Bio


Vishnu Ravi is a physician, software engineer, and digital health architect focusing on creating innovative digital health solutions that support research and improve clinical care at Stanford Medicine. During his medical training, he did early work on clinical applications for conversational agents and extracting insights from unstructured health data. He has also co-founded a digital health startup, developed solutions for COVID-19 that were deployed internationally, and contributed to the first family of international mobile health data standards via the IEEE.

As the Lead Architect of the Building for Digital Health program at the Stanford Byers Center for Biodesign, Vishnu has led the development of the Stanford CardinalKit digital health framework and co-created its successor, Stanford Spezi. CardinalKit and Spezi have been used to create over 20 digital health clinical and research applications at Stanford and other leading healthcare and research institutions. Vishnu has also been an instructor for CS342/MED253, a real-world digital health app development course for Stanford computer science undergraduates and graduate students, since 2021.

Vishnu is currently the Technology Architect for Catalyst, Stanford Medicine’s flagship innovation program to support inventors across the Stanford community in developing and accelerating their most promising innovations for transformative health, which spans digital health, diagnostics, and therapeutics.

Current Role at Stanford


Technology Architect, Stanford Medicine Catalyst; Lead Architect, Building for Digital Health, Stanford Byers Center for Biodesign; Instructor, Stanford CS342/MED253

Education & Certifications


  • Board Certification, American Board of Internal Medicine
  • Residency, Icahn School of Medicine at Mount Sinai
  • MD, Albany Medical College
  • BA, Cornell University

All Publications


  • CardinalKit: open-source standards-based, interoperable mobile development platform to help translate the promise of digital health. JAMIA open Aalami, O., Hittle, M., Ravi, V., Griffin, A., Schmiedmayer, P., Shenoy, V., Gutierrez, S., Venook, R. 2023; 6 (3): ooad044

    Abstract

    Smartphone devices capable of monitoring users' health, physiology, activity, and environment revolutionize care delivery, medical research, and remote patient monitoring. Such devices, laden with clinical-grade sensors and cloud connectivity, allow clinicians, researchers, and patients to monitor health longitudinally, passively, and persistently, shifting the paradigm of care and research from low-resolution, intermittent, and discrete to one of persistent, continuous, and high resolution. The collection, transmission, and storage of sensitive health data using mobile devices presents unique challenges that serve as significant barriers to entry for care providers and researchers alike. Compliance with standards like HIPAA and GDPR requires unique skills and practices. These requirements make off-the-shelf technologies insufficient for use in the digital health space. As a result, budget, timeline, talent, and resource constraints are the largest barriers to new digital technologies. The CardinalKit platform is an open-source project addressing these challenges by focusing on reducing these barriers and accelerating the innovation, adoption, and use of digital health technologies. CardinalKit provides a mobile template application and web dashboard to enable an interoperable foundation for developing digital health applications. We demonstrate the applicability of CardinalKit to a wide variety of digital health applications across 18 innovative digital health prototypes.

    View details for DOI 10.1093/jamiaopen/ooad044

    View details for PubMedID 37485467

    View details for PubMedCentralID PMC10356573

  • Design and Implementation of an Electronic Health Record-Integrated Hypertension Management Application. Journal of the American Heart Association Funes Hernandez, M., Babakhanian, M., Chen, T. P., Sarraju, A., Seninger, C., Ravi, V., Azizi, Z., Tooley, J., Chang, T. I., Lu, Y., Downing, N. L., Rodriguez, F., Li, R. C., Sandhu, A. T., Turakhia, M., Bhalla, V., Wang, P. J. 2024; 13 (2): e030884

    Abstract

    High blood pressure affects approximately 116 million adults in the United States. It is the leading risk factor for death and disability across the world. Unfortunately, over the past decade, hypertension control rates have decreased across the United States. Prediction models and clinical studies have shown that reducing clinician inertia alone is sufficient to reach the target of ≥80% blood pressure control. Digital health tools containing evidence-based algorithms that are able to reduce clinician inertia are a good fit for turning the tide in blood pressure control, but careful consideration should be taken in the design process to integrate digital health interventions into the clinical workflow.We describe the development of a provider-facing hypertension management platform. We enumerate key steps of the development process, including needs finding, clinical workflow analysis, treatment algorithm creation, platform design and electronic health record integration. We interviewed and surveyed 5 Stanford clinicians from primary care, cardiology, and their clinical care team members (including nurses, advanced practice providers, medical assistants) to identify needs and break down the steps of clinician workflow analysis. The application design and development stage were aided by a team of approximately 15 specialists in the fields of primary care, hypertension, bioinformatics, and software development.Digital monitoring holds immense potential for revolutionizing chronic disease management. Our team developed a hypertension management platform at an academic medical center to address some of the top barriers to adoption and achieving clinical outcomes. The frameworks and processes described in this article may be used for the development of a diverse range of digital health tools in the cardiovascular space.

