Medical students' perception of their 'distance travelled' in medical school applications.

INTRODUCTION: Within medical school's holistic review of applicants includes a review of their distance travelled to get to this point in their education. The AAMC defines distance travelled (DT) as, 'any obstacles or hardships you've overcome to get to this point in your education or any life challenges you've faced and conquered'. What medical students consider as their distance travelled has not been explored. The authors sought to identify the factors medical students perceive are important for medical school admissions to consider when assessing someone's 'distance travelled' by asking current medical students to share their DT experiences along with the barriers and facilitators they encountered on their medical school journey. METHODS: The authors conducted semi-structured interviews with US medical students through purposeful sampling methods. The social-ecological model framework was used to develop questions to elicit participants' experiences that contributed to their distance travelled. Interviews were conducted in 2021 and ranged from 60-75 minutes. Transcribed interviews were qualitatively analysed using interpretive description. RESULTS: A total of 31 medical students from seven medical schools were included in the study. Overall, participants defined distance travelled as an applicant's hardships (e.g. being the primary caregiver for a family member) and privileges (e.g. having physician parents) they experienced. Three major themes were identified: (1) individual-level characteristics and factors, (2) interpersonal relationships and (3) aspects of the participants' community and society. DISCUSSION: Our findings show that medical school applicants considered DT to be a valuable component of a holistic medical school admission process. Participants' experiences of DT were varied and complex. Our research suggests that admissions teams for medical schools should incorporate more comprehensive recruitment practices and inclusive methodological frameworks to accurately capture the diversity of identities and experiences of medical school applicants and to consider the factors that shape their journey to medical schools.

The impact of frailty on ventral hernia repair outcomes in a statewide database.

INTRODUCTION: Preoperative frailty is a strong predictor of postoperative morbidity in the general surgery population. Despite this, there are a paucity of research examining the effect of frailty on outcomes after ventral hernia repair (VHR), one of the most common abdominal operations in the USA. We examined the association of frailty with short-term postoperative outcomes while accounting for differences in preoperative, operative, and hernia characteristics. METHODS: We retrospectively reviewed the Michigan Surgery Quality Collaborative Hernia Registry (MSQC-HR) for adult patients who underwent VHR between January 2020 and January 2022. Patient frailty was assessed using the validated 5-factor modified frailty index (mFI5) and categorized as follows: no (mFI5 = 0), moderate (mFI5 = 1), and severe frailty (mFI5 ≥ 2). Our primary outcome was any 30-day complication. Multivariable logistic regression was used to evaluate the association of frailty with outcomes while controlling for patient, operative, and hernia variables. RESULTS: A total of 4406 patients underwent VHR with a mean age (SD) of 55 (15) years, 2015 (46%) females, and 3591 (82%) white patients. The mean (SD) BMI of the cohort was 33 (8) kg/m2. A total of 2077 (47%) patients had no frailty, 1604 (36%) were moderately frail, and 725 (17%) were severely frail. The median hernia size (interquartile range) was 2.5 cm (1.5-4.0 cm). Severe frailty was associated with increased odds of any complication (adjusted Odds Ratio (aOR) 3.12, 95% CI 1.78-5.47), serious complication (aOR 5.25, 95% CI 2.17-13.19), SSI (aOR 3.41, 95% CI 1.58-7.34), and post-discharge adverse events (aOR 1.70, 95% CI 1.24-2.33). CONCLUSION: After controlling for patient, operative, and hernia characteristics, frailty was independently associated with increased odds of postoperative complications. These findings highlight the importance of preoperative frailty assessment for risk stratification and to inform patient counseling.

Application of Component Separation and Short-Term Outcomes in Ventral Hernia Repairs.

INTRODUCTION: Component separation (CS) techniques have evolved in recent years. How surgeons apply the various CS techniques, anterior component separation (aCS) versus posterior component separation (pCS), by patient and hernia-specific factors remain unknown in the general population. Improving the quality of ventral hernia repair (VHR) on a large scale requires an understanding of current practice variations and how these variations ultimately affect patient care. In this study, we examine the application of CS techniques and the associated short-term outcomes while taking into consideration patient and hernia-specific factors. METHODS: We retrospectively reviewed a clinically rich statewide hernia registry, the Michigan Surgical Quality Collaborative Hernia Registry, of persons older than 18 y who underwent VHR between January 2020 and July 2021. The exposure of interest was the use of CS. Our primary outcome was a composite end point of 30-d adverse events including any complication, emergency department visit, readmission, and reoperation. Our secondary outcome was surgical site infection (SSI). Multivariable logistic regression examined the association of CS use, 30-d adverse events, and SSI with patient-, hernia-, and operative-specific variables. We performed a sensitivity analysis evaluating for differences in application and outcomes of the posterior and aCS techniques. RESULTS: A total of 1319 patients underwent VHR, with a median age (interquartile range) of 55 y (22), 641 (49%) female patients, and a median body mass index of 32 (9) kg/m2. CS was used in 138 (11%) patients, of which 101 (73%) were pCS and 37 (27%) were aCS. Compared to patients without CS, patients undergoing a CS had larger median hernia widths (2.5 cm (range 0.01-23 cm) versus 8 cm (1-30 cm), P < 0.001). Of the CS cases, 49 (36%) performed in hernias less than 6 cm in size. Following multivariate regression, factors independently associated with the use of a CS were diabetes (odds ratio [OR]: 2.00, 95% confidence interval [CI]: 1.19-3.36), previous hernia repair (OR: 1.88, 95% CI: 1.20-2.96), hernia width (OR: 1.28, 95% CI: 1.22-1.34), and an open approach (OR: 3.83, 95% CI: 2.24-6.53). Compared to patients not having a CS, use of a CS was associated with increased odds of 30-d adverse events (OR: 1.88 95% CI: 1.13-3.12) but was not associated with SSI (OR: 1.95, 95% CI: 0.74-4.63). Regression analysis demonstrated no differences in 30-d adverse events or SSI between the pCS and aCS techniques. CONCLUSIONS: This is the first population-level report of patients undergoing VHR with concurrent posterior or aCS. These data suggest wide variation in the application of CS in VHR and raises a concern for potential overutilization in smaller hernias. Continued analysis of CS application and the associated outcomes, specifically recurrence, is necessary and underway.

