Dr. Hindin obtained his MD from the University of Pennsylvania Perelman School of Medicine in Philadelphia, Pennsylvania. He completed his general surgery training at Temple University School of Medicine, also in Philadelphia, and subsequently completed fellowship in surgical critical care at Stanford University School of Medicine. Dr. Hindin is currently a Clinical Assistant Professor of Surgery at Stanford University in the section of Trauma and Critical Care Surgery and at the VA Palo Alto. Dr. Hindin also serves as Assistant Director of Stanford University’s Biodesign Faculty Fellowship, a university-wide program that trains faculty members from medicine, engineering, and other schools in the process of creating health technology innovation, from needs-finding to commercialization.
Dr. Hindin has a particular interest in training physicians to leverage story-based skills to increase the effectiveness of their communication. He has previously developed and taught a semester-long storytelling course at Stanford Biodesign, which trains physicians and engineers to create more effective pitches when seeking venture funding.
- General Surgery
Clinical Assistant Professor, Surgery - General Surgery
Residency: Temple University Hospital Dept of Surgery (2019) PA
Fellowship: Stanford University Surgical Critical Care Fellowship (2022) CA
Board Certification: American Board of Surgery, General Surgery (2020)
Internship: Hospital of the University of Pennsylvania General Surgery Residency (2012) PA
Medical Education: Perelman School of Medicine University of Pennsylvania (2011) PA
A National Study on Training Innovation in US Medical Education.
2023; 15 (10): e46433
Introduction Traditional medical education has leaned heavily on memorization, pattern recognition, and learned algorithmic thinking. Increasingly, however, creativity and innovation are becoming recognized as a valuable component of medical education. In this national survey of Association of American Medical Colleges (AAMC) member institutions, we seek to examine the current landscape of exposure to innovation-related training within the formal academic setting. Methods Surveys were distributed to 168 of 171 AAMC-member institutions (the remaining three were excluded from the study for lack of publicly available contact information). Questions assessed exposure for medical students among four defined innovation pillars as follows: (1) medical humanities, (2) design thinking, (3) entrepreneurship, or (4) technology transfer. Chi-squared analysis was used to assess statistical significance between schools, comparing schools ranked in the top 20 by the USNews and World Report against non-top 20 respondents, and comparing schools that serve as National Institutes of Health (NIH) Clinical and Translational Science Awards (CTSA) program hubs against non-CTSA schools. Heat maps for geospatial visualization of data were created using ArcGIS (ArcMAP 10.6) software (Redlands, CA: Environmental Systems Research Institute). Results The overall response rate was 94.2% with 161 schools responding. Among respondents, 101 (63%) reported having medical humanities curricula at their institution. Design thinking offerings were noted at 51/161 (32%) institutions. Support for entrepreneurship was observed at 51/161 institutions (32%), and technology transfer infrastructure was confirmed at 42/161 (26%) of institutions. No statistically significant difference was found between top 20 schools and lower 141 schools when comparing schools with no innovation programs or one or more innovation programs (p=0.592), or all four innovation programs (p=0.108). CTSA programs, however, did show a statistically significant difference (p<0.00001) when comparing schools with no innovation programs vs. one or more programs, but not when comparing to schools with all four innovation programs (p=0.639). Conclusion This study demonstrated an overwhelming prevalence of innovation programs in today's AAMC medical schools, with over 75% of surveyed institutions offering at least one innovation program. No statistically significant trend was seen in the presence of zero programs, one or more, or all four programs between top 20 programs and the remaining 141. CTSA hub schools, however, were significantly more likely to have at least one program vs. none compared to non-CTSA hub schools. Future studies would be valuable to assess the long-term impact of this trend on medical student education.
View details for DOI 10.7759/cureus.46433
View details for PubMedID 37927762
- Rib fracture fixation in a patient on veno-venous extracorporeal membrane oxygenation following a motor vehicle collision. Trauma surgery & acute care open 2022; 7 (1): e001004
Surgical Infection Society: Chest Wall Injury Society Recommendations for Antibiotic Use during Surgical Stabilization of Traumatic Rib or Sternal Fractures to Reduce Risk of Implant Infection.
