Informs Annual Meeting Phoenix 2018

INFORMS Phoenix – 2018

SA56

3 - Revisiting the Role of Collaboration in Creating Breakthrough Inventions Manuel Emilio Sosa, INSEAD, 1 Ayer Rajah Avenue, Singapore, 138676, Singapore, Tian Chan, Jurgen Mihm We use utility and design patent data for 1985-2009 to compare the probability of creating a breakthrough of working alone versus working in a team. Consistent with literature, for utility patents we find that working alone reduces the probability of achieving a breakthrough. Yet this disadvantage of lone inventors disappears for design patents. We theorize and show empirically that the holistic (i.e., nearly non-decomposable) nature of design is a major factor contributing to the relative efficacy of lone designers at achieving breakthroughs. Finally, we show that lone inventors with a large number of past collaborators has improved likelihood of creating breakthroughs and can outperform teams. 4 - Gender Preference for Tech & Competition: Very-Large-Scale Field ExperimentalEvidence from an Internet-of-Things Platform Nilam Kaushik, University College London, Boston, MA, 02115, United States, Kevin Boudreau This paper presents results from a field experiment on 112,000 students and alumni of an American university to understand willingness to participate in working on innovation problems related to a new area of technological innovation and commercialization, the Internet-of-Things. n SA56 West Bldg 101A Operations Analytics in Healthcare Sponsored: Health Applications Sponsored Session Chair: Tolga Tezcan, London Business School, London, NW14SA, United Kingdom 1 - Integrating Prediction Algorithms with Physician Decisions Attempts to use machine learning techniques to create personalized predictions in healthcare are becoming common. Adoption of such methods in practice will require integrating them into the decisionmaking processes of physicians. In this talk we will discuss our attempt to better understand how a mortality prediction algorithm for advanced cancer patients can augment physician predictions and decision making regarding end-of-life care. 2 - Dynamic Server Assignment in Multiclass Queues with Shifts Carri Chan, Columbia Business School, 3022 Broadway, Uris Hall, New York, NY, 10027, United States, Vahid Sarhangian Nurse staffing decisions in emergency departments (EDs) are typically assigned weeks in advance, which can create staffing imbalances as patient demand fluctuates. In this work, we consider the potential benefits of assigning nurses to different areas within an ED at the beginning of each shift. We study the problem of optimal reassignment of nurses to areas by considering a multiclass queueing model of the system. We analyze an associated fluid control problem and use the solution to develop policies that achieve asymptotically optimal performance under fluid-scaling for the original stochastic system. We find this additional flexibility can substantially reduce waiting times for patients. 3 - Joint Patient Selection and Scheduling: Theory and Application in Proton Therapy Ruihao Zhu, MIT, Cambridge, MA, United States, Soroush Saghafian, Nikolaos Trichakis Motivated by the practice of our partner proton therapy center, we develop joint patient selection and scheduling mechanisms. The center has a tight capacity to serve patients, and any patient scheduled beyond the regular capacity incurs an overtime cost. Developing simulations calibrated with data as well as a variety of analytical bounds, we show that an intuitive index policy that takes into account estimations of both class-dependent and time-dependent (a) no-show probabilities, and (b) service durations achieves a good performance. We also shed light on ways to identify the number of patient classes, estimate time-dependent no-show probabilities, and determine patient service durations. 4 - Transfer Rates and Routing of Patients from ICUs to Downstream Units Andrew Schaefer, Rice University, Department of Computational and Applied Mathematics, United States We present a model for determining the transfer rates and routing of patients from intensive care units (ICUs) to downstream units within a hospital. Using a utility maximizing objective, we offer a decomposition approach that allows for an efficient solution algorithm in which each ICU determines its individual transfer rate while a network model determines the specific patient routing. We illustrate the model and solution approach with numerical examples and explore how flexible capacity, unit occupancy, fairness constraints, and network topology play a role in the optimal solution. Junchao Ma, Yale School of Management, Yale School of Management, New Haven, CT, 06520, United States, Edieal J. Pinker

5- A Holistic Data Analytic Approach to Determine Impacts of the Caregiver Advise, Record, Enable (CARE) Act on Reducing Readmission and Mortality Rates among Older Adults Nichalin S. Summerfield, University of Massachusetts Lowell, OIS Department, One University Avenue, Lowell, MA, 01854, United States, Asil Oztekin Family caregivers are the front line of providing post-discharge care to patients and preventing hospital readmissions. CARE Act, enacted in 36 states, allows a patient to designate a caregiver and requires hospitals to provide post-discharge training to the caregivers. In this research, we evaluate the impact of the act by examining hospital 30-day readmission and mortality rates before and after the act implementation in New Jersey. We deploy a data analytic approach on 2013 and 2016 Medicare inpatient claims data of patients 65 years and older. n SA57 West Bldg 101B Innovation in Healthcare Delivery Sponsored: Health Applications Sponsored Session Chair: Kamalini Ramdas, London Business School, London, NW1 4SA, United Kingdom 1 - The Effects of Home Health Visit Length on Hospital Readmission Hummy Song, The Wharton School, University of Pennsylvania, Philadelphia, PA, United States, Elena Andreyeva, Guy David This study uses a novel dataset on home health care visits to quantify the effects of the length of a post-acute home health visit on hospital readmissions for patients with conditions that are subject to readmission penalties under the Hospital Readmission Reduction Program. Using an instrumental variable approach, we find that an extra minute relative to the average length of a patient’s home health visits reduces their readmission likelihood by about 8 percent. 2 - Increasing Patient Engagement Through Shared Medical Appointments Ryan Buell, Harvard Business School, Morgan Hall 429, Boston, MA, 02163, United States, Kamalini Ramdas, Nazli Sonmez Through a randomized control trial, we examine the impact of shared medical appointments (SMAs), in which a group of patients with similar chronic conditions meet with a doctor simultaneously, on levels of patient engagement. Relative to traditional one-on-one care models, we study how SMAs affect engagement levels, both during the appointment (such as making eye contact with the physician, engaging in the proceedings, and asking questions) and after (such as complying with prescribed medications in the home). Although SMAs hold obvious promise for improving the efficiency of healthcare, to the extent that they may lead to increased patient engagement, they may result in improved outcomes as well. 3 - Structural Estimation of Kidney Transplant Candidates’ Quality of Life Scores A. Cem Randa, University of Chicago, Booth School of Business, 5807 S. Woodlawn Avenue, Chicago, IL, 60637, United States, Baris Ata, John J. Friedewald This paper develops a framework for assessing the impact of changes to the deceased-donor kidney allocation policy on the transplant candidates’ organ acceptance behavior, the transplant waitlist, organ availability for dierent patient groups and organ wastage. It advances a fluid model of the transplant waitlist and a dynamic structural model of the transplant candidates’ accept/reject decisions for organ oers. Building on these two models, we also provide an equilibrium framework, enabling counterfactual studies for assessing the (unintended) consequences of policy changes. 4 - Deployment Guidelines for Community Health Workers in Sub - Saharan Africa

Jonas Oddur Jonasson, MIT Sloan School of Management, 30 Memorial Drive, E62-588, Cambridge, MA, 02142, United States, Carri Chan, Sarang Deo, Jeremie Gallien

Community health workers (CHWs) are increasingly important to healthcare delivery in many African countries. Leveraging an extensive dataset featuring time, clinical findings, and GPS information for CHW visits in sub-Saharan Africa, we develop a stochastic model describing the health dynamics of a population served by a time-constrained CHW. We report closed-form solutions quantifying the impact of CHW deployment on public health for a special case and build a heuristic to solve a policy maker s CHW deployment problem.

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