Steven M. Thompson

Improving disaster response efforts with decision support systems

As evidenced by Hurricane Katrina in August, 2005, disaster response efforts are hindered by a lack of coordination, poor information flows, and the inability of disaster response managers to validate and process relevant information and make decisions in a timely fashion. A number of factors contribute to current lacklustre response efforts. Some are inherent to the complex, rapidly changing decision-making environments that characterise most disaster response settings. Others reflect systematic flaws in how decisions are made within the organisational hierarchies of the many agencies involved in a disaster response. Slow, ineffective strategies for gathering, processing, and analysing data can also play a role. Information technology, specifically decision support systems, can be used to reduce the time needed to make crucial decisions regarding task assignment and resource allocation. Decision support systems can also be used to guide longer-term decisions involving resource acquisition as well as for training and the evaluation of command and control capability.

OR Practice---Efficient Short-Term Allocation and Reallocation of Patients to Floors of a Hospital During Demand Surges

Many hospitals face the problem of insufficient capacity to meet demand for inpatient beds, especially during demand surges. This results in quality degradation of patient care due to large delays from admission time to the hospital until arrival at a floor. In addition, there is loss of revenue because of the inability to provide service to potential patients. A solution to the problem is to proactively transfer patients between floors in anticipation of a demand surge. Optimal reallocation poses an extraordinarily complex problem that can be modeled as a finite-horizon Markov decision process. Based on the optimization model, a decision-support system has been developed and implemented at Windham Hospital in Willimantic, Connecticut. Projections from an initial trial period indicate very significant financial gains of about 1% of their total revenue, with no negative impact on any standard quality of care or staffing effectiveness indicators. In addition, the hospital showed a marked improvement in quality of care because of a resulting decrease of almost 50% in the average time that an admitted patient has to wait from admission until being transferred to a floor.

Improving patient flow in a hospital through dynamic allocation of cardiac diagnostic testing time slots

A cardiac diagnostic testing center (CDTC) makes real-time scheduling decisions that impact the use of its resources and the availability of telemetry-equipped beds within a hospital. Both inpatients and outpatients are frequent users of CDTC resources, and physicians prescribe one of several single-phase or multiple-phase test protocols. This complex online decision-making environment is modeled as a finite-horizon, discrete-time Markov decision process (MDP), but the growth of the state space motivates the introduction of a fast heuristic for real-time decision support. We therefore introduce a dynamic network scheduling tool which is both more flexible and more robust, making it applicable to the various configurations that may be found in practically any CDTC. We evaluate this new method computationally using simulation, comparing it to both an MDP model for small instances, and to the existing operational practice at our partner hospital for more realistic sized problems.

Managing Risks in Multiple Online Auctions: An Options Approach*

The scenario of established business sellers utilizing online auction markets to reach consumers and sell new products is becoming increasingly common. We propose a class of risk management tools, loosely based on the concept of financial options that can be employed by such sellers. While conceptually similar to options in financial markets, we empirically demonstrate that option instruments within auction markets cannot be developed employing similar methodologies, because the fundamental tenets of extant option pricing models do not hold within online auction markets. We provide a framework to analyze the value proposition of options to potential sellers, option-holder behavior implications on auction processes, and seller strategies to write and price options that maximize potential revenues. We then develop an approach that enables a seller to assess the demand for options under different option price and volume scenarios. We compare option prices derived from our approach with those derived from the Black-Scholes model (Black & Scholes, 1973) and discuss the implications of the price differences. Experiments based on actual auction data suggest that options can provide significant benefits under a variety of option-holder behavioral patterns.

Releasing Individually Identifiable Microdata with Privacy Protection Against Stochastic Threat: An Application to Health Information

The ability to collect and disseminate individually identifiable microdata is becoming increasingly important in a number of arenas. This is especially true in health care and national security, where this data is considered vital for a number of public health and safety initiatives. In some cases legislation has been used to establish some standards for limiting the collection of and access to such data. However, all such legislative efforts contain many provisions that allow for access to individually identifiable microdata without the consent of the data subject. Furthermore, although legislation is useful in that penalties are levied for violating the law, these penalties occur after an individuals privacy has been compromised. Such deterrent measures can only serve as disincentives and offer no true protection. This paper considers security issues involved in releasing microdata, including individual identifiers. The threats to the confidentiality of the data subjects come from the users possessing statistical information that relates the revealed microdata to suppressed confidential information. The general strategy is to recode the initial data, in which some subjects are “safe” and some are at risk, into a data set in which no subjects are at risk. We develop a technique that enables the release of individually identifiable microdata in a manner that maximizes the utility of the released data while providing preventive protection of confidential data. Extensive computational results show that the proposed method is practical and viable and that useful data can be released even when the level of risk in the data is high.

