Precision Education: The Future of Lifelong Learning in Medicine

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 levels, 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.

Haptics: The Science of Touch As a Foundational Pathway to Precision Education and Assessment

ABSTRACT

Clinical touch is the cornerstone of the doctor-patient relationship and can impact patient experience and outcomes. In the current era, driven by an ever-increasing infusion of point-of-care technologies, physical exam skills have become undervalued. Moreover, touch and hands-on skills have been difficult to teach due to inaccurate assessments and difficulty with learning transfer through observation. In this article, the authors argue that haptics, the science of touch, provides a unique opportunity to explore new pathways to facilitate touch training. Furthermore, haptics can dramatically increase the density of touch-based assessments without increasing human rater burden-essential for realizing precision assessment. The science of haptics is reviewed, including the benefits of using haptics-informed language for objective structured clinical examinations. The authors describe how haptic devices and haptic language have and can be used to facilitate learning, communication, documentation and a much-needed reinvigoration of physical examination, and touch excellence at the point of care. The synergy of haptic devices, artificial intelligence, and virtual reality environments are discussed. The authors conclude with challenges of scaling haptic technology in medical education, such as cost and translational needs, and opportunities to achieve wider adoption of this transformative approach to precision education.

Sensor-Based Discovery of Search and Palpation Modes in the Clinical Breast Examination

PURPOSE

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.

METHOD

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 versus unsuccessful attempts to identify masses in CBEs.

RESULTS

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 with 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).

CONCLUSIONS

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.

Surgical Education

This paper summarizes the proceedings of the joint European Surgical Association ESA/American Surgical Association symposium on Surgical Education that took place in Bordeaux, France, as part of the celebrations for 30 years of ESA scientific meetings. Three presentations on the use of quantitative metrics to understand technical decisions, coaching during training and beyond, and entrustable professional activities were presented by American Surgical Association members and discussed by ESA members in a symposium attended by members of both associations.

The Quantified Surgeon: A Glimpse Into the Future of Surgical Metrics and Outcomes

This paper summarizes key points of the 2023 Southeastern Surgical Congress Laws Lecture. The focus of the presentation was on the use of advanced engineering technology to quantify surgical mastery. New concepts relating to the visual-haptic loop, mastery and perception, and mastery and technical decisions were introduced and shown in an empirical fashion to have relevance in procedural outcomes in a simulated setting. The major takeaway point is that surgical mastery can be quantified using advanced engineering technology, and this process will help to shorten the learning curve.

Society of Black Academic Surgeons (SBAS) diversity, equity, and inclusion series: Microaggressions - Lessons Learned from Black Academic Surgeons

Background:

Microaggressions can target individuals based on a variety of differences and these can include sexual orientation, nationality, gender, or personal traits and are often disruptors in the healthcare setting.

Methods:

To address this issue, The Society of Black Academic Surgeons (SBAS) convened a series of presentations and a panel discussion by leaders from SBAS regarding the issue of microaggressions in the surgical workplace. This program was part of a monthly diversity, equity, and inclusion series produced by the Advances in Surgery Channel in alliance with the American College of Surgeons. Dr. Yewande Alimi addresses microaggressions in surgical training, Dr. Fabian Johnston talks about microaggressions in the black male physician, Dr. Lola Fayanju speaks to microaggressions and the black female surgeon, Dr. Carla Pugh discusses microaggressions in the surgical workplace, and Dr. Paris Butler presents on allyship, policies, and real solutions.

Results:

Specifically, through the lens of the Black surgeon experience, SBAS leaders candidly articulate and elaborate on microaggressions’ pervasiveness and the deleterious impact on the profession. Authentic opinions are rendered and constructive techniques to mitigate this challenge are provided. The concept of majority allyship is also introduced, and recommendations on how this can be operationalized is also examined.

Conclusions:

There are a lot of experiences that contribute to our understanding of microaggressions. We look forward to finding new ways to partner with our allies and continuing the conversation.

Do Individual Surgeon Preferences Affect Procedural Outcomes?