Variation of ventral and incisional hernia repairs in kidney transplant recipients.

INTRODUCTION: As survivorship following kidney transplant continues to improve, so does the probability of intervening on common surgical conditions, such as ventral or incisional hernia, in this population. Ventral hernia management is known to vary across institutions and this variation has an impact on patient outcomes. We sought to evaluate hospital level variation of ventral or incisional hernia repair (VIHR) in the kidney transplant population. METHODS: We performed a retrospective review of 100% inpatient Medicare claims to identify patients who underwent kidney transplant between 2007 and 2018. The primary outcome was 1- and 3-year ventral or incisional risk- and reliability-adjusted VIHR rates. Patient and hospital characteristics were evaluated across risk- and reliability-adjusted VIHR rate tertiles. Models were adjusted for age, sex, race, and Elixhauser comorbidities. RESULTS: Overall, 139,741 patients underwent kidney transplant during the study period with a mean age (SD) of 51.6 (13.7) years. 84,717 (60.6%) were male, and 72,657 (52.0%) were white. Median follow up time was 5.4 years. 2098 (1.50%) patients underwent VIHR. the 1 year risk- and reliability-adjusted hernia repair rates were 0.49% (95% Conf idence Interval (CI) 0.48-0.51, range 0.31-0.59) in tertile 1, 0.63% (95% CI 0.62-0.63, range 0.59-0.68) in tertile 2, and 0.98 (95% CI 0.91-1.05, range 0.68-2.94) in tertile 3. Accordingly, compared to hospitals in tertile 1, the odds of post-transplant hernia repair tertile 2 hospitals were 1.78 (95% CI 1.37-2.31) and at tertile 3 hospitals 3.53 (95% CI 2.87-4.33). CONCLUSIONS: In a large cohort of Medicare patients undergoing kidney transplant, the overall cumulative incidence of hernia repair varied substantially across hospital tertiles. Patient and hospital characteristics varied across tertile, most notably in diabetes and obesity. Future research is needed to understand if program and surgeon level factors are contributing to the observed variation in treatment of this common disease.

The Inequitable Experiences of Left-Handed Medical Students in Surgical Education.

PURPOSE: Left-handed medical students contend with unique educational barriers within surgery, such as lack of educational resources, lack of left-handed-specific training, and widespread stigmatization of surgical left-handedness. This study aimed to highlight the surgical experiences of left-handed medical students so educators may be empowered to act with greater care and appreciation of these students' circumstances. METHOD: In this qualitative study, the authors conducted semistructured interviews on surgical experiences during medical school between January 31, 2021, and June 20, 2021, on 31 current surgical residents and fellows from 15 U.S. institutions and 6 surgical specialties. Left-handed trainees were included regardless of their surgical hand dominance. RESULTS: The authors identified 3 themes related to left-handed medical students' surgical experience: (1) disorienting advice from faculty or residents, (2) discouraging right-handed pressures and left-handed stigmatization, and (3) educational wishes of left-handed medical students. Trainees describe dialogues during medical school in which their handedness was directly addressed by residents and faculty with disorienting and nonbeneficial advice. Often trainees were explicitly told which hand to use, neglecting any preferences of the left-handed student. Participants also described possible changes in future surgical clerkships, including normalization of left-handedness, tangible mentorship, or granular and meaningful instruction. CONCLUSIONS: Left-handed medical students encounter unique challenges during their surgical education. These students report being disoriented by the variability of advice provided by mentors, discouraged by how pressured they feel to operate right-handed, and burdened by the need to figure things out by themselves in the absence of adequate left-handed educational resources. Surgical education leadership should detail the unique problems left-handed learners face, impartially elicit the learner's current operative hand preference, take responsibility for their left-handed students, promote acceptance and accommodation strategies of left-handed surgical trainees, and endeavor to improve the breadth of left-handed surgical resources.