    View details for DOI 10.1161/JAHA.123.030884

    View details for PubMedID 38226516

  • Utility of smart watches for identifying arrhythmias in children. Communications medicine Zahedivash, A., Chubb, H., Giacone, H., Boramanand, N. K., Dubin, A. M., Trela, A., Lencioni, E., Motonaga, K. S., Goodyer, W., Navarre, B., Ravi, V., Schmiedmayer, P., Bikia, V., Aalami, O., Ling, X. B., Perez, M., Ceresnak, S. R. 2023; 3 (1): 167

    Abstract

    Arrhythmia symptoms are frequent complaints in children and often require a pediatric cardiology evaluation. Data regarding the clinical utility of wearable technologies are limited in children. We hypothesize that an Apple Watch can capture arrhythmias in children.We present an analysis of patients ≤18 years-of-age who had signs of an arrhythmia documented by an Apple Watch. We include patients evaluated at our center over a 4-year-period and highlight those receiving a formal arrhythmia diagnosis. We evaluate the role of the Apple Watch in arrhythmia diagnosis, the results of other ambulatory cardiac monitoring studies, and findings of any EP studies.We identify 145 electronic-medical-record identifications of Apple Watch, and find arrhythmias confirmed in 41 patients (28%) [mean age 13.8 ± 3.2 years]. The arrythmias include: 36 SVT (88%), 3 VT (7%), 1 heart block (2.5%) and wide 1 complex tachycardia (2.5%). We show that invasive EP study confirmed diagnosis in 34 of the 36 patients (94%) with SVT (2 non-inducible). We find that the Apple Watch helped prompt a workup resulting in a new arrhythmia diagnosis for 29 patients (71%). We note traditional ambulatory cardiac monitors were worn by 35 patients (85%), which did not detect arrhythmias in 10 patients (29%). In 73 patients who used an Apple Watch for recreational or self-directed heart rate monitoring, 18 (25%) sought care due to device findings without any arrhythmias identified.We demonstrate that the Apple Watch can record arrhythmia events in children, including events not identified on traditionally used ambulatory monitors.

    View details for DOI 10.1038/s43856-023-00392-9

    View details for PubMedID 38092993

    View details for PubMedCentralID 4937287

  • Lubricin: a novel means to decrease bacterial adhesion and proliferation. Journal of biomedical materials research. Part A Aninwene, G. E., Abadian, P. N., Ravi, V., Taylor, E. N., Hall, D. M., Mei, A., Jay, G. D., Goluch, E. D., Webster, T. J. 2015; 103 (2): 451-62

    Abstract

    This study investigated the ability of lubricin (LUB) to prevent bacterial attachment and proliferation on model tissue culture polystyrene surfaces. The findings from this study indicated that LUB was able to reduce the attachment and growth of Staphylococcus aureus on tissue culture polystyrene over the course of 24 h by approximately 13.9% compared to a phosphate buffered saline (PBS)-soaked control. LUB also increased S. aureus lag time (the period of time between the introduction of bacteria to a new environment and their exponential growth) by approximately 27% compared to a PBS-soaked control. This study also indicated that vitronectin (VTN), a protein homologous to LUB, reduced bacterial S. aureus adhesion and growth on tissue culture polystyrene by approximately 11% compared to a PBS-soaked control. VTN also increased the lag time of S. aureus by approximately 43%, compared to a PBS-soaked control. Bovine submaxillary mucin was studied because there are similarities between it and the center mucin-like domain of LUB. Results showed that the reduction of S. aureus and Staphylococcus epidermidis proliferation on mucin coated surfaces was not as substantial as that seen with LUB. In summary, this study provided the first evidence that LUB reduced the initial adhesion and growth of both S. aureus and S. epidermidis on a model surface to suppress biofilm formation. These reductions in initial bacteria adhesion and proliferation can be beneficial for medical implants and, although requiring more study, can lead to drastically improved patient outcomes.

    View details for DOI 10.1002/jbm.a.35195

    View details for PubMedID 24737699

    View details for PubMedCentralID PMC4669951