OBJECTIVES

Surgeon preferences such as instrument and suture selection and idiosyncratic approaches to individual procedure steps have been largely viewed as minor differences in the surgical workflow. We hypothesized that idiosyncratic approaches could be quantified and shown to have measurable effects on procedural outcomes.

METHODS

At the American College of Surgeons (ACS) Clinical Congress, experienced surgeons volunteered to wear motion tracking sensors and be videotaped while evaluating a loop of porcine intestines to identify and repair 2 preconfigured, standardized enterotomies. Video annotation was used to identify individual surgeon preferences and motion data was used to quantify surgical actions. χ 2 analysis was used to determine whether surgical preferences were associated with procedure outcomes (bowel leak).

RESULTS

Surgeons' (N=255) preferences were categorized into 4 technical decisions. Three out of the 4 technical decisions (repaired injuries together, double-layer closure, corner-stitches vs no corner-stitches) played a significant role in outcomes, P <0.05. Running versus interrupted did not affect outcomes. Motion analysis revealed significant differences in average operative times (leak: 6.67 min vs no leak: 8.88 min, P =0.0004) and work effort (leak-path length=36.86 cm vs no leak-path length=49.99 cm, P =0.001). Surgeons who took the riskiest path but did not leak had better bimanual dexterity (leak=0.21/1.0 vs no leak=0.33/1.0, P =0.047) and placed more sutures during the repair (leak=4.69 sutures vs no leak=6.09 sutures, P =0.03).

CONCLUSIONS

Our results show that individual preferences affect technical decisions and play a significant role in procedural outcomes. Future analysis in more complex procedures may make major contributions to our understanding of contributors to procedure outcomes.

Open surgery tool classification and hand utilization using a multi-camera system

PURPOSE

The goal of this work is to use multi-camera video to classify open surgery tools as well as identify which tool is held in each hand. Multi-camera systems help prevent occlusions in open surgery video data. Furthermore, combining multiple views such as a top-view camera covering the full operative field and a close-up camera focusing on hand motion and anatomy may provide a more comprehensive view of the surgical workflow. However, multi-camera data fusion poses a new challenge: A tool may be visible in one camera and not the other. Thus, we defined the global ground truth as the tools being used regardless their visibility. Therefore, tools that are out of the image should be remembered for extensive periods of time while the system responds quickly to changes visible in the video.

METHODS

Participants (n = 48) performed a simulated open bowel repair. A top-view and a close-up cameras were used. YOLOv5 was used for tool and hand detection. A high-frequency LSTM with a 1-second window at 30 frames per second (fps) and a low-frequency LSTM with a 40-second window at 3 fps were used for spatial, temporal, and multi-camera integration.

RESULTS

The accuracy and F1 of the six systems were: top-view (0.88/0.88), close-up (0.81,0.83), both cameras (0.9/0.9), high-fps LSTM (0.92/0.93), low-fps LSTM (0.9/0.91), and our final architecture the multi-camera classifier(0.93/0.94).

CONCLUSION

Since each camera in a multi-camera system may have a partial view of the procedure, we defined a 'global ground truth.' Defining this at the data labeling phase emphasized this requirement at the learning phase, eliminating the need for any heuristic decisions. By combining a system with a high fps and a low fps from the multiple camera array, we improved the classification abilities of the global ground truth.

Using open surgery simulation kinematic data for tool and gesture recognition

PURPOSE

The use of motion sensors is emerging as a means for measuring surgical performance. Motion sensors are typically used for calculating performance metrics and assessing skill. The aim of this study was to identify surgical gestures and tools used during an open surgery suturing simulation based on motion sensor data.

METHODS

Twenty-five participants performed a suturing task on a variable tissue simulator. Electromagnetic motion sensors were used to measure their performance. The current study compares GRU and LSTM networks, which are known to perform well on other kinematic datasets, as well as MS-TCN++, which was developed for video data and was adapted in this work for motion sensors data. Finally, we extended all architectures for multi-tasking.

