2016 INFORMS Annual Meeting Program

WE21

INFORMS Nashville – 2016

WE22 107B-MCC Joint Session MSOM-HC/HAS: Modeling and Optimization for Organ Allocation and Donation Networks Sponsored: Health Applications Sponsored Session Chair: Murat Kurt, Merck Research Labs, 351 N. Sumneytown Pike, North Wales, PA, 19454, United States, murat.kurt7@gmail.com Co-Chair: David Kaufman, Assistant Professor, University of Michigan- Dearborn, 19000 Hubbard Dr, Dearborn, MI, 48126, United States, davidlk@umich.edu 1 - Designing an Efficient And Fair Heart Allocation Rule For Transplantation Farhad Hasankhani, Clemson University, 278 Freeman Hall, Clemson, SC, 29634, United States, fhasank@g.clemson.edu, Amin Khademi The optimal allocation of limited donated hearts to patients on the waiting list is one of the top priorities in heart transplantation management. To design an efficient and fair system for allocating donor hearts to patients waiting for transplantation, we model the waiting list as a fluid model of overloaded queues. The fluid model is an optimal control problem with vector valued state variable defined as number of patients waiting for transplantation in each class and control variable defined as number of hearts to be allocated to patients of each class. 2 - Cherrypicking Kidneys And Patients: Incentives In Transplant Centers Mazhar Arikan, University of Kansas, 931 Drum Dr, Lawrence, KS, 66049, United States, mazhararikan@hotmail.com, Baris Ata, Rodney Parker In 2007 the Centers for Medicare and Medicaid Services implemented a set of regulations for transplant centers. These rules evaluate transplant centers based on one-year patient and organ survival rates post transplantation. Using actual transplant data, we empirically analyze some potential unintended consequences of these regulations such that more risk averse centers choose healthier patients and higher quality organs to transplant. 3 - Modeling Of The United States Liver Allocation System Policy To We propose and study a DSA-centered linking approach for organ sharing. This approach was tested in and out-of-sample by using different demand generation procedures. We show that, under suitable conditions, the known redistricting and concentric circle approaches for organ sharing are retrievable from our more general modeling framework. We will present results comparing the proposed approach with alternatives. 4 - Redesigning The National Network For Deceased Donor Organ Extraction In The Netherlands Joris van de Klundert, Erasmus University Rotterdam, vandeklundert@bmg.eur.nl, Kristiaan Michel Glorie, Thije Van Barneveld, Sylvia Elkhuizen, Kirsten Ooms End Stage Renal Disease is a fatal condition, for which a choice of costly treatment exists. Kidney transplantation is the most cost-effective treatment. In The Netherlands, kidney extraction for transplantation is nationally coordinated to ensure high quality transplantation. This requires responsive deployment of highly specialized teams, which forms a costly service process in itself. In this talk, we consider the present regional structure and operating mode, and consider the problem of finding improved structures and operating procedures. We present results of the simulation analysis, and consider practical requirements taken into account in the implementation which starts in 2017. Reduce Disparity Using Novel Approaches Sanjay Mehrotra, Northwestern University, mehrotra@northwestern.edu, Vikram Kilambi

2 - Determinants Of Meaningful Usage Of Health Information Technology Jingyun Li, Assistant Professor, California State University - Stanislaus, 1 University Circle, Turlock, CA, 95382, United States, jli9@csustan.edu, Indranil R Bardhan, Steves Ring Meaningful use (MU) is a new, government-funded initiative to improve health care system via adoption and usage of HIT. The first stage of MU focuses on capturing and sharing of electronic patient health information. In this study, we explore the characteristics of hospitals that are likely to be associated with achievement of MU. Using archival, hospital-level data gathered from several sources, we observe that hospitals with greater IT leadership are more likely to achieve meaningful use. We also observe that standalone hospitals are less likely to achieve meaningful use. Our findings indicate that hospitals with greater levels of EMR support are also more likely to achieve meaningful use. WE21 107A-MCC Joint Session MSOM-HC/HAS: Healthcare Operations Sponsored: Health Applications Sponsored Session Chair: Tolga Tezcan, London Business School, Regent’s Park, O, London, TX, NW1 4SA, United Kingdom, ttezcan@london.edu 1 - The Role Of Non-clinical Workforce On Patient Service: Evidence From NHS Helpline Although non-clinical workers are vital in many healthcare delivery settings, their impact on efficiency and quality of patient service has not been examined in the OM literature. In this study, making use of a novel dataset based on NHS’s 111 non-emergency helpline in England, we quantify and demonstrate trade-offs associated with employing non-clinical personnel in delivering patient service. Our results indicate that while non-clinical workforce increases the efficiency of patient service by reducing abandoned calls, it may lead to new inefficiencies through misuse of critical resources (i.e., unnecessary ambulance dispatches) and it may reduce the quality outcome of the patient service. 2 - Physiology-based Anticipative Icu Management Yasin Ulukus, University of Pittsburgh, yasin.ulukus@gmail.com, Guodong Pang, Andrew J Schaefer, Gilles Clermont The efficient operation of ICUs is crucial to providing high quality of care while controlling costs. We consider transfer operations from an ICU to a downstream unit. In current practice, downstream beds are requested only when a patient is clinically ready for transfer. We investigate anticipative bed requests that can be made before a patient is clinically ready for transfer, and show that such policy combined with effective use of clinical markers can significantly improve the system performance. We present a Markov Decision Process (MDP) model and solve it via approximations. We further investigate the sensitivity of policy change upon cost parameter estimation errors via robust models. 3 - New Empirical Evidence For The Clinical Effectiveness And Process Implications Of Managing Migraine Care Via Telemedicine: Interim Results Abraham Seidmann, University of Rochester, Simon Business School, Dir of OR Dept, Rochester, NY, 14627, United States, avi.seidmann@simon.rochester.edu, Balaraman Rajan, Deborah Friedman Telemedicine has been proved to increase access to patients and reduce travel burden. In the context of an ongoing pilot study of telemedicine for individuals with migraine, we completed in-person baseline assessments and follow-up visits via telemedicine to test the hypothesis that follow-up care delivered by telemedicine is as effective as with in-office visits. We then investigate ways in which telemedicine could add economic value to patients through convenience and better compliance, and benefit specialists through a higher productivity. 4 - Adaptive Monitoring Of Depression Treatment Population: A Data-driven Approach Ying Lin, University of Washington, linyeliana.ie@gmail.com, Shan Liu, Shuai Huang 30 million Americans use antidepressant medication. Inadequate follow-up monitoring has been identified as a main challenge in managing the depression patient population. We developed a decision support algorithm to create patient- specific adaptive monitoring schedules and dynamically allocate limited sensing resources to detect high risk individuals of severe depression. The proposed method integrates depression trajectory modeling, prognosis, and selective sensing into a unified framework. The effectiveness of the proposed method is demonstrated on a depression treatment population. Bilal Gokpinar, UCL, London, United Kingdom, b.gokpinar@ucl.ac.uk, Emmanouil Avgerinos

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