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Cluster :  Health Applications

Session Information  : Wednesday Nov 04, 08:00 - 09:30

Title:  Data-driven Healthcare Operations
Chair: Muge Capan,Value Institue, Christiana Care Health System, 4755 Ogletown-Stanton Road, John H. Ammon Medical Education Center, Newark DE 19718, United States of America, Muge.Capan@ChristianaCare.org

Abstract Details

Title: Determining an Optimal Schedule for Pre-mixing Chemotherapy Drugs
 Presenting Author: Donald Richardson,University of Michigan, Ann Arbor MI, donalric@umich.edu
 Co-Author: Amy Cohn,University of Michigan, IOE 1205 Beal Ave., Ann Arbor, United States of America, amycohn@umich.edu
 
Abstract: In collaboration with the University of Michigan Comprehensive Cancer Center, we have developed a data-driven, optimization-based approach to improving the timeliness of drug preparation for chemotherapy infusion patients while reducing staff workload and improving resource utilization. We compare the results from both static and dynamic decision policies to determine the optimal schedule for pre-mixing chemotherapy drugs at the cancer center.
  
Title: Using Text Analytics to Identify Labor and Delivery Sentiment from the Internet and Social Media
 Presenting Author: Karen Hicklin,Phd Student, North Carolina State University, 111 Lampe Drive, Campus Box 7906, Raleigh NC 27695, United States of America, kthickli@ncsu.edu
 Co-Author: Fay Cobb Payton,Associate Professor, North Carolina State University, COM, Box 7229, Raleigh NC, United States of America, fcpayton@ncsu.edu
 Julie Ivy,North Carolina State University, 111 Lampe Drive, Raleigh NC 27695-7906, United States of America, jsivy@ncsu.edu
 Vidyadhar Kulkarni,Professor, UNC Chapel Hill, 322 Hanes Hall, UNC Campus, Chapel Hill NC 27599, United States of America, vkulkarn@email.unc.edu
 Evan Myers,Duke University School of Medicine, 244 Baker House, Durham NC 27710, United States of America, evan.myers@duke.edu
 Meera Viswanathan,RTI International, 3040 Cornwallis Road, PO Box 12194, Research Triangle Park NC 27709-2194, United States of America, viswanathan@rti.org
 Michael Wallis,Analytical Consultant, SAS Institute Inc., SAS Campus Drive, Cary NC 27513, United States of America, Michael.Wallis@sas.com
 
Abstract: Pregnant women often seek counsel online from doctors, midwives, experienced and other expectant mothers to understand if their experience lines up with that of others and to seek opinions, suggestions and recommendations. We use text analytics to identify key attributes and preferences for women from internet data to identify important attributes that influence patient perceptions in regards to the birth experience that can be used as input parameters to inform delivery mode decision models.
  
Title: Data-driven and Analytical Approaches to Falls Injury Prediction and Rescue Resources Allocation
 Presenting Author: Tze Chiam,Associate Director, Research Informatics, Christiana Care Health Systems, 4755 Ogletown-Stanton Road, Newark DE 19718, United States of America, Tze.C.Chiam@ChristianaCare.org
 Co-Author: Bailey Ingraham Lopresto,Christiana Care Health Systems, 4755 Ogletown-Stanton Road, Newark DE 19718, United States of America, BIngrahamLopresto@ChristianaCare.org
 Kristen Miller,Christiana Care Health Systems, 4755 Ogletown-Stanton Road, Newark DE 19718, United States of America, KrMiller@christianacare.org
 
Abstract: As an effort to improve patient safety, Christiana Care Health Systems embarked on work to evaluate current rescue strategies for patient fall events. This study investigates the use of age, bone density, coagulation, surgery and fall type to identify patients at high risk for injury due to falls and the appropriate responses based on these criteria. A discrete-event simulation is used to evaluate rescue strategies that yield fastest response time while minimizing interruptions to the system.
  
Title: Nurse Scheduling Optimization in the Neonatal Intensive Care Unit
 Presenting Author: Muge Capan,Value Institue, Christiana Care Health System, 4755 Ogletown-Stanton Road, John H. Ammon Medical Education Center, Newark DE 19718, United States of America, Muge.Capan@ChristianaCare.org
 Co-Author: Eric V. Jackson,Value Institute, Christiana Care Health System, Newark DE 19718, United States of America, EJackson@ChristianaCare.org
 Robert Locke,Division of Neonatology, Christiana Care Health System, Newark DE 19718, United States of America, RLocke@Christianacare.org
 
Abstract: Nurse scheduling is the process of assigning nurses to work shifts. A suboptimal schedule can impact the staffing ratios, nurses’ well-being, job satisfaction, and quality of care. Nurse scheduling in the Neonatal Intensive Care Unit is particularly challenging due to the complexity of care environment and required nursing skillset. We present a multi-objective optimization approach to allocate nurses to shifts while considering institutional requirements, workload fairness and nurses' health.