RESULTS

In the gesture recognition task the MS-TCN++ has the highest performance with accuracy of [Formula: see text] and F1-Macro of [Formula: see text], edit distance of [Formula: see text] and F1@10 of [Formula: see text] In the tool usage recognition task for the right hand, MS-TCN++ performs the best in most metrics with an accuracy score of [Formula: see text], F1-Macro of [Formula: see text], F1@10 of [Formula: see text], and F1@25 of [Formula: see text]. The multi-task GRU performs best in all metrics in the left-hand case, with an accuracy of [Formula: see text], edit distance of [Formula: see text], F1-Macro of [Formula: see text], F1@10 of [Formula: see text], and F1@25 of [Formula: see text].

CONCLUSION

In this study, using motion sensor data, we automatically identified the surgical gestures and the tools used during an open surgery suturing simulation. Our methods may be used for computing more detailed performance metrics and assisting in automatic workflow analysis. MS-TCN++ performed better in gesture recognition as well as right-hand tool recognition, while the multi-task GRU provided better results in the left-hand case. It should be noted that our multi-task GRU network is significantly smaller and has achieved competitive results in the rest of the tasks as well.

Developing a longitudinal database of surgical skills performance for practicing surgeons: A formal feasibility and acceptance inquiry

BACKGROUND

We explored the feasibility and surgeons' perceptions of the utility of a longitudinal skills performance database.

METHODS

A 10-station surgical skills assessment center was established at a national scientific meeting. Skills assessment volunteers (n = 189) completed a survey including opinions on practicing surgeons' skills evaluation, ethics, and interest in a longitudinal database. A subset (n = 23) participated in a survey-related interview.

RESULTS

Nearly all participants reported interest in a longitudinal database and most believed there is an ethical obligation for such assessments to protect the public. Several interviewees specified a critical role for both formal and informal evaluation is to first create a safe and supportive environment.

CONCLUSIONS

Participants support the construction of longitudinal skills databases that allow information sharing and establishment of professional standards. In a constructive environment, structured peer feedback was deemed acceptable to enhance and diversify surgeon skills. Large scale skills testing is feasible and scientific meetings may be the ideal location.

SAGES consensus recommendations on an annotation framework for surgical video

BACKGROUND

The growing interest in analysis of surgical video through machine learning has led to increased research efforts; however, common methods of annotating video data are lacking. There is a need to establish recommendations on the annotation of surgical video data to enable assessment of algorithms and multi-institutional collaboration.

METHODS

Four working groups were formed from a pool of participants that included clinicians, engineers, and data scientists. The working groups were focused on four themes: (1) temporal models, (2) actions and tasks, (3) tissue characteristics and general anatomy, and (4) software and data structure. A modified Delphi process was utilized to create a consensus survey based on suggested recommendations from each of the working groups.

RESULTS

After three Delphi rounds, consensus was reached on recommendations for annotation within each of these domains. A hierarchy for annotation of temporal events in surgery was established.

CONCLUSIONS

While additional work remains to achieve accepted standards for video annotation in surgery, the consensus recommendations on a general framework for annotation presented here lay the foundation for standardization. This type of framework is critical to enabling diverse datasets, performance benchmarks, and collaboration.

Reassessing career pathways of surgical leaders: An examination of surgical leaders' early accomplishments

BACKGROUND

The American College of Surgeon (ACS), American Surgical Association (ASA), Association of Women Surgeons (AWS), and Society of Black Academic Surgeons (SBAS) partnered to gain insight into whether inequities found in surgical society presidents may be present earlier.

METHODS

ACS, ASA, AWS, and SBAS presidents' CVs were assessed for demographics and scholastic achievements at the time of first faculty appointment. Regression analyses controlling for age were performed to determine relative differences across societies.

RESULTS

66 of the 68 presidents' CVs were received and assessed (97% response rate). 50% of AWS future presidents were hired as Instructors rather than Assistant professors, compared to 29.4% of SBAS, 25% of ASA and 29.4% of ACS. The future ACS, ASA, and SBAS presidents had more total publications than the AWS presidents, but similar numbers of 1st and Sr. author publications.

