Focus on Healthcare
INFORMS Focus on... collections bring together articles that address similar topics, practices, or regions from all the INFORMS journals. The collection you are about to read is entitled "Focus on Healthcare." The 16 articles in this index represents only a sampling, from 8 of INFORMS 12 journals, on the successful application of operations research to the field of Healthcare. Each article has been specially selected from INFORMS suite of highly authoritative journals to provide a small representation of the breath and depth of our content in this area.
INFORMS would like to thank Ritu Agarwal, University of Maryland, and Brian Denton, North Carolina State University, for assisting us in reviewing this collection. If you would like to submit an idea for a Focus on... or if you have suggestions for articles that should be included in a particular collection, please contact INFORMS manager of publications.
While the abstracts are available to all, the full texts can only be accessed by subscriptions or pay per view.
Please enjoy this collection. We would very much like to have your comments about the overall index, individual articles, or your thoughts about additional collections that INFORMS can develop.
______________________________________________________
— Research Commentary — The Digital Transformation of Healthcare: Current Status and the Road Ahead (Ritu Agarwal University of Maryland, Guodong (Gordon) Gao University of Maryland, Catherine DesRoches Massachusetts General Hospital, Ashish K. Jha Harvard School of Public Health), Information Systems Research, 21(4) (2010), pp. 796–809
Describes efforts toward the digitization of a health-care system as policy makers across the globe look to information technology (IT) as a means of making health-care systems safer, more affordable, and more accessible
— Social Contagion and Information Technology Diffusion: The Adoption of Electronic Medical Records in U.S. Hospitals (Corey M. Angst University of Notre Dame, Ritu Agarwal, University of Maryland, V. Sambamurthy Michigan State University, Ken Kelley University of Notre Dame), Management Science, 56 (8) (2010), pp. 1219–1241
Use of a social contagion lens to study the dynamic, temporal process of the diffusion of electronic medical records in the population of U.S. hospitals
— Division of Labor in Medical Office Practices (Gregory Dobson University of Rochester, Edieal Pinker University of Rochester, R. Lawrence Van Horn Vanderbilt University), Manufacturing & Service Operations Management (M&SOM), 11(3) (2009), pp. 525–537
Examination of the staffing, division of labor, and resulting profitability of primary care physician practices
— The Impact of Automation of Systems on Medical Errors: Evidence from Field Research * (Ravi Aron Johns Hopkins University, Shantanu Dutta University of Southern California, Ramkumar Janakiraman Texas A&M University, Praveen A. Pathak University of Florida), Information Systems Research, * published online in Articles in Advance, April 8, 2011
An investigation of data from multiple wards from two hospitals spanning a three-year period to focusing on the impact of automation of the core error prevention functions in hospitals on medical error rates.
— A Health-Status Index and its Application to Health-Services Outcomes (S. Fanshel, Ph.D. Fairleigh Dickinson University, J. W. Bush, M.D. New York University), Operations Research, 18 (6) (2010), pp. 1021–1066
Explores the relation between health program output and modern decision theory for program planning, and shows how these analytical tools are useful for fitting the results of the study into larger conceptual frameworks.
— Operating Room Pooling and Parallel Surgery Processing Under Uncertainty (Sakine Batun University of Pittsburgh, Brian T. Denton North Carolina State University, Todd R. Huschka Mayo Clinic, Andrew J. Schaefer University of Pittsburgh) INFORM Journal on Computing, 23(2) (2011) pp.220–237
Presents a novel two-stage stochastic mixed-integer programming model to minimize total expected operating cost given that scheduling decisions are made before the resolution of uncertainty in surgery durations.
— OR Practice—Efficient Short-Term Allocation and Reallocation of Patients to Floors of a Hospital During Demand Surges (Steven Thompson University of Richmond, Manuel Nunez University of Connecticut, Robert Garfinkel University of Connecticut, Matthew D. Dean University of New Orleans), Operations Research, 57 (2) (2009), pp. 261–273
Many hospitals face the problem of insufficient capacity to meet demand for inpatient beds, especially during demand surges. A solution to the problem is to proactively transfer patients between floors in anticipation of a demand surge.