Integrated Block Sharing: A Win--Win Strategy for Hospitals and Surgeons

We consider the problem of balancing two competing objectives in the pursuit of efficient management of operating rooms in a hospital: providing surgeons with predictable, reliable access to the operating room and maintaining high utilization of capacity. The common solution to the first problem (in practice) is to grant exclusive “block time,” in which a portion of the week in an operating room is designated to a particular surgeon, barring other surgeons from using this room/time. As a major improvement over this existing approach, we model the possibility of “shared” block time, which need only satisfy capacity constraints in expectation. We reduce the computational difficulty of the resulting NP-hard block-scheduling problem by implementing a column-generation approach and demonstrate the efficacy of this technique using simulation, calibrated to a real hospitals historical data and objectives.Our simulations illustrate substantial benefits to hospitals under a variety of circumstances and demonstrate the advantages of our new approach relative to a benchmark method taken from the recent literature.

A model to support IT infrastructure planning and the allocation of IT governance authority

Information technology (IT) requires a significant investment, involving up to 10.5% of revenue for some firms. Managers responsible for aligning IT investments with their firms strategy seek to minimize technology costs, while ensuring that the IT infrastructure can accommodate increasing utilization, new software applications, and modifications to existing software applications. It becomes more challenging to align IT infrastructure and IT investments with firm strategy when firms operate in multiple geographic markets, because the firm faces different competitive positions and unique challenges in each market. We discussed these challenges with IT executives at four Forbes Global 2000 firms headquartered in Northern Europe. We build on interviews with these executives to develop a discrete-time, finite-horizon Markov decision model to identify the most economically-beneficial IT infrastructure configuration from a set of alternatives. While more flexibility is always better (all else equal) and lower cost is always better (all else equal), our model helps firms evaluate the tradeoff between flexibility and cost given their business strategy and corporate structure. Our model supports firms in the decision process by incorporating their data and allowing firms to include their expectations of how future business conditions may impact the need to make IT changes. Because the model is flexible enough to accept parameters across a range of business strategies and corporate structures, the model can help inform decisions and ensure that design choices are consistent with firm strategy.

Improving the Flow of Patients Through Healthcare Organizations

Healthcare organizations face a challenging operational environment characterized by uncertain demand, the need to deliver highly complex and specialized services, and increasing pressure to provide better quality care to more patients at lower total cost. Healthcare organizations invest substantial financial resources into the human, technological, and structural assets needed to provide a wide range of healthcare services. Determining how much capacity is made available, how that capacity is allocated to patients, and how various specialized units in the organization coordinate their activities are important drivers of performance. In particular, healthcare organizations continuously evaluate the flow of patients through the organization as different healthcare services are provided. If patients do not flow smoothly through the healthcare delivery process, either due to inadequate capacity or the inefficient use of capacity, then patient satisfaction and quality of care can suffer. This chapter provides an overview of the concept of patient flow as one measure of the quality and effectiveness of healthcare delivery, examines some of the most significant challenges to improving patient flow, provides an overview of prior operations research related to patient flow, and discusses current factors that are driving future research opportunities.

Transforming the dominant logic of hospitals.

Substantial and sustained change is inevitable for U.S. hospitals, driven by the Medicare and Medicaid cost inflation curve and embodied in regulatory initiatives and reforms. This study explores the conception that evidence-based management is necessary but not sufficient for 21st century success in health care organizations. Success will require challenging and changing the organizations dominant logic, substituting a more transformational style of problem analysis and decision making. In order for evidence-based management decisions to transform organizations, the organizational culture must be ready to adopt transformation changes. The outcomes of this shift in management style are dramatic changes in worker engagement and retention and a reinforcing cycle of performance improvement efforts. We use a series of examples to illustrate changes in the dominant logic and to identify how the combination of evidence-based management and a new dominant logic results in a fundamental and highly productive shift in how problems are framed and solved. We conclude with recommendations for changing the dominant logic--such as visioning, sensemaking, process questioning, getting the right people together, rewarding innovation, and overcoming risk aversion--all necessary for transforming the dominant logic, allowing evidence-based management techniques to flourish.

How Multinational Corporations Use Information Technology to Manage Global Operations

ABSTRACT Despite a generally acknowledged importance of information technology (IT) in enabling global strategy and a broad understanding of the manner in which IT enhances coordination and reduces cost, few studies have focused precisely on how multinational corporations (MNCs) use IT to facilitate globalization. To address this gap in the literature, we conduct a case study across four large MNCs, and use primary data to develop predictive propositions on the characteristics of products, processes, and customers that impact the ways in which MNCs use IT to manage their global operations.