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695


Navigating the Landscape of Precision Education: Insights from On-the-Ground Initiatives

Garibaldi, Brian T; Hollon, McKenzie M; Woodworth, Glenn E; Winkel, Abigail Ford; Desai, Sanjay V
A central goal of precision education (PE) is efficiently delivering the right educational intervention to the right learner at the right time. This can be achieved through a PE cycle that involves gathering inputs, using analytics to generate insights, planning and implementing interventions, learning and assessing outcomes, and then using lessons learned to inform modifications to the cycle. In this paper the authors describe three PE initiatives utilizing this cycle. The Graduate Medical Education Laboratory (GEL) uses longitudinal data on graduate trainee behavior, clinical skills, and wellness to improve clinical performance and professional fulfillment. The Transition to Residency Advantage (TRA) program uses learner data from medical school coupled with individualized coaching to improve the transition to residency. The Anesthesia Research Group for Educational Technology (TARGET) is developing an automated tool to deliver individualized education to anesthesia residents based on a longitudinal digital representation of the learner. The authors discuss strengths of the PE cycle and transferrable learnings for future PE innovations. Common challenges are identified, including related to data (e.g., volume, variety, sharing across institutions, using the electronic health record), analytics (e.g., validating augmented intelligence models), and interventions (e.g., scaling up learner assessments with limited resources). PE developers need to share their experiences in order to overcome these challenges, develop best practices, and ensure ethical development of future systems. Adapting a common framework to develop and assess PE initiatives will lead to a clearer understanding of their impact, help to mitigate potential risks, and allow deployment of successful practices on a larger scale.
PMID: 38109650
ISSN: 1938-808x
CID: 5612452

mRNA COVID-19 vaccine elicits potent adaptive immune response without the acute inflammation of SARS-CoV-2 infection

Ivanova, Ellie N.; Shwetar, Jasmine; Devlin, Joseph C.; Buus, Terkild B.; Gray-Gaillard, Sophie; Koide, Akiko; Cornelius, Amber; Samanovic, Marie I.; Herrera, Alberto; Mimitou, Eleni P.; Zhang, Chenzhen; Karmacharya, Trishala; Desvignes, Ludovic; Ødum, Niels; Smibert, Peter; Ulrich, Robert J.; Mulligan, Mark J.; Koide, Shohei; Ruggles, Kelly V.; Herati, Ramin S.; Koralov, Sergei B.
SARS-CoV-2 infection and vaccination elicit potent immune responses. Our study presents a comprehensive multimodal single-cell analysis of blood from COVID-19 patients and healthy volunteers receiving the SARS-CoV-2 vaccine and booster. We profiled immune responses via transcriptional analysis and lymphocyte repertoire reconstruction. COVID-19 patients displayed an enhanced interferon signature and cytotoxic gene upregulation, absent in vaccine recipients. B and T cell repertoire analysis revealed clonal expansion among effector cells in COVID-19 patients and memory cells in vaccine recipients. Furthermore, while clonal αβ T cell responses were observed in both COVID-19 patients and vaccine recipients, expansion of clonal γδ T cells was found only in infected individuals. Our dataset enables side-by-side comparison of immune responses to infection versus vaccination, including clonal B and T cell responses. Our comparative analysis shows that vaccination induces a robust, durable clonal B and T cell responses, without the severe inflammation associated with infection.
SCOPUS:85179086246
ISSN: 2589-0042
CID: 5620862

Bridging the Gap from Student to Doctor: Developing Coaches for the Transition to Residency

Winkel, Abigail Ford; Gillespie, Colleen; Park, Agnes; Branzetti, Jeremy; Cocks, Patrick; Greene, Richard E; Zabar, Sondra; Triola, Marc
BACKGROUND/UNASSIGNED:A lack of educational continuity creates disorienting friction at the onset of residency. Few programs have harnessed the benefits of coaching, which can facilitate self-directed learning, competency development, and professional identity formation, to help ease this transition. OBJECTIVE/UNASSIGNED:To describe the process of training faculty Bridge Coaches for the Transition to Residency Advantage (TRA) program for interns. METHODS/UNASSIGNED:Nineteen graduate faculty educators participated in a coaching training course with formative skills assessment as part of a faculty development program starting in January 2020. Surveys (n = 15; 79%) and a focus group (n = 7; 37%) were conducted to explore the perceived impact of the training course on coaching skills, perceptions of coaching, and further program needs during the pilot year of the TRA program. RESULTS/UNASSIGNED:Faculty had strong skills around establishing trust, authentic listening, and supporting goal-setting. They required more practice around guiding self-discovery and following a coachee-led agenda. Faculty found the training course to be helpful for developing coaching skills. Faculty embraced their new roles as coaches and appreciated having a community of practice with other coaches. Suggestions for improvement included more opportunities to practice and receive feedback on skills and additional structures to further support TRA program encounters with coaches. CONCLUSIONS/UNASSIGNED:The faculty development program was feasible and had good acceptance among participants. Faculty were well-suited to serve as coaches and valued the coaching mindset. Adequate skills reinforcement and program structure were identified as needs to facilitate a coaching program in graduate medical education.
PMID: 36351566
ISSN: 1087-2981
CID: 5357372

