2015 Informs Annual Meeting

TC41

INFORMS Philadelphia – 2015

2 - The Effect of Price Ending on Consumer Behavior Yoshiyuki Okuse, Professor, Senshu University, 2-1-1, Higashi-Mita, Tama-Ku, Kawasaki, 2148580, Japan, okuse@isc.senshu-u.ac.jp

3 - Dynamic New Patient Consult Scheduling for Medical Oncology Antoine Sauré, University of British Columbia, 2053 Main Mall, Vancouver, BC, V6T 1Z2, Canada, antoine.saure@sauder.ubc.ca, Claire Ma, Jonathan Patrick, Martin Puterman Motivated by an increasing demand for cancer care and long waits for new patient consults, we undertook a study of medical oncology scheduling practices at a regional cancer center. As a result, we formulated and approximately solved a discounted infinite-horizon MDP model that seeks to identify policies for allocating oncologist consultation time to incoming new patients, while reducing waits in a cost-effective manner. The benefits from the proposed method are evaluated using simulation. 4 - Optimal Issuing Policies for Hospital Blood Inventory Alireza Sabouri, Assistant Professor, Haskayne School of Business, University of Calgary, Calgary, AB, Canada, alireza.sabouri@haskayne.ucalgary.ca, Steven Shechter, Tim Huh We propose a model for allocating red blood cells for transfusion to patients, which is motivated by recent evidence suggesting that transfusing older blood is associated with increased mortality rate. We study the properties of blood issuance policies that balance the trade-off between “quality” measured in average age of blood transfused and “efficiency” measured in the amount of shortage. Based on our analysis, we design efficient issuance policies and evaluate their performance. TC42 42-Room 102B, CC Joint Session MSOM-Health/HAS: Workarounds, Errors and Interruptions in Healthcare Sponsor: Manufacturing & Service Oper Mgmt/Healthcare Operations Sponsored Session Chair: Anita Tucker, Associate Professor, Brandeis University, 415 South Street, Waltham, MA, 02453, United States of America, atucker@brandeis.edu 1 - Hospital Operations and Patient Satisfaction Sarah Zheng, Doctoral Candidate, Boston University, 16 Gold Star We look at the impact of operations performance on service quality. Our study site is a nationally-ranked major hospital in the Boston area. Service quality is measured by both medical errors and patient satisfaction. Daily operations are measured by performance in about a dozen of its supporting services. We attempt to answer questions such as: What are the operational drivers of medical errors? To what extent does higher operations performance lead to higher patient satisfaction? 2 - Medical Errors in the Healthcare Delivery: An Econometric Analysis of the Operational Sources Sriram Thirumalai, Associate Professor, Texas Christian University, Neeley School of Business, TCU Box 298530, Fort Worth, TX, 76116, United States of America, s.thirumalai@tcu.edu Medical errors in the delivery of care is a significant cause of concern in healthcare supply chains. Based on an econometric analysis of a panel dataset on medical errors, this study serves to examine the sources of medical errors and error mitigation in the delivery of care in hospitals. 3 - The Impact of Workarounds on Patient Falls and Pressure Ulcers Anita Tucker, Associate Professor, Brandeis University, 415 South Street, Waltham, MA, 02453, United States of America, atucker@brandeis.edu We present results from a survey of 100 medical/surgical nursing units that tests the impact of workarounds and operational failures on nursing sensitive patient outcomes, such as pressure ulcers, falls, patient satisfaction and infections. 4 - Batching of CSP Medication in In-Hospital Pharmacy Vera Tilson, Simon School of Business, University of Rochester, Rochester, NY, 14627, United States of America, vera.tilson@simon.rochester.edu, Gregory Dobson, David Tilson Hospital pharmacy departments batch production of Compounded Sterile Products (CSP). A change in a patient’s condition can lead to change or cancellation of physician’s orders. A very large proportion of orders are cancelled, which leads to waste custom compounded medication. We create an integer programming model to help pharmacies plan batch production trading off the cost of waste and the cost of employee labor. Rd., Cambridge, MA, 02140, United States of America, xinzheng@bu.edu, Amy McLaughlin, Aubrey Podell, Anita Tucker, Z. Justin Ren

In the area of pricing research, a lot of researches on price endings have been developed. The purpose of this research is to specify the effect of price endings on consumer behavior in Japan. 3 - I Like using My Mobile Apps But… A Study of Post Consumption Appraisal Anubha Mishra, Assistant Professor Of Marketing, University of Idaho, 875 Perimeter Dr, Moscow, ID, 83844, United States of America, amishra@uidaho.edu The study of mobile app consumption suggested three distinct dimensions. Users’ evaluation of control, freedom, newness, assimilation, and fulfillment of need from apps was captured by Perceived Benefits; Perceived Apprehension, covered chaos, enslavement, obsolesce, isolation, and creation of needs and Perceived Obscurity, examined ambiguity. Perceived usefulness positively influenced all dimensions indicating that while apps may be perceived as helpful, it can also create isolation. 4 - Increasing User Engagement with Mobile Analytics Chaitanya Sagar, Chief Executive Officer, Perceptive Analytics, 353 West 48th Street, New York, NY, 10036, United States of America, cs@perceptive-analytics.com Mobile represents a tectonic platform shift with great opportunities and challenges. 80% of users do not return to an app after the first day of downloading it. 80% of total app revenue is ‘in-app’ purchases - so unless an app can engage users, it cannot generate significant revenue. Add to that, top 20% apps generate 97% of the revenue making fierce competition among 1.2 million apps. I focus on the heart of this problem increasing engagement with users specifically using push-notifications. 5 - Maximum Entropy Models of Individual Choice Robert Bordley, Expert Systems Engr Professional, Booz-Allen- Hamilton, 525 Choice Court, Troy, MI, 48085, United States of America, Bordley_Robert@bah.com, Ehsan Soofi Many forecasts are based on economic models of individual choice. But these models assume actual individual choice is rational, an assumption which some viewed as having been refuted. To avoid making this assumption, this paper shows that maximum entropy models can approximate general discrete choice models. This paper also shows how to parameterize such models in order to use them for forecasting. TC41 41-Room 102A, CC Joint Session MSOM-Health/HAS: Healthcare Operations Sponsor: Manufacturing & Service Oper Mgmt/Healthcare Operations Sponsored Session Chair: Alireza Sabouri, Assistant Professor, Haskayne School of Business, University of Calgary, Calgary, AB, Canada, alireza.sabouri@haskayne.ucalgary.ca 1 - A Queueing Model for Liver Transplant Waiting List Process Zinan Yi, Operations Research, North Carolina State University, Raleigh, NC, United States of America, zyi@ncsu.edu, Maria Mayorga, Stephanie Wheeler, Sidney Barritt, Eric Orman Liver transplant is the only therapy for patients with end stage liver disease. The composition and dynamics of the waiting list are the interest of both patients and doctors. In this paper, we used the United Network for Organ Sharing and Organ Procurement and Transplantation Network database to develop a queueing model for the waiting list population. Using the model, we will predict future waiting list and other characteristics. 2 - Investigating Steroid Withdrawal Strategies for Kidney Transplant Recipients Yann Ferrand, Assistant Professor, Clemson University, 100 Sirrine Hall, Clemson, SC, 29634, United States of America, yferran@clemson.edu, Vibha Desai, Christina Kelton, Teresa Cavanaugh, Jaime Caro, Jens Goeble, Pamela 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.

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