— Optimal Allocation of Surgery Blocks to Operating Rooms Under Uncertainty (Brian T. Denton North Carolina State University, Andrew J. Miller INRIA Bordeaux Sud-Ouest, Hari J. Balasubramanian University of Massachusetts, Todd R. Huschka Mayo Clinic), Operations Research, 58 (4) (2010), pp. 802–816
Details stochastic optimization models for the assignment of surgeries to ORs on a given day of surgery. The allocation of surgeries to operating rooms (ORs) is a challenging combinatorial optimization problem.
— Dynamic Multipriority Patient Scheduling for a Diagnostic Resource (Jonathan Patrick University of Ottawa, Martin L. Puterman University of British Columbia, Maurice Queyranne University of British Columbia), Operations Research, 56 (6) (2008), pp. 1507-1525
Present a method to dynamically schedule patients with different priorities for a diagnostic facility in a public health-care setting. Rather than maximizing revenue, the challenge facing is to dynamically allocate available capacity to incoming demand to achieve wait-time targets cost-effectively.
— Dynamic Scheduling of Outpatient Appointments Under Patient No-Shows and Cancellations (Nan Liu University of North Carolina at Chapel Hill, Serhan Ziya University of North Carolina at Chapel Hill, Vidyadhar G. Kulkarni University of North Carolina at Chapel Hill), Manufacturing & Service Operations Management (M&SOM), 12 (2) (2010), pp. 347–364
Develops a framework and proposes heuristic dynamic policies for scheduling patient appointments, taking into account the fact that patients may cancel or not show up for their appointments.
— Reducing Delays for Medical Appointments: A Queueing Approach (Linda V. Green Columbia University, Sergei Savin Columbia University), Operations Research, 56 (6) (2008), pp. 1526-1538
Conceptualizes an appointment system as a single-server queueing system in which customers who are about to enter service have a state-dependent probability of not being served and may rejoin the queue. The results demonstrate the usefulness of models to provide guidance on identifying patient panel sizes that are to implement a policy of "advanced access."
— Operating Room Manager Game (Erwin Hans University of Twente, Tim Nieberg University of Bonn), INFORMS Transactions on Education, 8 (1) (2007), pp. 25–36
Reports on the "Operating Room Manager Game,'' developed to give insight into managing a large hospital's OR department at various levels of control, and the difficulties of applying OR/MS techniques in healthcare.
— Cardinal Scales for Health Evaluation (Charles M. Harvey University of Houston, Lars Peter Østerdal University of Copenhagen), Decision Analysis, 7 (3) (2010), pp. 256–281
Policy studies often evaluate health for an individual or for a population by using measurement scales that are ordinal scales or expected-utility scales. This paper develops scales of a different type, commonly called cardinal scales, that measure changes in health.
— Utility Functions for Life Years and Health Status (Joseph S. Pliskin Tel-Aviv University, Donald S. Shepard Harvard School of Public Health, Milton C. Weinstein Harvard School of Public Health), Operations Research, 28 (1) (1980), pp. 206–224
Multiattribute utility theory is used to suggest a form for a utility function over life years and health status. This analysis considers two diseases—coronary artery disease and chronic kidney disease—in which the choice of treatment may depend on the patient's tradeoff between these attributes.
— A Simulation Model to Compare Strategies for the Reduction of Health-Care–Associated Infections (Reidar Hagtvedt University of Alberta, Paul Griffin Georgia Institute of Technology, Pnar Keskinocak Georgia Institute of Technology, Rebecca Roberts Cook County Hospital), Interfaces, 39 (3) (2009), pp. 256–270
Pursuit of a strategy to combat health-care–associated infections (HAIs) and a study on a systems-level approach to infection-control procedures required to contain health-care–associated infections.
— Helping Men Decide About Scheduling a Prostate Cancer Screening Exam (Matthew Liberatore Villanova University, Robert Nydick Villanova University, Constantine Daskalakis Thomas Jefferson University, Elisabeth Kunkel Thomas Jefferson University, James Cocroft Thomas Jefferson University, Ronald Myers Thomas Jefferson University), Interfaces, 39 (3) (2009), pp. 209–217
Reports on the application of decision counseling based on the analytic hierarchy process (AHP) to assist men in deciding whether or not to schedule a prostate cancer screening exam.
