Christian Wernz, Ph.D., joined the Grado Department of Industrial and Systems Engineering at Virginia Tech as an Assistant Professor in Fall 2008. He conducts research in decision theory and healthcare systems engineering...(Read more: Curriculum Vitae, Publications)
Dr. Wernz teaches classes in management systems (ISE 4015), decision theory (ISE 6054) and is developing a graduate class in decision analysis...(Read more: Teaching)
Dr. Wernz is the director of the Multiscale Decision Making (MSDM) Laboratory at Virginia Tech. The lab's mission is to advance decision theory for multiscale systems and organizations. The MSDM Lab develops novel decision making tools for health care organizations and service/manufacturing enterprises. Multiscale systems show scale interdependencies across and between organizational, temporal, informational and geographical scales...(Read more: MSDM Lab Research)
A talented and diverse group of students is working on research questions related to the advancement and application of multiscale decision theory, decision analysis, organizational improvements of healthcare systems, healthcare analytics, healthcare IT, among others...(Read more: MSDM Lab Students)
The ISE department offers a variety of international programs. Dr. Wernz leads the German exchange program with the Karlsruhe Institute of Technology, KIT...(Read more: Study Abroad)
Prospective Ph.D. students interested in working with Dr. Wernz should apply via the graduate school at Virginia Tech to the ISE program and indicate their research interests in their statement letter. Please understand that emails directly sent to Dr. Wernz cannot be answered. Acceptance decisions are made by a committee, not individual professors.
Mailing address and contact information:
Christian Wernz, Ph.D.
205 Durham Hall (0118)
1145 Perry Street
Blacksburg, VA 24061
|August 16, 2016
HCMS paper accepted:
"Modeling and Designing Health Care Payment Innovations for Medical Imaging" by Hui Zhang, Christian Wernz and Danny R. Hughes (Senior Director, Harvey L. Neiman Health Policy Institute) has been accepted for publication by Health Care Management Science. The pre-print version is available on Research Gate.
|August 1, 2016
AHRQ R21 grant awarded:
Dr. Wernz has been awarded an R21 grant from the Agency for Healthcare Research Quality (AHRQ) for "Evidence-based Contingency Planning for Electronic Health Record Downtime." Together with co-investigators Dr. Raj Ratwani and Dr. Terry Fairbanks of the National Center for Human Factors in Healthcare, the research team will assess the clinical and operational implications of EHR downtime events and develop a simulation model to improve downtime procedures.
January 18, 2016
Dell research grant awarded:
Dr. Wernz has been awarded a 2-year grant from Dell Inc. for "Agent-Based Simulation for Managerial Decision-Making and Cost Reductions for SupportAssist." The objective of this research project is to develop a decision support tool that can evaluate business opportunities for Dell's service product SupportAssist.
Aug 1, 2015
NSF EAGER awarded:
Dr. Wernz has been awarded an Early Concept Grant for Exploratory Research (EAGER) from the National Science Foundation (NSF) for "Advancing the Foundations of Systems Engineering through Multiscale Decision Theory." The objective of this 2-year research project is to derive fundamental insights into the system design process by mathematically modeling the effects and interdependencies of organizational structures, incentives, time, and information on system value creation.
June 29, 2015
Best Paper Award:
"International study of technology investment decisions at hospitals" co-authored by Dr. Wernz, Hui Zhang (PhD student) and Dr. Kongkiti Phusavat (Kasetsart University, Thailand) received the 2015 Highly Commended Paper Award from the Industrial Management Data Systems journal.
May 1, 2015
ACR grant renewed:
Dr. Wernz has been awarded a second year of funding from the Harvey L. Neiman Health Policy Institute (HPI) of the American College of Radiology (ACR) for "Integrating model-driven and data-driven approaches to advance healthcare payment innovations."