2022; 23 (4): 321-331
Background: Surgical stabilization of rib fractures is recommended in patients with flail chest or multiple displaced rib fractures with physiologic compromise. Surgical stabilization of rib fractures (SSRF) and surgical stabilization of sternal fractures (SSSF) involve open reduction and internal fixation of fractures with a plate construct to restore anatomic alignment. Most plate constructs are composed of titanium and presence of this foreign, non-absorbable material presents opportunity for implant infection. Although implant infection rates after SSRF and SSSF are low, they present a challenging clinical entity often requiring prolonged antibiotic therapy, debridement, and potentially implant removal. Methods: The Surgical Infection Society's Therapeutics and Guidelines Committee and Chest Wall Injury Society's Publication Committee convened to develop recommendations for antibiotic use during and after surgical stabilization of traumatic rib and sternal fractures. Clinical scenarios included patients with concomitant infectious processes (sepsis, pneumonia, empyema, cellulitis) or sources of contamination (open chest, gross contamination) incurred as a result of their trauma and present at the time of their surgical stabilization. PubMed, Embase, and Cochrane databases were searched for pertinent studies. Using a process of iterative consensus, all committee members voted to accept or reject each recommendation. Results: For patients undergoing SSRF or SSSF in the absence of pre-existing infectious process, there is insufficient evidence to suggest existing peri-operative guidelines or recommendations are inadequate. For patients undergoing SSRF or SSSF in the presence of sepsis, pneumonia, or an empyema, there is insufficient evidence to provide recommendations on duration and choice of antibiotic. This decision may be informed by existing guidelines for the concomitant infection. For patients undergoing SSRF or SSSF with an open or contaminated chest there is insufficient evidence to provide specific antibiotic recommendations. Conclusions: This guideline document summarizes the current Surgical Infection Society and Chest Wall Injury Society recommendations regarding antibiotic use during and after surgical stabilization of traumatic rib or sternal fractures. Limited evidence exists in the chest wall surgical stabilization literature and further studies should be performed to delineate risk of implant infection among patients undergoing SSSRF or SSSF with concomitant infectious processes.
View details for DOI 10.1089/sur.2022.025
View details for PubMedID 35522129
Scalable Deep Learning Algorithm to Compute Percent Pulmonary Contusion among Patients with Rib Fractures.
The journal of trauma and acute care surgery
Pulmonary contusion exists along a spectrum of severity, yet is commonly binarily classified as present or absent. We aimed to develop a deep learning algorithm to automate percent pulmonary contusion computation and exemplify how transfer learning could facilitate large-scale validation. We hypothesized our deep learning algorithm could automate percent pulmonary contusion computation and that greater percent contusion would be associated with higher odds of adverse inpatient outcomes among patients with rib fractures.We evaluated admission-day chest computed tomography (CT) scans of adults aged ≥18 years admitted to our institution with multiple rib fractures and pulmonary contusions (2010-2020). We adapted a pre-trained convolutional neural network that segments 3-dimensional lung volumes and segmented contused lung parenchyma, pulmonary blood vessels, and computed percent pulmonary contusion. Exploratory analysis evaluated associations between percent pulmonary contusion (quartiles) and odds of mechanical ventilation, mortality, and prolonged hospital length-of-stay using multivariable logistic regression. Sensitivity analysis included pulmonary blood vessel volumes during percent contusion computation.A total of 332 patients met inclusion criteria (median 5 rib fractures), among whom 28% underwent mechanical ventilation and 6% died. The study population's median (IQR) percent pulmonary contusion was 4(2-8)%. Compared to the lowest quartile of percent pulmonary contusion, each increasing quartile was associated with higher adjusted odds of undergoing mechanical ventilation (OR[95%CI]: 1.5[1.1-2.1]) and prolonged hospitalization (OR[95%CI]: 1.6[1.1-2.2]), but not with mortality (OR[95%CI]: 1.1 [0.6-2.0]. Findings were similar on sensitivity analysis.We developed a scalable deep learning algorithm to automate percent pulmonary contusion calculating using chest CTs of adults admitted with rib fractures. Open code sharing and collaborative research is needed to validate our algorithm and exploratory analysis at large scale. Transfer learning can help harness the full potential of big data and high-performing algorithms to bring precision medicine to the bedside.IV.
View details for DOI 10.1097/TA.0000000000003619
View details for PubMedID 35319542