Using learning analytics in clinical competency committees: Increasing the impact of competency-based medical education

Carney, Patricia A; Sebok-Syer, Stefanie S; Pusic, Martin V; Gillespie, Colleen C; Westervelt, Marjorie; Goldhamer, Mary Ellen J
Graduate medical education (GME) and Clinical Competency Committees (CCC) have been evolving to monitor trainee progression using competency-based medical education principles and outcomes, though evidence suggests CCCs fall short of this goal. Challenges include that evaluation data are often incomplete, insufficient, poorly aligned with performance, conflicting or of unknown quality, and CCCs struggle to organize, analyze, visualize, and integrate data elements across sources, collection methods, contexts, and time-periods, which makes advancement decisions difficult. Learning analytics have significant potential to improve competence committee decision making, yet their use is not yet commonplace. Learning analytics (LA) is the interpretation of multiple data sources gathered on trainees to assess academic progress, predict future performance, and identify potential issues to be addressed with feedback and individualized learning plans. What distinguishes LA from other educational approaches is systematic data collection and advanced digital interpretation and visualization to inform educational systems. These data are necessary to: 1) fully understand educational contexts and guide improvements; 2) advance proficiency among stakeholders to make ethical and accurate summative decisions; and 3) clearly communicate methods, findings, and actionable recommendations for a range of educational stakeholders. The ACGME released the third edition CCC Guidebook for Programs in 2020 and the 2021 Milestones 2.0 supplement of the Journal of Graduate Medical Education (JGME Supplement) presented important papers that describe evaluation and implementation features of effective CCCs. Principles of LA underpin national GME outcomes data and training across specialties; however, little guidance currently exists on how GME programs can use LA to improve the CCC process. Here we outline recommendations for implementing learning analytics for supporting decision making on trainee progress in two areas: 1) Data Quality and Decision Making, and 2) Educator Development.
PMCID:9970252
PMID: 36821373
ISSN: 1087-2981
CID: 5448242

Biomarkers and cardiovascular events in patients with stable coronary disease in the ISCHEMIA Trials

Newman, Jonathan D; Anthopolos, Rebecca; Ruggles, Kelly V; Cornwell, Macintosh; Reynolds, Harmony R; Bangalore, Sripal; Mavromatis, Kreton; Held, Claes; Wallentin, Lars; Kullo, Iftikar J; McManus, Bruce; Newby, L Kristin K; Rosenberg, Yves; Hochman, Judith S; Maron, David J; Berger, Jeffrey S; ,
IMPORTANCE:Biomarkers may improve prediction of cardiovascular events for patients with stable coronary artery disease (CAD), but their importance in addition to clinical tests of inducible ischemia and CAD severity is unknown. OBJECTIVES:To evaluate the prognostic value of multiple biomarkers in stable outpatients with obstructive CAD and moderate or severe inducible ischemia. DESIGN AND SETTING:The ISCHEMIA and ISCHEMIA CKD trials randomized 5,956 participants with CAD to invasive or conservative management from July 2012 to January 2018; 1,064 participated in the biorepository. MAIN OUTCOME MEASURES:Primary outcome was cardiovascular death, myocardial infarction (MI), or hospitalization for unstable angina, heart failure, or resuscitated cardiac arrest. Secondary outcome was cardiovascular death or MI. Improvements in prediction were assessed by cause-specific hazard ratios (HR) and area under the receiver operating characteristics curve (AUC) for an interquartile increase in each biomarker, controlling for other biomarkers, in a base clinical model of risk factors, left ventricular ejection fraction (LVEF) and ischemia severity. Secondary analyses were performed among patients in whom core-lab confirmed severity of CAD was ascertained by computed cardiac tomographic angiography (CCTA). EXPOSURES:Baseline levels of interleukin-6 (IL-6), high sensitivity troponin T (hsTnT), growth differentiation factor 15 (GDF-15), N-terminal pro-B-type natriuretic peptide (NT-proBNP), lipoprotein a (Lp[a]), high sensitivity C-reactive protein (hsCRP), Cystatin C, soluble CD 40 ligand (sCD40L), myeloperoxidase (MPO), and matrix metalloproteinase 3 (MMP3). RESULTS:Among 757 biorepository participants, median (IQR) follow-up was 3 (2-5) years, age was 67 (61-72) years, and 144 (19%) were female; 508 had severity of CAD by CCTA available. In an adjusted multimarker model with hsTnT, GDF-15, NT-proBNP and sCD40L, the adjusted HR for the primary outcome per interquartile increase in each biomarker was 1.58 (95% CI 1.22, 2.205), 1.60 (95% CI 1.16, 2.20), 1.61 (95% 1.22, 2.14), and 1.46 (95% 1.12, 1.90), respectively. The adjusted multimarker model also improved prediction compared with the clinical model, increasing the AUC from 0.710 to 0.792 (P < .01) and 0.714 to 0.783 (P < .01) for the primary and secondary outcomes, respectively. Similar findings were observed after adjusting for core-lab confirmed atherosclerosis severity. CONCLUSIONS AND RELEVANCE:Among ISCHEMIA biorepository participants, biomarkers of myocyte injury/distension, inflammation, and platelet activity improved cardiovascular event prediction in addition to risk factors, LVEF, and assessments of ischemia and atherosclerosis severity. These biomarkers may improve risk stratification for patients with stable CAD.
PMID: 37604357
ISSN: 1097-6744
CID: 5598422

