Assistant Professor of Health Policy & Clinical Practice and Adjunct Assistant Professor in Computer Science
Geisel School of Medicine at Dartmouth College
Inas Khayal, PhD is an Assistant Professor at the Dartmouth Institute of Health Policy & Clinical Practice at the Geisel School of Medicine and Adjunct Assistant Professor at the Department of Computer Science at Dartmouth College. Dr. Khayal is a highly interdisciplinary researcher focused on translational research toward improving chronic disease health outcomes. Her training and experience in biomedical engineering, management of technology, and engineering systems allowed her to develop the concept of Sustainable Health. This began with her biomedical research within the clinic, focused on biological sensing in NeuroOncology and MR Imaging. Her work expanded to include Social and Environmental Sensing using Internet-of-Things enabled sensors outside the clinic and within ‘real-world’ living labs. Her work acts at the intersection of engineering, medicine, computer science, and innovation to address the reality of the multi-level interconnected systems we live in. Her most recent work seeks to develop systems solutions that curb the growth of chronic disease by modeling, measuring, designing, and implementing systems. Dr. Khayal earned her PhD in Bioengineering from both the University of California, Berkeley and the University of California, San Francisco, a BS in Biomedical Engineering from Boston University and completed the Management of Technology Program at the University of California, Berkeley, Haas School of Business. She holds several US, European, and international patents and is featured in the book Medicine by Design: The Practice and Promise of Biomedical Engineering by Fen Montaigne. She has also been selected as a 2017 Systems Science Scholar by AcademyHealth. She has served on the faculty in the departments of Medicine, Engineering, and Computer Science.
Our health is influenced by the places we live, work, and play. Improving and maintaining health requires creating healthier, more equitable communities. Many stakeholders at different levels are beginning to work collaboratively to improve health (ranging from neighboring towns, to local neighborhood coalitions, to more regional initiatives). Most attempts to compare one community to another have used a limited number of health factors (e.g. housing, transit, income, education level, healthcare access) and, more importantly, have relied upon ad-hoc intuitive judgments. Communities are multi-faceted social, economic, and physical interconnected systems. The goal of this project is to identify patterns of these multi-faceted community factors, which then form what we define here as community system typologies (or types of community systems). Community factors compiled mostly from public and some private data will be analyzed using engineering and computer science techniques. Community stakeholders may use such typologies as a holistic measure of their community to: better understand health outcomes, choose a successful community intervention from an area with a similar typology, collaborate with similar-proximity typology areas for community improvement and change, or to identify critical sector stakeholders to foster cross-sector collaboration
Why did you apply to New Connections
Professionally, I have been blessed with the ability to interact with a diverse population of colleagues, mentors, and mentees. That being said, diversity and culture even as it affected and shaped my experiences was rarely directly addressed. As an Arab-American, I felt drawn to joining a professional network with diversity as a focus.
Dr. Khayal’s primarily research interest comes from a deep-rooted drive to keep people healthy. Her research began primarily focused on understanding human body content using imaging technology. Focusing on health outcomes as my goal, Dr. Khayal realized she needed to expand her research to incorporate understanding human context. This included the use of technology to measure biological, social, and environmental factors outside the clinical setting. The use of mobile technologies without an integration into the clinic fell short in the promise to affect health outcomes. Health is everywhere. The reality of chasing after health outcomes is that researchers are forced out of reductionist thinking of many classical fields to systems thinking. This led to Dr. Khayal’s systems research, considering health and health care to integrate our understanding of content and context. I use methods and tools from engineering, computer science, medicine, implementation science, and design to focus on assessing, designing, and analyzing health and healthcare systems.
I. Khayal and A. Farid, “Architecting a System Model for Personalized Healthcare Delivery and Managed Individual Health Outcomes,” Complexity (in press), 2017.
I. S. Khayal and A. M. Farid, “The Need for Systems Tools in the Practice of Clinical Medicine,” Systems Engineering, vol. 20, no. 1, pp. 3–20, Jan 2017.
I.Khayal and A. Farid, “Designing Smart Cities for Citizen Health & Well-being,”in Proceedings of the 2017 IEEE International Summer School on Smart Cities (IEEE S3C), August 2017.
I. Khayal, M. McGovern, M. Bruce, and S. Bartels, “Developing an Integrated Behavioral Health System Model using Engineering Design,” in Proceedings of the 2017 Institute of Industrial and Systems Engineering Annual Conference, Pittsburgh, PA, May 2017.
I. Khayal and A. Farid, “A Dynamic Model for a Cyber-Physcal Healthcare Delivery System with Human Agents,” in Proceedings of the 2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC2017), Intelligent Industrial System Special Issue, October 2017.
I. Khayal and A. Farid, “An Architecture for a Cyber-Physical Healthcare Delivery System with Human Agents,” in Proceedings of the 2017 IEEE International Summer School on Smart Cities (IEEE S3C), August 2017.
I. Khayal, W. Zhou, and J. Skinner, “Structuring and Visualizing Healthcare Claims Data Using Systems Architecture,” International Journal of Biological, Biomolecular, Agricultural, Food and Biotechnological Engineering, vol. 11, no. 4, pp. 342–346, 2017.
I. Khayal and A. M. Farid, “Axiomatic Design Based Human Resources Management for the En- terprise Transformation of the Abu Dhabi Healthcare Labor Pool,” Journal of Enterprise Transfor- mation, vol. 5, no. 3, pp. 162–191, 2015.
I. Khayal, W. Zhou, and J. Skinner, “Structuring and Visualizing Healthcare Claims Data Using Systems Architecture,” in Proceedings of the 19th International Conference on Bioinformatics, Computational Biology and Biomedical Engineering, Boston, MA, April 2017.
- New Connections Status: Junior Investigator
- Award Year: 2018
- RWJF Team/Portfolio: Creating Healthier, More Equitable Communities
- Project Name: Developing and Understanding Neighborhood Typologies Using Machine Learning Methods