Penn State National Science Foundation Center for Health Organization Transformation
(Penn State CHOT) - An Industry-University Cooperative Research Center
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2019 Spring Industry Advisory Board Meeting Recap
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IAB Meeting Recap
The Center for Health Organization Transformation's (CHOT) 2019 Spring Industry Advisory
Board (IAB) Meeting, held April 3-4, was hosted by Penn State
Great Valley in Malvern, Pennsylvania. There were more than 60
individuals in attendance, including 11 IAB members and four potential IAB members.
The week comprised of 17 research project proposal presentations, which included two members representing Penn State with their research proposals. CHOT's 2019/2020 research themes include population health, care coordination, analytics and innovative technologies, patient experience, and access to care.
After each project proposal presentation, IAB members, guests, faculty, and students were able to discuss the proposals' research aims and approaches during
15-minute question and answer sessions.
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"The CHOT team had a wonderful experience at the spring conference. Two of our own Penn State members presented meaningful and impactful work that sparked insightful conversation and excitement among the industry members attending. The atmosphere consisted of a strong passion for creating paradigm shifts in the way effective health care is accomplished, and continues to inspire the students working at Penn State to establish such change." - Mallory Peterson, medical student in engineering at Milton S. Hershey Medical Center
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"I had a wonderful experience witnessing the strong showing of Penn State in CHOT presentations/ workshops and it was good to learn about the outcomes of projects. Attending the meetings was also very informative about the project structure for next year." - Rajeev Bhatt, graduate assistant in electrical engineering
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"The IAB meeting was a great experience for me. Together with Prof. Qiushi Chen, I presented the proposal for combating the current opioid crisis. We are able to get connected with a few industry partners (e.g., Hershey Medical Center, Highmark, and York Risk Group), as well as other CHOT university sites (e.g., UAB), for further collaborations." - Leon Xu, doctoral student in Smeal College of Business
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"I had a great opportunity to present my research. There was a great interest in my talk and audiences from industry and academia asked lots of questions about it. It was wonderful to know the idea of practitioners my hearing my research, which helps me significantly to perform more impact and real-life research." - Farhad Imani, graduate student in Industrial Engineering
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Ph.D. student Leon Xu and Associate Professor Hui Zhao from Smeal College of Business present at April IAB meeting
Leon Xu, doctoral student in business administration, presented "A Prediction, Prevention, and Intervention Model to Combat the Opioid Epidemic" at the April IAB meeting, on behalf of the Penn State research team, which consisted of Professor Qiushi Chen, Professor Hui Zhao, and Xu.
The new proposal on opioid research further investigates the individual treatment pathway and individually-customized prediction models to predict patient behavior (treatment retention/relapse) and health outcomes.
While most research has focused on the supply side of the opioid problem (e.g., tighter control of pres
cription), this research looks at the demand-side of the opioid problem, studying the impact of treatment facilities of opioid addicts. Using data from
2006-2017 on the National Survey of Substance Abuse Treatment Services, data from 2006-2017 on CDC Wonder, and data from 2006-2017 on Healthcare Cost and Utilization Project (HCUP), the researchers quantified that on average, 1% increase of the number of s
ubstance use treatment
facilities leads to a 2.7% decrease of opioid overdose death and 0.21% decrease of opioid-related emergency room visits. Compared to previous research that only indicates the potential relationships without quantifying them, these results provide evidence and policy implications for improving the accessibility of treatment facilities
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The research is concluded, results were presented in the April IAB meeting, and a manuscript is being prepared to be submitted to a health policy journal, "Health Affairs."
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Graduate student, Farhad Imani presents at April IAB meeting
Farhad Imani, a graduate student in Industrial Engineering presented his research in "data-enabled predictive modeling and intervention
optimization of breast cancer" at the spring CHOT IAB meeting on behalf of the Penn State research team, which consisted of Dr. Hui Yang, Dr. Conrad Tucker and graduate student Ruimin Chen.
Imani shared his findings of the recurrence analysis of breast cancer incidences and the important factor that has an impact on the recurrence of breast cancer. His presentation included a focus about leveraging this data to improve the quality of life for patients who suffers from breast cancer.
In his submitted abstract Imani stated that;
The recurrence of breast cancer is a prevailing problem which decreases the quality of a patients' lives, leads to the high expenditure in post-treatment screening for families and influences well-being of society. The advancements in sensing technology provide an unprecedented opportunity to increase information visibility and describe the patterns of event occurrence.
Research has been submitted to IEEE International Conference on Automation Science and Engineering 2019. Another conference paper is currently being worked on which will be presented in coming INFORMS conference.
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Penn State CHOT Research Highlights
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Text Summarizer
Rajeev Bhatt, a master's student in the College of
Engineering,
with his adviser, College of Information Sciences and Technology Professor Prasenjit Mitra, are building a state-of-the-art text summarizer.
The text summarizer
takes a large
document as an input to automatically summarize the important highlights in a few sentences. The model is built on fundamentals from deep learning largely due to its effectiveness in predictive modeling and scalability with available training data.
ROUGE is a standard measure to evaluate the quality of a summarizer compared to a human benchmark. The model currently has a ROUGE score of 39 compared to the state-of-the-art of around 41. Bhatt and Professor Mitra are working toward the advancement of the summarization.
Bhatt is hoping to submit the research project to the Conference on Empirical Methods in Natural Language Processing.
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Hosted by the University of Washington
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Date: Thurs., Oct.17, 2019 and Fri., Oct.18, 2019
Location: University of Washington
More information can be found here. |
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