimation (WLSMV) to take the ordinal distributions of the entrustment items into account. RESULTS: 73 medical students (39 women; Age 26.5 (+2.6) years) completed NOC. The one-factor CFA model fit the data (chi² = 155.27, df = 112, p < .001, CFI = 0.97, TLI = 0.97, RMSEA = 0.07, p > 0.05). All but 2 of the 16 factor loadings were greater than 0.3, (Attn factor loading = 0.23 and the SP ratings from the first clinical case of NOC sequence (0.21)). CONCLUSIONS: A single-factor model with 16measures fit the entrustment framework within an ecologically valid simulated workplace suggesting that an individual student's clinical trustworthiness is measurable across discrete work activities. This work provides an assessment framework for the educational handoff from medical school to residency to ensure quality of care and patient safety

NEEDS AND OBJECTIVES: To address rising education costs, physician shortages, and the need for educational reform, several medical schools have developed accelerated 3-year MD programs. In 2013, NYU School of Medicine began its new 3-year MD program with guaranteed acceptance into residency upon graduation. Using the AAMC's 13 Core Entrustable Professional Activities for Entry into Residency (CEPAER) framework, we designed an immersive 4-hour simulated "Night on Call" (NOC) experience to compare performance of our first graduating cohort of fifteen 3-year MD students (3A), with third (3T) and fourth year (4T) students in the traditional 4-year MD program. SETTING AND PARTICIPANTS: 73 medical students (39 women, age 26.5 (+2.6) years; 36 '3T', 12 '3A', 25 '4T') completed an IRB-approvedNOC at our simulation center 4 weeks prior to the end of their third or final year of medical school. DESCRIPTION: We developed NOC to measure competence and entrustment across all 13 CEPAERs from the perspective of patients, nurses, and attendings. During the simulation, a medical student rotated through a series of 8 clinical coverage scenarios including: 4 standardized patient (SP) cases with varying degrees of complexity, each of which require answering a call from a standardized nurse (SN), evaluating an SP with the SN in the room, making immediate management decisions and writing a coverage note; a phone call to an experienced clinician to orally present (OP) the case; formulation of a clinical question and finding the most appropriate evidence-based medicine (EBM) answer using digital library resources; a clinical vignette (CV) to test ability to recognize a pre-entrustable peer; and a handoff (HO) of 4 cases to a peer (a senior medical student). CEPAERs assessments based on validated tools included communication, physical exam, patient education and interprofessional teamwork skills assessed by an SP and SN, and clinical reasoning based on notes, OP, EBM, CV, HO. Each rater also provided an entrustment judgment. EVALUATION: Although overall student performance improved across cases and some interesting individual performance patterns emerged, there were no significant differences across the three groups in the core competency and entrustment measures evaluated across various NOC activities. DISCUSSION/REFLECTION/LESSONS LEARNED: The 13 CEPAERs are meant to define what students should be expected to perform (without direct supervision) prior to entering residency. Our results, based on multiple rater perspectives, suggest that our cohort of 3A students is as prepared for residency as their 4T counterparts

BACKGROUND: Training residents to effectively practice value-based care is challenging. We hypothesized that residents with better communication skills would order fewer unnecessary tests and prescribe more appropriate care. We used a USP case of a patient with uncontrolled asthma to examine the relationship between value-based care and communication skills. METHODS: A 25 year-old female USP presented as a new patient to a medicine resident's clinic, reporting asthma since childhood with worsening symptoms over the past few months. At the time of the visit, she was using her albuterol inhaler multiple times daily, without any additional asthma treatment, and was unsure whether she was using it properly. Data was collected using two forms of assessment: a post-visit USP checklist and a systematic review of the corresponding clinic note to examine treatment recommendations including referrals and quality of documentation. The USP checklist measured communication, patient education, and assessment skills. Each response option included descriptive behavioral anchors and was rated as not done, partly done, or well done. Domain scores were calculated as percent items rated well done. RESULTS: 141 USP visits were made from 2009 to 2016 with a mean visit length = 88 min, SD= 28 min (range: 40 to 180 min). Almost all residents (92%) evaluated the patient's asthma with a pulmonary examination. The most common treatment prescribed was albuterol and an inhaled steroid, with or without a spacer (79%). The majority of residents (53%) did not order any additional studies; 21% ordered one study, and 26% ordered two or more studies. Study orders fell into one of three categories: gold (appropriate/recommended: PFTs, flu shot, HIV), grey (pulmonary consult, HCG), or inappropriate (TSH, A1C). Across the 141 visits, 129 studies were ordered; 46% were gold, 5% were grey, and 49% were inappropriate. The most common study ordered was a PFT (31%). 87% of single study orders were gold, but 92% of multiple orders included at least one inappropriate study. Residents who did not order any studies had significantly higher patient education and counseling skills than residents who ordered one or more studies (54% vs 34%, p = 0.00) and were more likely to explain how to correctly use an inhaler than residents who ordered one or more studies (48% vs 27%, p = 0.01). These residents also had significantly higher management and treatment skills (61% vs 39%, p = 0.00) and overall communication skills (68% vs 55%, p = 0.01). There were no significant differences between groups in medications prescribed or in quality of documentation. CONCLUSIONS: Effective communication skills may contribute to valuebased care through appropriate patient education and ordering of fewer inappropriate studies. Rigorous curricula and assessment of resident's patient education skills should be in place to help both patients and health care system achieve value-based care

