About

John R. Richards, M.D., F.A.A.E.M., F.R.S.M., is a professor in the Department of Emergency Medicine at UC Davis Health. His research interests include the treatment of alcohol, cannabis, and stimulant toxicity and addiction, as well as solutions for overcrowding in emergency departments. Dr. Richards completed his undergraduate studies with a B.A. in Molecular Biology from UC Berkeley in 1989 and earned his M.D. from UC Davis School of Medicine in 1993. He completed his residency in Emergency Medicine at UC Davis Medical Center from 1993 to 1996. Throughout his career, Dr. Richards has received several honors, including the C. John Tupper Prize for Excellence in Teaching in 2019, the Distinguished Teaching Award from UC Davis Academic Senate in 2017, and the Society for Academic Emergency Medicine Award for Excellence in 2017. His research has contributed to understanding the physiology of cardiac repolarization and sodium channels, as well as clinical management of overdose cases involving stimulants and alcohol. He has authored multiple publications on emergency medicine topics and is recognized for his expertise in ultrasound, treatment of toxicity, and emergency department overcrowding solutions.

Research topics

• Medicine
• Internal medicine
• Anesthesia
• Psychiatry
• Surgery
• Cardiology
• Pharmacology
• Emergency medicine
• Dermatology
• Psychology
• Physical therapy
• Medical emergency
• Intensive care medicine
• Family medicine

Selected publications

• Review of previously published ambient air respirable crystalline silica concentration data for use in risk assessment of mineral industry sources

  Frontiers in Public Health · 2025-04-30 · 3 citations

  reviewOpen access1st authorCorresponding

  This paper is part of a set of papers concerning the possible health implications of ambient respirable crystalline silica beyond the fencelines of mineral industry sources such as frac sand, construction sand, crushed stone, and specialty silica product plants. Previously published ambient respirable crystalline silica data relevant to mineral industry sources are reviewed to identify the typical and maximum downwind ambient respirable crystalline silica concentrations expected beyond facility fencelines. These typical and maximum downwind concentrations can be used in risk assessment studies. Relevant RCS facility downwind and upwind ambient data sets previously compiled by the authors, state regulatory agencies, the Agency for Toxic Substances and Disease Registration (ASTDR), and academic researchers are reviewed. Emphasis is placed on data sets compiled in multi-year sampling programs that take into account seasonal variations and facility operational variations. To the extent possible, data from different geographic areas are included to account for differing background (upwind) concentrations. The ambient RCS data are condensed to yield mean and maximum long-term average concentrations that can be used in risk assessment studies. There is a high degree of consistency in the RCS concentration data published by numerous researchers at a wide variety of mineral industry facilities. The authors recommend a mean concentration of 0.28 μg/m 3 as an estimate of the long term average RCS concentration downwind of the fencelines of typical mineral industry facilities and a maximum concentration of 1.5 μg/m 3 as an estimate of 95% upper confidence level of the mean RCS concentration downwind of the fencelines of especially large mineral industry facilities and/or those facilities where the very hilly terrain limit dispersion of facility emissions. The authors recommend a mean concentration of 0.22 μg/m 3 as an estimate of the typical long term average background concentrations. If there are community health concerns at the RCS concentrations in the range of 0.22 to 0.28 μg/m 3 , new measurement procedures that provide higher 24-h sample volumes and/or more sensitive analytical techniques would be needed to provide accurate community exposure data.

  PublisherOA PDFDOI

• FUTURE PROOFING NAVY VERTICAL LIFT: A MISSION CENTERED OPTIMIZATION FRAMEWORK FOR MANNED–UNMANNED FORCE COMPOSITION

  Calhoun: The Naval Postgraduate School Institutional Archive (Naval Postgraduate School) · 2025-09-01

  dissertation1st authorCorresponding

  Includes Supplementary Material

  Publisher

• Quantitative AI Risk Assessments: Opportunities and Challenges

  Seton Hall Journal of Legislation and Public Policy · 2025-01-01

  articleOpen accessSenior author

  Although artificial intelligence (AI) systems are increasingly being leveraged to provide value to organizations, individuals, and society, significant attendant risks have been identified 1 and have manifested.

  PublisherOA PDFDOI

• Developing a Risk Identification Framework for Foundation Model Uses

  ArXiv.org · 2025-06-01

  preprintOpen access

  As foundation models grow in both popularity and capability, researchers have uncovered a variety of ways that the models can pose a risk to the model's owner, user, or others. Despite the efforts of measuring these risks via benchmarks and cataloging them in AI risk taxonomies, there is little guidance for practitioners on how to determine which risks are relevant for a given foundation model use. In this paper, we address this gap and develop requirements and an initial design for a risk identification framework. To do so, we look to prior literature to identify challenges for building a foundation model risk identification framework and adapt ideas from usage governance to synthesize four design requirements. We then demonstrate how a candidate framework can addresses these design requirements and provide a foundation model use example to show how the framework works in practice for a small subset of risks.

