Dr. Amit Singh is a Clinical Associate Professor of Pediatrics in the Division of Pediatric Hospital Medicine within the Department of Pediatrics at the Stanford University School of Medicine. He completed his medical education at the Baylor College of Medicine in Houston, TX and completed his internship and residency in pediatrics at the former Children's Hospital and Research Center Oakland (now UCSF Benioff Children's Hospital Oakland) in Oakland, CA. He then completed a two-year fellowship in Pediatric Hospital Medicine with IT focus at the University of California San Diego and Rady Children's Hospital San Diego in San Diego, CA. There he developed and implemented the use of a novel electronic communication tool aimed at improving medical care team identification for inpatients hospitalized on the pediatric hospital medicine service. He joined Stanford in the Fall of 2013 and his main non-clinical work is focused in patient communication and inpatient health information technology.
He has previously served as the Physician Lead for the Office of Patient Experience at Lucile Packard Children's Hospital Stanford from 2015-2017. His current quality improvement efforts are focused on improving the overall medical rounding experience for both patients and providers on the inpatient Pediatric Hospital Medicine service with scheduled-based family-centered rounds. He additionally is the Clinical Informatics Medical Director for the hospital-wide communications technology platform (Voalte) at LPCH. He is also involved with a collaborative project with the Stanford Computer Vision department in utilizing artificial intelligence and machine learning to monitor and improve hand hygiene in the hospital. Dr. Singh is also a facilitator for the Advancing Communication Excellence at Stanford (ACES) communication workshops/trainings provided to faculty working at LPCH.
Dr. Singh is a native Texan now residing in San Francisco, CA with his wife and two sons.
- Pediatric Hospital Medicine
- Relationship-Centered Communication
- Clinical Informatics/Healthcare Information Technology
- Pediatric Hospital Medicine Fellowship
Clinical Associate Professor, Pediatrics
Facilitator/Instructor at Lucile Packard Children's Hospital Stanford (LPCH), Advancing Communication Excellence at Stanford (ACES) (2019 - Present)
Clinical Partner - LPCH site leader, Stanford Partnership in AI-Assisted Care (PAC) (2014 - Present)
Medical Director of Clinical Informatics - Voalte communications platform, Stanford Children's Health (2016 - Present)
Physicial Lead for Packard Vision Optimization, Lucile Packard Children's Hospital (2015 - 2017)
Physician Hand Hygiene Champion, Lucile Packard Children's Hospital (2013 - 2016)
Physicial Lead for the Office of Patient Experience, Lucile Packard Children's Hospital (2015 - 2017)
Boards, Advisory Committees, Professional Organizations
Member, American Academy of Pediatrics (2008 - Present)
Member, Society of Hospital Medicine (2011 - Present)
Medical Education: Baylor College of Medicine Registrar (2008) TX
Fellowship: The Univ of San Diego School of Medicine (2013) CA
Certification, Epic Systems Corporation, Inpatient Electronic Medical Record Procedure Orders certification versions 2010, 2012 (2012)
Board Certification: American Board of Pediatrics, Pediatrics (2011)
Residency: Children's Hospital at Oakland (2011) CA
Current Research and Scholarly Interests
My current quality improvement efforts are focused on improving the overall medical rounding experience for both patients and providers on the inpatient Pediatric Hospital Medicine service with a novel pilot of scheduled based rounds. With this project we have adapted a novel tool within the EMR for automatically scheduling patients for a "slot" or time for rounds for the medical team. This QI project was selected as one of the first Value-Based Care initiative projects sponsored by the executive team at Lucile Packard Children's Hospital.
I additionally serve as the Clinical Informatics Medical Director for the hospital-wide communications technology platform (Voalte) at LPCH. With this we have been interested in exploring team communication surrounding safety events such as Rapid Response or Code Blue calls. This research is in its preliminary phases.
Finally, I have been involved in a novel project as part of a collaboration between the School of Medicine and the Stanford Computer Vision lab on the cutting edge use of artificial intelligence and machine learning to monitor and improve hand hygiene in the hospital. More information about this can be found on the PAC website: https://aicare.stanford.edu/projects/hand_hygiene/
Automatic detection of hand hygiene using computer vision technology.
