2016 INFORMS Annual Meeting Program

SB22

INFORMS Nashville – 2016

4 - Applications Of Real Time Locating Systems In Ambulatory Oncology

1 - Optimal Liver Cancer Surveillance In Hepatitis C Infected Population

Sarah Kadish, Dana-Farber Cancer Instititue, Boston, MA, United States, sarah_kadish@dfci.harvard.edu, Constance Barysauskas,

Qiushi Chen, Georgia Institute of Technology, Atlanta, GA, United States, chenqiushi0812@gatech.edu, Turgay Ayer, Jagpreet Chhatwal

Ryan Leib, Avishai Mandelbaum, Petar Momcilovic, Arik Senderovich, Nikolaos Trichakis, Craig Bunnell

Liver cancer is the fastest growing cause of cancer deaths in the United States. Although early diagnosis through can improve survival, the optimal surveillance policy remains unknown. We develop a mixed-integer programming-based framework to identify the most cost-effective surveillance policy. Our framework allows a formulation of practical policy structures. Our numerical results find that (1) the optimal surveillance interval should depend on patient’s stage of hepatitis C and age, and (2) expanding surveillance to earlier stage of hepatitis C improves the cost-effectiveness of HCC surveillance. 2 - The Changing Etiology Of End Stage Liver Disease And The Implicationsfor The Liver Transplant Waitlist Maria Mayorga, North Carolina State University, memayorg@ncsu.edu Zinan Yu, Stephanie B Wheeler Changes in the epidemiology of end stage liver disease will impact future liver transplant (LT) waitlist. We performed a discrete event simulation model to forecast both regional and national LT waitlist size, number of transplants, and hazard of waitlist drop out, while considering patient arrivals, demographic and clinical attributes, waiting time and liver availability. 3 - Investigating Steroid Withdrawal Strategies For Kidney Transplant Recipients Yann B. Ferrand, Clemson University, Clemson, SC, United States, yferran@clemson.edu, Vibha Desai, Christina M. Kelton, Teresa M. Cavanaugh, Jaime Caro, Jens W. Goebel, Pamela C. Heaton We evaluate various steroid withdrawal strategies for kidney transplant recipients. The goal is to minimize major complications resulting from these complex drug regimens over the long term. We develop a model calibrated with an econometric study of patient data from a national registry to simulate the long-term course of these patients. We report on the frequency and timing of adverse events and identify trade-offs in the steroid withdrawal strategies. 4 - Eliciting Patients’ Revealed Risk Perceptions Of Dialysis And Death In Preemptive Living-donor Kidney Transplantation Masoud Barah, University of Tennessee, Knoxville, TN, United States, mbarah@vols.utk.edu, Anahita Khojandi, Murat Kurt When kidneys can no longer function at the level needed, patients must undergo either dialysis or transplantation to survive. Given empirical patterns in timing of pre-dialysis living donor transplantation, we investigate the behavioral dynamics behind patients’ risk-averse behavior. We develop an inverse MDP model to elicit the perceived life-year loss associated with kidney failure or death due to delaying transplantation. We calibrate the model using clinical literature and publicly available datasets and provide insights on patients’ perceptions of kidney failure and risk of death.

Real Time Locating Systems (RTLS) implementations have increased in the healthcare industry despite few studies supporting efficacy. In addition, the potential applications of RTLS as a tool for improving hospital operations management remains relatively unexplored. We sought to measure the improvement in quality of care and patient experience immediately after RTLS implementation. Furthermore, we explored the utility of RTLS in providing unbiased data to improve accuracy for chemotherapy scheduling. Finally, we demonstrate the ability for RTLS to assess impacts of large organizational changes such as the implementation of an Electronic Health Record on patient time in clinic. SB22 107B-MCC Panel: Challenges of Implementing OR in the Healthcare Industry Invited: ORinformed Healthcare Policies Invited Session Moderator: Michael W Carter, University of Toronto, Toronto, ON, Canada, carter@mie.utoronto.ca Implementing OR/MS in healthcare poses major challengers to practical researchers. The problems and the corresponding solutions are similar to those in industry and other service industries. So why is it so difficult? This panel brings together a group of researchers who have been successful in overcoming the challenges. 1 - The Challenge Of Lean; Working With Health Professionals Who Think O.R. Means Operating Room Panelist: Martin L Puterman, University of British Columbia, martin.puterman@sauder.ubc.ca 2 - Developing Good Collaborations And Avoiding Bad Ones Panelist: Brian T Denton, University Of Michigan, btdenton@umich.edu 3 - The Good, The Bad, And The Ugly Of Publishing Operations Research Work In Medical Journals Panelist: Sheldon H Jacobson, University Of Illinois, shj@illinois.edu 4 - Struggles In Getting Data For Healthcare Research Panelist: Amy Cohn, University Of Michigan, amycohn@umich.edu 5 - Moving The Needle In Public Health Decision Making Panelist: Margaret L Brandeau, Stanford University, brandeau@stanford.edu 108-MCC Joint Session MIF/HAS: Modeling and Optimization for Advanced Stage Liver and Kidney Disease Patients Sponsored: Health Applications Sponsored Session Chair: Anahita Khojandi, University of Tennessee Knoxville, 521 John D. Tickle Building, 851 Neyland Drive, Knoxville, TN, 37996, United States, khojandi@utk.edu Co-Chair: Murat Kurt, Merck Research Labs, 351 N. Sumneytown Pike, North Wales, PA, 19454, United States, murat.kurt7@gmail.com SB23

SB24

109-MCC Ecology of Innovation: Sources of Knowledge

and Complements Invited: Strategy Science Invited Session

Chair: Daniel Levinthal, University of Pennsylvania, Wharton School, Philadelphia, PA, 189, United States, levinthal@wharton.upenn.edu 1 - Intra-firm Spillovers? The Stock And Flow Effects Of Collocation

Evan Rawley, Columbia Business School, New York, NY, United States, erawley@columbia.edu, Robert Seamans

We study how intra-firm collocation—geographic clustering of establishments owned by the same parent company—influences performance, decomposing collocation effects to learn about the mechanisms behind intra-firm agglomeration. Using Census micro data on the population of U.S. hotels and restaurants 1977-2007, we find that doubling the intensity of intra-firm collocation is associated with a productivity increase of about 2%. Further analyses reveal that a significant component of the productivity gains persist after an establishment ceases to be collocated, suggesting that proximity to other establishments owned by the same parent firm facilitates the transfer of knowledge.

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