  PublisherOA PDFDOI

• Alternative Importance Measure for Seismic Probabilistic Risk Assessments

  2023-01-01

  article
  PublisherDOI

• Effects of process changes on emergency department crowding in a changing world: an interrupted time-series analysis

  International Journal of Emergency Medicine · 2023-02-15 · 12 citations

  articleOpen access

  Abstract Background During a 6-year period, several process changes were introduced at the emergency department (ED) to decrease crowding, such as the implementation of a general practitioner cooperative (GPC) and additional medical staff during peak hours. In this study, we assessed the effects of these process changes on three crowding measures: patients’ length of stay (LOS), the modified National ED OverCrowding Score (mNEDOCS), and exit block while taking into account changing external circumstances, such as the COVID-19 pandemic and centralization of acute care. Methods We determined time points of the various interventions and external circumstances and built an interrupted time-series (ITS) model per outcome measure. We analyzed changes in level and trend before and after the selected time points using ARIMA modeling, to account for autocorrelation in the outcome measures. Results Longer patients’ ED LOS was associated with more inpatient admissions and more urgent patients. The mNEDOCS decreased with the integration of the GPC and the expansion of the ED to 34 beds and increased with the closure of a neighboring ED and ICU. More exit blocks occurred when more patients with shortness of breath and more patients > 70 years of age presented to the ED. During the severe influenza wave of 2018–2019, patients’ ED LOS and the number of exit blocks increased. Conclusions In the ongoing battle against ED crowding, it is pivotal to understand the effect of interventions, corrected for changing circumstances and patient and visit characteristics. In our ED, interventions which were associated with decreased crowding measures included the expansion of the ED with more beds and the integration of the GPC on the ED.

  PublisherOA PDFDOI

• Pedicel colour does not separate Epipactis dunensis (Dune Helleborine) from E. ‘sancta’ (Lindisfarne Helleborine) (Orchidaceae)

  British & Irish Botany · 2023-02-14 · 1 citations

  articleOpen access1st authorCorresponding

  The characters which supposedly differentiate the narrow endemic Epipactis sancta (Delforge) Delforge on Lindisfarne (north-east England) from ‘Tyne’ and west coast (type) populations of Epipactis dunensis (T. & T.A. Stephenson) Godfery are examined. Lindisfarne plants vary for purple staining of the pedicel, while ‘Tyne’ populations and at least some west coast plants lack this character. There is no significant difference between ‘Tyne’ and Lindisfarne populations for the relative length of the inflorescence (position of uppermost leaf). It is shown that other supposed differences are apparently trivial. It is considered that minor differences in sequence in chloroplast DNA between the populations do not in themselves suggest that E. sancta deserves specific rank. It is concluded that the Lindisfarne population is best regarded as E. dunensis.

  PublisherOA PDFDOI

• Emergency Department Hallway Care From the Millennium to the Pandemic: A Clear and Present Danger

  Journal of Emergency Medicine · 2022-09-11 · 13 citations

  articleOpen access1st authorCorresponding
  PublisherOA PDFDOI

• AI Explainability 360: Impact and Design

  Proceedings of the AAAI Conference on Artificial Intelligence · 2022-06-28 · 17 citations

  articleOpen access

  As artificial intelligence and machine learning algorithms become increasingly prevalent in society, multiple stakeholders are calling for these algorithms to provide explanations. At the same time, these stakeholders, whether they be affected citizens, government regulators, domain experts, or system developers, have different explanation needs. To address these needs, in 2019, we created AI Explainability 360, an open source software toolkit featuring ten diverse and state-of-the-art explainability methods and two evaluation metrics. This paper examines the impact of the toolkit with several case studies, statistics, and community feedback. The different ways in which users have experienced AI Explainability 360 have resulted in multiple types of impact and improvements in multiple metrics, highlighted by the adoption of the toolkit by the independent LF AI & Data Foundation. The paper also describes the flexible design of the toolkit, examples of its use, and the significant educational material and documentation available to its users.

  PublisherOA PDFDOI

• Cannabis hyperemesis syndrome: Incidence and treatment with topical capsaicin

  Medicina Clínica (English Edition) · 2022-07-26 · 1 citations

  articleSenior author
  PublisherDOI

Frequent coauthors

• Robert W. Derlet

  52 shared

• John P. Congalidis

  Experimental Station

  42 shared

• Edward A. Panacek

  University of South Alabama

  31 shared

• John P. McGahan

  University of California, Davis

  27 shared

• Sridevi Devaraj

  Baylor College of Medicine

  26 shared

• Sally P. Stabler

  University of Colorado Denver

  26 shared

• Jesse F. Gregory

  University of Florida

  26 shared

• Janet M Peerson

  26 shared

Awards & honors

• C. John Tupper Prize for Excellence in Teaching (2019)
• Distinguished Teaching Award, UC Davis Academic Senate (2017…
• First Place, IGNITE! Society of Academic Emergency Medicine…
• Society for Academic Emergency Medicine Award for Excellence…
• Alpha Omega Alpha Research Fellowship (1992)