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Duke Acute Care Technology Laboratory (DACTL)

Photo of Daniel Buckland, MD, MS, PhD

Daniel Buckland, MD, MS, PhD

Campus Mail: DUMC Box 3096, 2301 Erwin Road, Durham, NC 27710

Overview

Led by Daniel Buckland, MD, PhD, a physician in the Division of Emergency Medicine and Assistant Professor of Mechanical Engineering, the focus of the Duke Acute Care Technology Laboratory (DACTL) is on the development of safety critical technology solutions for acute medical conditions at the interface of Data Science, Robotics, and Human Health. We have a special interest in resource-limited operations, including human spaceflight, rural medicine, wilderness medicine, or even well-resourced academic medical center emergency rooms when dealing with the logistics of operating in the current era of medical care.

We are engineers and physicians collaborating on solving acute clinical problems through technology.

Program Highlights

  • NASA-funded study to develop an autonomous IV placement robot
  • Data Science projects predicting near-term health outcomes with the Duke Institute for Health Innovation (DIHI) and the Laboratory for Transformative Administration (Dept of Surgery)
  • Development of drone networks to deliver medical care to Durham-area patients

Members

  • Daniel Buckland
  • Brandon Ruderman
  • PhD Student: Siobhan Oca
  • PhD Student: Nicolas Garside
  • AI.Health@Duke Fellow: Hamed Zaribafzadeh
  • AI.Health@Duke Fellow: Connor Davis

Selected Achievements

Development of drone networks to deliver acute medical care to reduce time to care over existing EMS systems.

  • Starks, M.A., Blewer, A.L., Sharpe, E., Van Vleet, L., Riley, J., Arnold, E., Slattery, J., Joiner, A., Buckland, D.M., Ye, J. and Mark, D., 2020. Bystander performance during simulated drone delivery of an AED for mock out-of-hospital cardiac arrest. Journal of the American College of Cardiology, 75(11 Supplement 1), p.303.
  • Ye, J.J., Zhang, C., Vissoci, J.R.N. and Buckland, D., 2019. Optimizing a Drone Network to Deliver Naloxone. Annals of Emergency Medicine, 74(4), p.S64.
  • Buckland, D.M., Mark, D.B., Banerjee, A.G., Snyder, K. and Starks, M.A., 2019, March. Design Considerations for UAV-Delivered Opioid Overdose Interventions. In 2019 IEEE Aerospace Conference (pp. 1-7). IEEE.

Ongoing Collaborations

Advanced Training

Able to consider clinical or research fellowships in medical technology development.

Collaborate with Us

Please contact Dan Buckland (dan.buckland@duke.edu) for more information or potential collaborations.

Lab Website

Visit the Duke Acute Care Technology Laboratory website for up-to-date news and job openings for students.

Latest Publications

Fenn, Alexander, Connor Davis, Daniel M. Buckland, Neel Kapadia, Marshall Nichols, Michael Gao, William Knechtle, Suresh Balu, Mark Sendak, and B Jason Theiling. “Development and Validation of Machine Learning Models to Predict Admission From Emergency Department to Inpatient and Intensive Care Units.” Annals of Emergency Medicine 78, no. 2 (August 2021): 290–302. https://doi.org/10.1016/j.annemergmed.2021.02.029.

Full Text

Oca, Siobhan R., Angelo Navas, Erin Leiman, and Daniel M. Buckland. “Effect of language interpretation modality on throughput and mortality for critical care patients: A retrospective observational study.” Journal of the American College of Emergency Physicians Open 2, no. 4 (August 2021): e12477. https://doi.org/10.1002/emp2.12477.

Full Text

Garside, Nicholas, Hamed Zaribafzadeh, Ricardo Henao, Royce Chung, and Daniel Buckland. “CPT to RVU conversion improves model performance in the prediction of surgical case length.” Scientific Reports 11, no. 1 (July 8, 2021): 14169. https://doi.org/10.1038/s41598-021-93573-2.

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Ma, Guangshen, Weston Ross, Matthew Tucker, Po-Chun Hsu, Daniel M. Buckland, and Patrick J. Codd. “Touch-Point Detection Using Thermal Video With Applications to Prevent Indirect Virus Spread.” Ieee Journal of Translational Engineering in Health and Medicine 9 (January 2021): 4900711. https://doi.org/10.1109/jtehm.2021.3083098.

Full Text