BACKGROUND: Obesity is under-treated and primary care teams find it difficult to provide effective lifestyle-based weight management counseling. Further, only 10% of eligible patients attendMOVE!, theVAweight management and health promotion program. We developed an intervention called Goals for Eating and Moving (GEM) to improve counseling within primary care (PC) and increase attendance in intensive weight management programs such as MOVE!. METHODS: Veterans with a Body Mass Index of greater than or equal to 30 or between 25 and 29.99 with at least one comorbidity were recruited by phone and randomized toGEMor "Enhanced Usual Care" (EUC). GEMutilizes the Patient Aligned Care Teams (PACTs) within the VA to deliver 5As counseling (Assess, Advise, Agree, Assist and Arrange) to promote modest weight loss and behavior change. Participants use a goal-setting tool to generate tailored materials, which facilitates in-person and phone counseling with health coaches. Coaches support PACTcounseling during regular PC visits and encourage participants to join VA weight management services. Veterans in GEM received the intervention and Veterans in EUC met with a coach to receive the VA "healthy living messages" pamphlet. At baseline and 3 months, participants had weight measurements and completed surveys. We used the Paffenbarger Physical Activity Questionnaire and a 17-item screener to derive fruit and vegetable intake, energy from fat, and dietary fiber. Vegetable intake (leafy greens/salad) and sugar-sweetened beverage were measured as individual items. We performed per-protocol analyses (Wilcoxon Rank sums test and Spearman Correlation) to assess the relationship between GEM and different variables. RESULTS: Thirty-one Veterans (mean age = 53.48, 63% male, mean BMI = 31.72) enrolled and 25 returned at 3-months (1 dropped out and 5 were lost-tofollow up). Those in GEM lost significantly more weight at 3-months (-1.59 kg, SD = 1.76) than those in EUC (-0.63 kg, SD = 3.42, p = 0.03). There were no statistically significant differences in diet and physical activity. For Veterans that received GEM, higher number of phone coaching sessions was correlated with weight loss (Spearman Correlation -0.58, p = 0.09). CONCLUSIONS: This early analysis indicates that GEM promotes small but significant (p = 0.03) weight loss at 3-months and identified the need for high patient retention and engagement, since the number of health coaching calls may correlate with weight loss. Based on this we have refined protocols for phone coaching to ensure that scheduling and reminder calls are patientcentered. This pilot study informed the development of a multi-site cluster- RCT of GEM to begin in June 2017 (NIH # 1R01 DK111928-01)

AIM: To assess the feasibility and utility of measuring baseline professional identity formation (PIF) in a theory-based professionalism curriculum for early medical students. METHODS: All 132 entering students completed the professional identity essay (PIE) and the defining issues test (DIT2). Students received score reports with individualized narrative feedback and wrote a structured reflection after a large-group session in which the PIF construct was reviewed. Analysis of PIEs resulted in assignment of a full or transitional PIF stage (1-5). The DIT2 score reflects the proportion of the time students used universal ethical principles to justify a response to 6 moral dilemma cases. Students' reflections were content analyzed. RESULTS: PIF scores were distributed across stage 2/3, stage 3, stage 3/4, and stage 4. No student scores were in stages 1, 2, 4/5, or 5. The mean DIT2 score was 53% (range 9.7?76.5%); the correlation between PIF stage and DIT score was rho = 0.18 (p = 0.03). Students who took an analytic approach to the data and demonstrated both awareness that they are novices and anticipation of continued PIF tended to respond more positively to the feedback. CONCLUSIONS: These PIF scores distributed similarly to novice students in other professions. Developmental-theory based PIF and moral reasoning measures are related. Students reflected on these measures in meaningful ways suggesting utility of measuring PIF scores in medical education.