CONCLUSION

Gender inequities in academic surgeon hiring practices and perceived scholastic success may be present at first hire.

How Wearable Technology Can Facilitate AI Analysis of Surgical Videos

Operative video has great potential to enable instant replays of critical surgical decisions for training and quality review. Recently, artificial intelligence (AI) has shown early promise as a method of enabling efficient video review, analysis, and segmentation. Despite the progress with AI analysis of surgical videos, more work needs to be done to improve the accuracy and efficiency of AI-driven video analysis. At a recent consensus conference held on July 10-11, 2020, 8 research teams shared their work using AI for surgical video analysis. Four of the teams showcased the utility of wearable technology in providing objective surgical metrics. Data from these technologies were shown to pinpoint important cognitive and motor actions during operative tasks and procedures. The results support the utility of wearable technology to facilitate efficient and accurate video analysis and segmentation.

The what? How? And Who? Of video based assessment

BACKGROUND

Currently, there is significant variability in the development, implementation and overarching goals of video review for assessment of surgical performance.

METHODS

This paper evaluates the current methods in which video review is used for evaluation of surgical performance and identifies which processes are critical for successful, widespread implementation of video-based assessment.

RESULTS

Despite the advances in video capture technology and growing interest in video-based assessment, there is a notable gap in the implementation and longitudinal use of formative and summative assessment using video.

CONCLUSION

Validity, scalability and discoverability are current but removable barriers to video-based assessment.

Does the location of short-arm cast univalve effect pressure of the three-point mould?

PURPOSE

Forearm and distal radius fractures are among the most common fractures in children. Many fractures are definitively treated with closed reduction and casting, however, the risk for re-displacement is high (7% to 39%). Proper cast application and the three-point moulding technique are modifiable factors that improve the ability of a cast to maintain the fracture reduction. Many providers univalve the cast to accommodate swelling. This study describes how the location of the univalve cut impacts the pressure at three-point mould sites for a typical dorsally displaced distal radius fracture.

METHODS

We placed nine force-sensing resistors on an arm model to collect pressure data at the three-point mould sites. Sensory inputs were sampled at 15 Hz. Cast padding and a three-point moulded short arm fibreglass cast was applied. The cast was then univalved on the dorsal, volar, radial or ulnar aspect. Pressure recordings were obtained throughout the procedure.

RESULTS

A total of 24 casts were analyzed. Casts univalved in the sagittal plane (dorsal or volar surface) retained up to 16% more pressure across the three moulding sites compared with casts univalved in the coronal plane (radial or ulnar border).

CONCLUSION

Maintaining pressure at the three-point mould prevents loss of reduction at the fracture site. This study shows that univalving the cast dorsally or volarly results in less pressure loss at moulding sites. This should improve the chances of maintaining fracture reductions when compared with radial or ulnar cuts in the cast. Sagittal plane univalving of forearm casts is recommended.

The Society of Black Academic Surgeons CV benchmarking initiative: Early career trends of academic surgical leaders

BACKGROUND

Surgeons from under-represented backgrounds are less likely to receive academic tenure and obtain leadership positions. Our objective was to query the curriculum vitaes (CVs) of SBAS leadership to develop a benchmarking tool to promote and guide careers in academic surgery.

METHODS

CVs from academic leaders were reviewed for academic productivity at early career stages-the first 5-and 10-years. Variables queried: peer-reviewed publications, grant funding, surgical societal involvement, invited lectureships and visiting professorships.

RESULTS

Of 20 CVs, 41 leadership positions including 13 SBAS Presidents were identified. At 5- and 10-years, respectively, the academic productivity increased: 20.6 and 52.3 publications; 4.7 and 9.7 grants; 18 and 42.6 lectures/professorships.

CONCLUSION

The CV benchmarking tool may be a useful framework for aspiring academic surgeons to track their progress relative to successful SBAS members. Creative strategies like these, paired with faculty mentorship and sponsorship are necessary to improve the ethnic diversity in academic surgery.