Natural Language Processing and Assessment of Resident Feedback Quality.

OBJECTIVE: To validate the performance of a natural language processing (NLP) model in characterizing the quality of feedback provided to surgical trainees. DESIGN: Narrative surgical resident feedback transcripts were collected from a large academic institution and classified for quality by trained coders. 75% of classified transcripts were used to train a logistic regression NLP model and 25% were used for testing the model. The NLP model was trained by uploading classified transcripts and tested using unclassified transcripts. The model then classified those transcripts into dichotomized high- and low- quality ratings. Model performance was primarily assessed in terms of accuracy and secondary performance measures including sensitivity, specificity, and area under the receiver operating characteristic curve (AUROC). SETTING: A surgical residency program based in a large academic medical center. PARTICIPANTS: All surgical residents who received feedback via the Society for Improving Medical Professional Learning smartphone application (SIMPL, Boston, MA) in August 2019. RESULTS: The model classified the quality (high vs. low) of 2,416 narrative feedback transcripts with an accuracy of 0.83 (95% confidence interval: 0.80, 0.86), sensitivity of 0.37 (0.33, 0.45), specificity of 0.97 (0.96, 0.98), and an area under the receiver operating characteristic curve of 0.86 (0.83, 0.87). CONCLUSIONS: The NLP model classified the quality of operative performance feedback with high accuracy and specificity. NLP offers residency programs the opportunity to efficiently measure feedback quality. This information can be used for feedback improvement efforts and ultimately, the education of surgical trainees.

The incidence and outcome of postoperative hepatic encephalopathy in patients with cirrhosis.

BACKGROUND: Cirrhosis is associated with increased perioperative risks related to hepatic decompensation. However, data are lacking regarding the incidence and outcomes of postoperative hepatic encephalopathy (HE). OBJECTIVE: To determine the incidence of HE postoperatively, factors associated with its development, and its association with in-hospital mortality. METHODS: Retrospective cohort study of 583 patients with cirrhosis undergoing non-hepatic surgery over a 10-year period. Outcomes included postoperative HE and in-hospital mortality and were, respectively, evaluated using multi-state modeling and Fine-Gray competing risk regression (with postoperative HE as a time-varying covariate). RESULTS: Overall, the median Model for End-Stage Liver Disease Sodium was 10, 61.7% had a history of ascites, 49.9% esophageal varices, and 34.6% HE. The most common surgeries including abdominal/non-bowel (33.3%), orthopedic (18.0%), and bowel (12.2%). A total of 42 (7.2%) patients developed HE postoperatively during admission. The cumulative risk of HE was 7.2%, which was most associated with a history of HE, ASA class, postoperative AKI, and postoperative infection. In-hospital mortality occurred in 34 (5.8%) individuals. Only ASA class was independently associated (HR 2.46, 95%CI 1.21-5.02), but there was a trend for postoperative HE (HR 1.71, 95%CI 0.73-3.98). DISCUSSION: HE is an uncommon but not rare postoperative complication that increases the risk of patient harm. This study implies its development is predictable. Consequently, at-risk patients should have consultation with a hepatologist before undergoing elective surgery.

Using Natural Language Processing to Automatically Assess Feedback Quality: Findings From 3 Surgical Residencies.

PURPOSE: Learning is markedly improved with high-quality feedback, yet assuring the quality of feedback is difficult to achieve at scale. Natural language processing (NLP) algorithms may be useful in this context as they can automatically classify large volumes of narrative data. However, it is unknown if NLP models can accurately evaluate surgical trainee feedback. This study evaluated which NLP techniques best classify the quality of surgical trainee formative feedback recorded as part of a workplace assessment. METHOD: During the 2016-2017 academic year, the SIMPL (Society for Improving Medical Professional Learning) app was used to record operative performance narrative feedback for residents at 3 university-based general surgery residency training programs. Feedback comments were collected for a sample of residents representing all 5 postgraduate year levels and coded for quality. In May 2019, the coded comments were then used to train NLP models to automatically classify the quality of feedback across 4 categories (effective, mediocre, ineffective, or other). Models included support vector machines (SVM), logistic regression, gradient boosted trees, naive Bayes, and random forests. The primary outcome was mean classification accuracy. RESULTS: The authors manually coded the quality of 600 recorded feedback comments. Those data were used to train NLP models to automatically classify the quality of feedback across 4 categories. The NLP model using an SVM algorithm yielded a maximum mean accuracy of 0.64 (standard deviation, 0.01). When the classification task was modified to distinguish only high-quality vs low-quality feedback, maximum mean accuracy was 0.83, again with SVM. CONCLUSIONS: To the authors' knowledge, this is the first study to examine the use of NLP for classifying feedback quality. SVM NLP models demonstrated the ability to automatically classify the quality of surgical trainee evaluations. Larger training datasets would likely further increase accuracy.