BFAM Member Spotlights

Meet the members of the Stanford Medicine Black Faculty Affinity Meetings (BFAM), a network created through OFDD's Community Support Initiative. BFAM is intended to provide networking and social engagement opportunities for Stanford Medicine faculty across all clinical lines and departments.

Carla Pugh, MD, PhD

Department of Surgery

Director, Technology Enabled Clinical Improvement (T.E.C.I.) Center Member, Commission on Justice & Equity

Research Interests
Simulation and advanced engineering technologies to develop new approaches for assessing and defining mastery in clinical procedural skills.

Something you wouldn’t know just by looking at me.
Anything outdoors - fishing, white water rafting and gardening

What are some of your favorite social activities?
Fishing, white water rafting, scuba, hiking, gardening, sight seeing

Full Stanford Profile

Thomas Krummel Professor

(650) 725-6630

cpugh@stanford.edu

Bio

Carla Pugh is Professor of Surgery at Stanford University School of Medicine. She is also the Director of the Technology Enabled Clinical Improvement (T.E.C.I.) Center. Her clinical area of expertise is Acute Care Surgery. Dr. Pugh obtained her undergraduate degree at U.C. Berkeley in Neurobiology and her medical degree at Howard University School of Medicine. Upon completion of her surgical training at Howard University Hospital, she went to Stanford University and obtained a PhD in Education. She is the first surgeon in the United States to obtain a PhD in Education. Her goal is to use technology to change the face of medical and surgical education. Her research involves the use of simulation and advanced engineering technologies to develop new approaches for assessing and defining competency in clinical procedural skills. Dr. Pugh holds three patents on the use of sensor and data acquisition technology to measure and characterize hands-on clinical skills. Currently, over two hundred medical and nursing schools are using one of her sensor enabled training tools for their students and trainees. Her work has received numerous awards from medical and engineering organizations. In 2011 Dr. Pugh received the Presidential Early Career Award for Scientists and Engineers from President Barak Obama at the White House. She is considered to be a lead, international expert on the use of sensors and motion tracking technology for performance measurement. In 2014 she was invited to give a TEDMED talk on the potential uses of technology to transform how we measure clinical skills in medicine. In April 2018, Dr. Pugh was inducted into the American Institute for Medical and Biological Engineering.

Publications

MS-TCRNet: Multi-Stage Temporal Convolutional Recurrent Networks for action segmentation using sensor-augmented kinematics PATTERN RECOGNITION Goldbraikh, A., Shubi, O., Rubin, O., Pugh, C. M., Laufer, S. 2024; 156 More

View details for DOI 10.1016/j.patcog.2024.110778

View details for Web of Science ID 001276182900001
Key Issues in Surgical Residency Education: Recommendations of the Blue Ribbon II Committee Residency Education Subcommittee. Annals of surgery Mellinger, J. D., Brasel, K., Elster, E., Fried, G., Hashimoto, D. A., Jarman, B., Joshi, A. R., Kelz, R. R., Lindeman, B., Pugh, C., Reznick, R. 2024 More

Abstract

In September 2022, a summit was convened by the American Board of Surgery (ABS) to discuss competency-based reform in surgical education. A key output of that summit was the recommendation that the prior work of the Blue Ribbon I Committee convened 20 years earlier be revived. With leadership from the American College of Surgeons (ACS) and the American Surgical Association (ASA) , the Blue Ribbon Committee (BRC) II was subsequently convened. This paper describes the output of the Residency Education Subcommittee of the BRC II Committee. The Subcommittee organized its work around prioritized themes including curriculum, assessment, and transition to practice. Top recommendations, time-based action steps, potential barriers, and required resources were detailed and vetted through group discussion, broader Committee review and critique, and subsequent refinement. Primary concluding emphases included transitioning to a competency-based training model, facilitating dynamically capable curricular reform emphasizing the digital transformation of surgical care, using predictive analytic assessment strategies to optimize training effectiveness and efficiency, and creating mentorship strategies to govern the transition from training to independent practice in an outcomes-accountable fashion. It was recognized that coordinated efforts across existing organizational structures will be required, informed by dataset integration strategies that meaningfully measure educational and related patient outcomes.