Ready Day One: What Residents and Program Directors Think is Needed for a Successful Transition to Residency

George, Karen; Winkel, Abigail Ford; Banks, Erika; Hammoud, Maya M; Wagner, Sarah A; Hazzard Bigby, Brittanie; Morgan, Helen Kang
OBJECTIVE:To evaluate perceived gaps in preparedness, current on-boarding practices, and need for specialty wide resources in the transition to residency training in obstetrics and gynecology (OB/GYN) DESIGN, SETTING, AND PARTICIPANTS: A cross-sectional survey of current U.S. OB/GYN residents and program directors (PDs) at the time of the resident in-training exam was conducted in 2022. Both groups provide demographic information and identified specific knowledge, skills, and abilities in need of more preparation at the start of residency. PDs were queried on perceptions of readiness for their current first year class, educational on-boarding practices, and their preference for standardized curricular materials and assessment tools. Chi-squared and Kruskal-Wallis tests were used to compare perceptions of skills deficits between PDs and residents, and the relationship of preparedness to program type and resident year in training. RESULTS:Response rates for residents and program directors were 64.9% and 72.6% respectively. A majority (115/200, 57.5%) of program directors agreed or strongly agreed with the statement, "In general, I feel that my new interns are well prepared for residency when they arrive at my program." Both groups agreed that basic suturing and ultrasound skills were deficits. Residents identified a need for better preparation in management of inpatient issues while PDs identified time management skills as lacking. There was considerable heterogeneity of program on-boarding practices across the specialty. Most PDs agreed or strongly agreed that a standardized curriculum (80.5%, 161/200) and assessment tools (75.3%, 150/199) would be helpful. CONCLUSION/CONCLUSIONS:OBGYN PDs feel that not all residents arrive prepared for residency and overwhelmingly support the development of standardized transition curricular and assessment tools, similar to the curriculum developed in general surgery. Based on input from PDs and residents, early curricular efforts should focus on basic surgical, ultrasound, and time management skills and on management of inpatient issues.
PMID: 37821351
ISSN: 1878-7452
CID: 5604412

Applicant Experience in Communication With Residency Programs After the Introduction of Program Signaling

Schoppen, Zachary; Morgan, Helen K; Hammoud, Maya; Marzano, David; George, Karen; Winkel, Abigail Ford
OBJECTIVE:Examine the applicant experience after introduction of program signaling for the 2023 obstetrics and gynecology (OBGYN) residency application cycle. DESIGN/METHODS:Responses to an online survey of OBGYN applicants participating in the 2023 match who participated in residency program signaling were compared to responses from a similar survey conducted in 2022. Demographic information included personal and academic background and how applicants and advisors communicated with programs. Numbers of applications and interviews, second look visits, away rotations, manner of contact, and timing of communication was compared. Statistical analysis included ANOVA for interval data, and χ2 and Kruskal-Wallis tests for categorical data. RESULTS:A total of 711 of 2631 (27%) applicants responded in 2022 and 606 of 2492 (24.3%) responded in 2023. Approximately 2/3 of gold signals and 1/3 of silver signals led to an interview. There was no change in number of applications or interviews per applicant, but there was a broader distribution of interviews per applicant in 2023. Applicants in 2023 were less likely to engage in preinterview communication or do an away rotation to indicate interest in a program. There was decreased communication between applicants and programs after signaling was introduced. Informal communication continued to differ by racial and medical school background. Applicants from DO programs and international medical graduates (IMG) had more communication with programs than MD applicants but received fewer interview invitations. Fewer Black and Latin(x)/Hispanic applicants had faculty reach out to residency programs on their behalf compared to White and Asian applicants. There were differences in the number of interviews received based on racial and ethnic identity. CONCLUSIONS:In the first year after implementation of program signaling, there was a decrease in preinterview communication and a broader distribution of interviews among applicants. Further efforts to create standard means of program communication may help to begin leveling the uneven playing field for applicants.
PMID: 37633809
ISSN: 1878-7452
CID: 5599182

