Improving Patient Experience During In-Office Procedures Using PARVA - Patient Augmented Reality Vibratory Array; Using Precision Medicine to Improve Prevention and Reduce the Cost of Healthcare
Cullen, Tucker, School of Engineering and Applied Science, University of Virginia
Ferguson, Sean, EN-Engineering and Society, University of Virginia
Barker, Shannon, EN-Biomed Engr Dept, University of Virginia
Daniero, James, UVA Health - Otolaryngology, University of Virginia
McColl, Logan, MD-DMED Student Affairs, University of Virginia
Gutierrez, Claudia, UVA Health - Otolaryngology, University of Virginia
Modern technological advances are having a profound effect across all areas of medicine. Treatment plans are becoming more precise and data-driven, and procedures are becoming less invasive. However, implementing these new technologies comes with its own challenges. For example, precision therapies can be extremely expensive, and minimally invasive in-office procedures can be more stressful for patients. The technical project and STS thesis presented here both revolve around solving some of these implementation challenges of new medical technologies in order to harness their full potential.
The technical component of this portfolio involves the development of a multisensory stimulation device intended to reduce patient perception of pain during in-office otolaryngology procedures. The term in-office refers to procedures that are conducted in a regular doctor’s office – as opposed to an operating room – where the patient is only given local anesthetic and kept awake throughout the entire procedure. As one might imagine, remaining coherent throughout these procedures can be incredibly stressful for the patient. The device my team and I developed uses augmented reality immersion and vibratory stimulation to distract the patient and ease anxiety, making in-office procedures more comfortable and accessible.
My STS thesis discusses the feasibility of precision medicine within the context of the American healthcare system, and proposes an implementation of precision medicine that focuses on preventative care in order to reduce costs. While precision medicine promises to revolutionize medicine and lead to significantly better patient outcomes, developing precision therapies can be quite costly, and reduction in uncertainty through genomics threatens to undermine the business model of private healthcare. However, America also currently lacks a focus on preventative care, even though increasing the use of preventative measures has been shown to reduce healthcare costs. As my thesis argues, precision medicine is well equipped to fill this gap in preventative care, which could provide an avenue for mitigating the other cost increases that are expected to come with this new model of health care.
Given the virtual nature of this year, our technical capstone project was fraught with delays and difficulties. We lacked access to many of the prototyping facilities that are generally available to BME students, we were not allowed observe patients in the clinic, and had to pass hardware back and forth between different team members. We were still able to create fully-functioning prototypes, but much testing still needs to be done to validate our designs. Similarly, my thesis work identifies some promising avenues for exploration in linking precision medicine to preventative care, but it primarily serves as a jumping off point for further inquiry and analysis.
I would like to thank my capstone advisors and instructors, Logan McColl, Dr. Claudia Gutierrez, Dr. James Daniero, Professor Timothy Allen, and Professor Shannon Barker for all their guidance and encouragement. Additionally, I’d like to thank Professor Bryn Seabrook and Professor Sean Ferguson for all their help in crafting my thesis.
BS (Bachelor of Science)
In-Office Procedures, Augmented Reality, Otolaryngology, Gate Control, Precision Medicine, Genomics
School of Engineering and Applied Science
Bachelor of Science in Biomedical Engineering
Technical Advisor: Shannon Barker
STS Advisor: Sean Ferguson
Technical Team Members: Sarah Glatz, Rehan Chaudhry, Chaeyeon Kim