Member Spotlight: Devin McCaslin
Our Precision Health member of the month, featured in this Member Spotlight, is Devin McCaslin, PhD. Dr. McCaslin is Clinical Professor of Otolaryngology-Head and Neck Surgery, and Director of the Audiology program at Michigan Medicine.
As director of the audiology program, McCaslin partners with individuals from across audiology, the department and the organization to guide the program into the future. He provides clinical leadership and practice oversight to audiologists, both faculty and staff, across the department. McCaslin’s collaboration with researchers, operations and program leaders and audiology team members focuses on identifying and executing opportunities to enhance clinical service delivery, advance science and support the professional growth of individuals.
Dr. McCaslin and colleagues have a new publication in OTO Open, “Development of an Automated Triage System for Longstanding Dizzy Patients Using Artificial Intelligence”, which can be read here. Let’s hear more from Dr. McCaslin:
- Tell us a bit more about the focus and details of your current research/projects
My current research focuses on automated triage in otolaryngology, particularly addressing dizziness and balance disorders. The project aims to develop an interactive, learning-based care pathway using machine learning models to optimize patient triage. By providing real-time recommendations on testing and consultations based on patient symptoms, the goal is to streamline the diagnostic process and reduce delays in care.
- What is innovative/new/exciting about these projects?
The use of a neural network for creating a data-driven care pathway is a novel approach in managing dizziness and balance issues. The project integrates front-end clinical recommendations with backend predictive modeling, allowing the system to learn and improve over time. This dynamic framework has the potential to expand beyond dizziness to other areas of otolaryngology, such as audiology, neurotology and laryngology.
- What is the anticipated outcome of this research?
The anticipated outcome is a streamlined process for diagnosing and managing dizziness, which will lead to faster, more accurate patient care. It will enable primary care and non-specialist clinicians to make informed decisions on the appropriate care pathway for patients, potentially reducing healthcare costs and improving quality of care
- How will it benefit patients and clinicians?
Patients will benefit from quicker access to appropriate care, reducing the need for multiple specialist visits. Clinicians will have a tool to guide decision-making, helping to ensure patients receive the right tests and consultations from the start. This approach could also decrease healthcare expenses and improve patient satisfaction through a more efficient care process.
- How is Precision Health is supporting this research?
By providing key resources like the Precision Health Analytics Platform and DataDirect, which simplify access to relevant datasets for cohort discovery. This platform enables efficient data analysis, while the member database connects me with interdisciplinary collaborators across campus, boosting the scope and impact of my work.
In addition, Precision Health’s Health (Clinical) Implementation team consulted with me, and they worked to develop a non-Nebula solution, that is built using the rule editor in MiChart. This solution could work in internal medicine and general family medicine clinics to assist them in the initial triage decision process when faced with a patient with primary complaint if dizziness / balance difficulties.
- What are your research interests, broadly?
My research interests broadly cover clinical electrophysiology, vestibular assessment, and healthcare economics, with a focus on using artificial intelligence to enhance the diagnosis and management of dizziness. I aim to integrate advanced technologies into clinical practice to improve patient outcomes in audiology and balance disorders. Additionally, I am interested in exploring how data-driven approaches can optimize healthcare delivery and reduce costs in the field of otolaryngology and audiology.
- How does your work apply to the field of precision health?
My work contributes to precision health by using machine learning to create personalized care pathways for diagnosing and managing balance disorders, particularly dizziness. By optimizing diagnostic processes and tailoring interventions, this research supports goals of discovery, treatment, and improving public health outcomes, while also potentially extending these methods to other areas of otolaryngology.
- Can you share links to recent/significant work?
Outcomes and Patient Experience in Individuals With Longstanding Dizziness – PubMed (nih.gov)
- What do you like to do outside of work?
When I’m not doing research and seeing patients in clinic, I enjoy biking around Ann Arbor with my wife, traveling with her and our two children, and fishing in the Upper Peninsula of Michigan, where I grew up. These activities allow me to unwind and connect with nature while spending quality time with my family.