View details for DOI 10.1097/SLA.0000000000006434

View details for PubMedID 38946537
Opportunities and Applications of Educational Technologies in Surgical Education and Assessment. Annals of surgery Fried, G. M., Varas, J., Telem, D. A., Greenberg, C. C., Hashimoto, D. A., Paige, J. T., Pugh, C. 2024 More

Abstract

Surgical education is challenged by continuously increasing clinical content, greater subspecialization, and public scrutiny of access to high quality surgical care. Since the last Blue Ribbon Committee on surgical education, novel technologies have been developed including artificial intelligence and telecommunication.The goals of this Blue Ribbon Sub-Committee were to describe the latest technological advances and construct a framework for applying these technologies to improve the effectiveness and efficiency of surgical education and assessment. An additional goal was to identify implementation frameworks and strategies for centers with different resources and access. All sub-committee recommendations were included in a Delphi consensus process with the entire Blue Ribbon Committee (N=67).Our sub-committee found several new technologies and opportunities that are well poised to improve the effectiveness and efficiency of surgical education and assessment (see Tables 1-3). Our top recommendation was that a Multidisciplinary Surgical Educational Council be established to serve as an oversight body to develop consensus, facilitate implementation, and establish best practices for technology implementation and assessment. This recommendation achieved 93% consensus during the first round of the Delphi process.Advances in technology-based assessment, data analytics, and behavioral analysis now allow us to create personalized educational programs based on individual preferences and learning styles. If implemented properly, education technology has the promise of improving the quality and efficiency of surgical education and decreasing the demands on clinical faculty.

View details for DOI 10.1097/SLA.0000000000006367

View details for PubMedID 38810267
Precision Education: The Future of Lifelong Learning in Medicine. Academic medicine : journal of the Association of American Medical Colleges Desai, S. V., Burk-Rafel, J., Lomis, K. D., Caverzagie, K., Richardson, J., O'Brien, C. L., Andrews, J., Heckman, K., Henderson, D., Prober, C. G., Pugh, C. M., Stern, S. D., Triola, M. M., Santen, S. A. 2024 More

Abstract

The goal of medical education is to produce a physician workforce capable of delivering high-quality equitable care to diverse patient populations and communities. To achieve this aim amidst explosive growth in medical knowledge and increasingly complex medical care, a system of personalized and continuous learning, assessment, and feedback for trainees and practicing physicians is urgently needed. In this perspective, the authors build on prior work to advance a conceptual framework for such a system: precision education (PE).PE is a system that uses data and technology to transform lifelong learning by improving personalization, efficiency, and agency at the individual, program, and organization levels. PE "cycles" start with data inputs proactively gathered from new and existing sources, including assessments, educational activities, electronic medical records, patient care outcomes, and clinical practice patterns. Through technology-enabled analytics, insights are generated to drive precision interventions. At the individual level, such interventions include personalized just-in-time educational programming. Coaching is essential to provide feedback and increase learner participation and personalization. Outcomes are measured using assessment and evaluation of interventions at the individual, program, and organizational level, with ongoing adjustment for repeated cycles of improvement. PE is rooted in patient, health system, and population data; promotes value-based care and health equity; and generates an adaptive learning culture.The authors suggest fundamental principles for PE, including promoting equity in structures and processes, learner agency, and integration with workflow (harmonization). Finally, the authors explore the immediate need to develop consensus-driven standards: rules of engagement between people, products, and entities that interact in these systems to ensure interoperability, data sharing, replicability, and scale of PE innovations.

View details for DOI 10.1097/ACM.0000000000005601

View details for PubMedID 38277444
Sensor-Based Discovery of Search and Palpation Modes in the Clinical Breast Examination. Academic medicine : journal of the Association of American Medical Colleges Laufer, S., Klatzky, R. L., Pugh, C. M. 2024 More

Abstract

Successful implementation of precision education systems requires widespread adoption and seamless integration of new technologies with unique data streams that facilitate real-time performance feedback. This paper explores the use of sensor technology to quantify hands-on clinical skills. The goal is to shorten the learning curve through objective and actionable feedback.A sensor-enabled clinical breast examination (CBE) simulator was used to capture force and video data from practicing clinicians (N = 152). Force-by-time markers from the sensor data and a machine learning algorithm were used to parse physicians' CBE performance into periods of search and palpation and then these were used to investigate distinguishing characteristics of successful vs unsuccessful attempts to identify masses in CBEs.Mastery performance from successful physicians showed stable levels of speed and force across the entire CBE and a 15% increase in force when in palpation mode compared to search mode. Unsuccessful physicians failed to search with sufficient force to detect deep masses F(5,146) = 4.24, P = .001. While similar proportions of male and female physicians reached the highest performance level, males used more force as noted by higher palpation to search force ratios t(63) = 2.52, P = .014.Sensor technology can serve as a useful pathway to assess hands-on clinical skills and provide data-driven feedback. When using a sensor-enabled simulator, the authors found specific haptic approaches that were associated with successful CBE outcomes. Given this study's findings, continued exploration of sensor technology in support of precision education for hands-on clinical skills is warranted.

View details for DOI 10.1097/ACM.0000000000005614

View details for PubMedID 38207081

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BFAM Member Spotlights

Carla Pugh, MD, PhD

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