Addressing social determinants of health in primary care: a quasi-experimental study using unannounced standardised patients to evaluate the impact of audit/feedback on physicians' rates of identifying and responding to social needs

Gillespie, Colleen; Wilhite, Jeffrey A; Hanley, Kathleen; Hardowar, Khemraj; Altshuler, Lisa; Fisher, Harriet; Porter, Barbara; Wallach, Andrew; Zabar, Sondra
BACKGROUND:Although efforts are underway to address social determinants of health (SDOH), little is known about physicians' SDOH practices despite evidence that failing to fully elicit and respond to social needs can compromise patient safety and undermine both the quality and effectiveness of treatment. In particular, interventions designed to enhance response to social needs have not been assessed using actual practice behaviour. In this study, we evaluate the degree to which providing primary care physicians with feedback on their SDOH practice behaviours is associated with increased rates of eliciting and responding to housing and social isolation needs. METHODS:Unannounced standardised patients (USPs), actors trained to consistently portray clinical scenarios, were sent, incognito, to all five primary care teams in an urban, safety-net healthcare system. Scenarios involved common primary care conditions and each included an underlying housing (eg, mould in the apartment, crowding) and social isolation issue and USPs assessed whether the physician fully elicited these needs and if so, whether or not they addressed them. The intervention consisted of providing physicians with audit/feedback reports of their SDOH practices, along with brief written educational material. A prepost comparison group design was used to evaluate the intervention; four teams received the intervention and one team served as a 'proxy' comparison (no intervention). Preintervention (February 2017 to December 2017) rates of screening for and response to the scripted housing and social needs were compared with intervention period (January 2018 to March 2019) rates for both intervention and comparison teams. RESULTS:108 visits were completed preintervention and 183 during the intervention period. Overall, social needs were not elicited half of the time and fully addressed even less frequently. Rates of identifying the housing issue increased for teams that received audit/feedback reports (46%-60%; p=0.045) and declined for the proxy comparison (61%-42%; p=0.174). Rates of responding to housing needs increased significantly for intervention teams (15%-41%; p=0.004) but not for the comparison team (21%-29%; p=0.663). Social isolation was identified more frequently postintervention (53%) compared with baseline (39%; p=0.041) among the intervention teams but remained unchanged for the comparison team (39% vs 32%; p=0.601). Full exploration of social isolation remained low for both intervention and comparison teams. CONCLUSIONS:Results suggest that physicians may not be consistently screening for or responding to social needs but that receiving feedback on those practices, along with brief targeted education, can improve rates of SDOH screening and response.
PMID: 35623722
ISSN: 2044-5423
CID: 5284022

Point-counterpoint: Time to wash away the SOAP note-Or merely rinse it?

Rodman, Adam; Schaye, Verity; Hofmann, Heather; Airan-Javia, Subha L
PMID: 37530094
ISSN: 1553-5606
CID: 5618942

Deep learning integrates histopathology and proteogenomics at a pan-cancer level

Wang, Joshua M; Hong, Runyu; Demicco, Elizabeth G; Tan, Jimin; Lazcano, Rossana; Moreira, Andre L; Li, Yize; Calinawan, Anna; Razavian, Narges; Schraink, Tobias; Gillette, Michael A; Omenn, Gilbert S; An, Eunkyung; Rodriguez, Henry; Tsirigos, Aristotelis; Ruggles, Kelly V; Ding, Li; Robles, Ana I; Mani, D R; Rodland, Karin D; Lazar, Alexander J; Liu, Wenke; Fenyö, David; ,
We introduce a pioneering approach that integrates pathology imaging with transcriptomics and proteomics to identify predictive histology features associated with critical clinical outcomes in cancer. We utilize 2,755 H&E-stained histopathological slides from 657 patients across 6 cancer types from CPTAC. Our models effectively recapitulate distinctions readily made by human pathologists: tumor vs. normal (AUROC = 0.995) and tissue-of-origin (AUROC = 0.979). We further investigate predictive power on tasks not normally performed from H&E alone, including TP53 prediction and pathologic stage. Importantly, we describe predictive morphologies not previously utilized in a clinical setting. The incorporation of transcriptomics and proteomics identifies pathway-level signatures and cellular processes driving predictive histology features. Model generalizability and interpretability is confirmed using TCGA. We propose a classification system for these tasks, and suggest potential clinical applications for this integrated human and machine learning approach. A publicly available web-based platform implements these models.
PMCID:10518635
PMID: 37582371
ISSN: 2666-3791
CID: 5590072