Journal of the American Medical Informatics Association : JAMIA
Hand hygiene is essential for preventing hospital-acquired infections but is difficult to accurately track. The gold-standard (human auditors) is insufficient for assessing true overall compliance. Computer vision technology has the ability to perform more accurate appraisals. Our primary objective was to evaluate if a computer vision algorithm could accurately observe hand hygiene dispenser use in images captured by depth sensors.Sixteen depth sensors were installed on one hospital unit. Images were collected continuously from March to August 2017. Utilizing a convolutional neural network, a machine learning algorithm was trained to detect hand hygiene dispenser use in the images. The algorithm's accuracy was then compared with simultaneous in-person observations of hand hygiene dispenser usage. Concordance rate between human observation and algorithm's assessment was calculated. Ground truth was established by blinded annotation of the entire image set. Sensitivity and specificity were calculated for both human and machine-level observation.A concordance rate of 96.8% was observed between human and algorithm (kappa = 0.85). Concordance among the 3 independent auditors to establish ground truth was 95.4% (Fleiss's kappa = 0.87). Sensitivity and specificity of the machine learning algorithm were 92.1% and 98.3%, respectively. Human observations showed sensitivity and specificity of 85.2% and 99.4%, respectively.A computer vision algorithm was equivalent to human observation in detecting hand hygiene dispenser use. Computer vision monitoring has the potential to provide a more complete appraisal of hand hygiene activity in hospitals than the current gold-standard given its ability for continuous coverage of a unit in space and time.
View details for DOI 10.1093/jamia/ocaa115
View details for PubMedID 32712656
Current Practices and Perspectives on Peer Observation and Feedback: A National Survey.
OBJECTIVE: Peer observation and feedback (POF) is the direct observation of an activity performed by a colleague followed by feedback with the goal of improved performance and professional development. Although well described in the education literature, the use of POF as a tool for development beyond teaching skills has not been explored. We aimed to characterize the practice of POF among pediatric hospitalists, to explore the perceived benefits and barriers, and to identify preferences regarding POF.METHODS: We developed a 14-item cross-sectional survey regarding divisional expectations, personal practice, perceived benefits and barriers, and preferences related to POF. We refined the survey based on expert feedback, cognitive interviews, and pilot testing, distributing the final survey to pediatric hospitalists at twelve institutions across the United States.RESULTS: Of 357 eligible participants, 198 (56%) responded with 115 (58%) practicing in a freestanding children's hospital. While 61% had participated in POF, less than half (42%) reported divisional POF expectation. The most common perceived benefits of POF were identifying areas for improvement (94%) and learning about colleagues' teaching and clinical styles (94%). The greatest perceived barriers were time (51%) and discomfort with receiving feedback from peers (38%), although participation within a POF program reduced perceived barriers. Most (76%) desired formal POF programs focused on improving teaching skills (85%), clinical management (83%), and family-centered rounds (82%).CONCLUSION: Though the majority of faculty desired POF, developing a supportive environment and feasible program is challenging. This study provides considerations for improving and designing POF programs.
View details for PubMedID 30910598
- Secure Text Messaging in Healthcare: Latent Threats and Opportunities to Improve Patient Safety. Journal of hospital medicine 2019; 14: E1–E3
- Working to Make the Hospital Smarter. Hospital pediatrics 2017; 7 (2): 122–24
Who's My Doctor? Using an Electronic Tool to Improve Team Member Identification on an Inpatient Pediatrics Team.
2016; 6 (3): 157-165
Increase parent/caregiver ability to correctly identify the attending in charge and define terminology of treatment team members (TTMs). We hypothesized that correct TTM identification would increase with use of an electronic communication tool. Secondary aims included assessing subjects' satisfaction with and trust of TTM and interest in computer activities during hospitalization.Two similar groups of parents/legal guardians/primary caregivers of children admitted to the Pediatric Hospital Medicine teaching service with an unplanned first admission were surveyed before (Phase 1) and after (Phase 2) implementation of a novel electronic medical record (EMR)-based tool with names, photos, and definitions of TTMs. Physicians were also surveyed only during Phase 1. Surveys assessed TTM identification, satisfaction, trust, and computer use.More subjects in Phase 2 correctly identified attending physicians by name (71% vs. 28%, P < .001) and correctly defined terms intern, resident, and attending (P ≤ .03) compared with Phase 1. Almost all subjects (>79%) and TTMs (>87%) reported that subjects' ability to identify TTMs moderately or strongly impacted satisfaction and trust. The majority of subjects expressed interest in using computers to understand TTMs in each phase.Subjects' ability to correctly identify attending physicians and define TTMs was significantly greater for those who used our tool. In our study, subjects reported that TTM identification impacted aspects of the TTM relationship, yet few could correctly identify TTMs before tool use. This pilot study showed early success in engaging subjects with the EMR in the hospital and suggests that families would engage in computer-based activities in this setting.
View details for DOI 10.1542/hpeds.2015-0164
View details for PubMedID 26920366
Mom, I’m going to be an INPATIENT doctor…” (A Graduating PHM Fellow’s Musings on the Past, Present, and Future)
2013; 3: 2
View details for DOI 10.1542/hpeds.2013-0030
- Painful Arthritis and Extremity Rash in an 8-Year-Old Boy CLINICAL INFECTIOUS DISEASES 2012; 54 (10): 1473-?