Strategic Management of Operations in the Emergency Department

This study is based on the analysis of field data on the revenues and patient flows that we collected on all adult emergency department (ED) visits to a level‐1 trauma, tertiary referral center. Our objective was to provide researchers in operations a rich overview of the processes, resources, and metrics of financial and operations performance in the ED. We analyze how patients, physicians, hospitals/physician employer groups, and payers are party to the value created and financial workflow of the ED. A waterfall model for professional services revenue is developed that highlights the impacts of changes in processes, resources, scale, complexity, and mix of patients treated in the ED. We also discuss future implications of new compensation models and potential scenarios that will focus upon controlling costs while maximizing population health and patient satisfaction. These models will necessitate re‐engineering of operations in the ED from a strategic perspective. Four major thrusts for selecting the capacity portfolio in the ED operations to align the interests of all the stakeholders are recommended. New avenues for research are also identified.     

The Impact of Variability and Patient Information on Health Care System Performance

In the delivery of health care services, variability in the patient arrival and service processes can cause excessive patient waiting times and poor utilization of facility resources. Based on data collected at a large primary care facility, this paper investigates how several sources of variability affect facility performance. These sources include ancillary tasks performed by the physician, patient punctuality, unscheduled visits to the facility's laboratory or X‐ray services, momentary interruptions of a patient's examination, and examination time variation by patient class. Our results indicate that unscheduled visits to the facility's laboratory or X‐ray services have the largest impact on a physician's idle time. The average patient wait is most affected by how the physician prioritizes completing ancillary tasks, such as telephone calls, relative to examining patients. We also investigate the improvement in system performance offered by using increasing levels of patient information when creating the appointment schedule. We find that the use of policies that sequence patients based on their classification improves system performance by up to 25.5%.     

Sustainable Operations Management

Operations management researchers and practitioners face new challenges in integrating issues of sustainability with their traditional areas of interest. During the past 20 years, there has been growing pressure on businesses to pay more attention to the environmental and resource consequences of the products and services they offer and the processes they deploy. One symptom of this pressure is the movement towards triple bottom line reporting (3BL) concerning the relationship of profit, people, and the planet. The resulting challenges include integrating environmental, health, and safety concerns with green‐product design, lean and green operations, and closed‐loop supply chains. We review these and other “sustainability” themes covered in the first 50 issues of Production and Operations Management and conclude with some thoughts on future research challenges in sustainable operations management.     

Clinic Capacity Management: Planning Treatment Programs that Incorporate Adherence

For infectious diseases like tuberculosis and HIV, treatment adherence plays an important role in treatment effectiveness and epidemic control. Studies of some infectious diseases indicate that patients who live closer to their health facilities maintain higher adherence; however, most models ignore the heterogeneity of patients' adherence. Clinics must balance knowledge about adherence with epidemic growth when creating successful treatment programs. We develop an optimization model that integrates a clinic's capacity decisions with population health outcomes. We find that incorporating adherence into clinic planning models can lead to decisions that significantly improve outcomes. For example, in a realistic case study of the HIV epidemic in Zambia, we find that decision makers who ignore decreasing adherence make suboptimal decisions and overestimate the effectiveness of their treatment programs by as much as 94%. Our model is a first step toward understanding the relationship between adherence and health delivery.     

Using Fairness Models to Improve Equity in Health Delivery Fleet Management

Inefficiency and inequity are two challenges that plague humanitarian operations and health delivery in resource‐limited regions. Increasing capacity in humanitarian and health delivery supply chains is one option that has the potential to improve equity while maintaining efficiency. For example, the nonprofit organization Riders for Health has worked to increase capacity by providing reliable transportation to health workers in rural parts of sub‐Saharan Africa; with more motorcycle hours at their disposal, health workers can perform more outreach to outlying communities. We develop a model using a family of fairness function to quantify the efficiency and equity of health delivery as capacity is increased via development programs. We present optimal resource allocations under utilitarian, proportionally fair, and egalitarian objectives and extend the model to include dual modes of transport and diminishing returns of subsequent outreach visits. Finally, we demonstrate how to apply our model at a regional level to provide support for humanitarian decision makers such as Riders for Health. We use data from the baseline phase of our evaluation trial of Riders for Health in Zambia to quantify efficiency and equity for one real‐world scenario.     

Panel Size and Overbooking Decisions for Appointment‐Based Services under Patient No‐Shows

Many service systems that work with appointments, particularly those in healthcare, suffer from high no‐show rates. While there are many reasons why patients become no‐shows, empirical studies found that the probability of a patient being a no‐show typically increases with the patient's appointment delay, i.e., the time between the call for the appointment and the appointment date. This paper investigates how demand and capacity control decisions should be made while taking this relationship into account. We use stylized single server queueing models to model the appointments scheduled for a provider, and consider two different problems. In the first problem, the service capacity is fixed and the decision variable is the panel size; in the second problem, both the panel size and the service capacity (i.e., overbooking level) are decision variables. The objective in both cases is to maximize some net reward function, which reduces to system throughput for the first problem. We give partial or complete characterizations for the optimal decisions, and use these characterizations to provide insights into how optimal decisions depend on patient's no‐show behavior in regards to their appointment delay. These insights especially provide guidance to service providers who are already engaged in or considering interventions such as sending reminders in order to decrease no‐show probabilities. We find that in addition to the magnitudes of patient show‐up probabilities, patients' sensitivity to incremental delays is an important determinant of how demand and capacity decisions should be adjusted in response to anticipated changes in patients' no‐show behavior.     

Toward an Effective Design of Behavioral Health Care Delivery: An Empirical Analysis of Care for Depression

A criticism of behavioral health care delivery is that it has largely missed the social determinants of behavioral health disorders and their diagnosis. Toward addressing this criticism, this study evaluates the delivery of behavioral health care as a part of primary care operations. Focusing on the treatment of depression, the study results show that: (i) primary care clinics operating in communities with superior social environment characteristics are associated with improved depression outcomes in the short term, and (ii) psychosocial resources (social and emotional support) and the built environment (man‐made resources and infrastructure to support human activity) of primary care clinics are associated with sustaining the improvement in depression outcome in the long term. Centering our attention on IT‐enabled, evidence‐based, and affordable primary care as mechanisms that can enable the integration of behavioral and medical care delivery, the results suggest that IT‐enabled and evidence‐based primary care are associated with improvements in depression outcomes. We also find that the effect of improving the affordability of behavioral health care delivery depends on the community's socioeconomic status. Primary care clinics in socioeconomically disadvantaged communities practicing cost‐containment are associated with improvements in depression outcomes, and, therefore, can contribute toward reducing disparities in behavioral health care delivery. Counter to our original expectations, we find that the effect of evidence‐based care on improvements on depression outcomes increases as the availability of medically trained behavioral health care specialists practicing in a community increases lending support to concerns that primary care clinics in resource‐rich communities obtain greater benefit from quality improvement interventions.     

Research Constituents and Authorship Patterns in the Production and Operations Management Journal

The Production and Operations Management Society is the largest professional society dedicated to creating and disseminating knowledge in product and process design, operations, and supply chains for the management of manufacturing and services. Its research journal, Production and Operations Management (POM), covers all topics in the discipline and all research paradigms to serve the entire community. Since its inception in 1992, POM has become recognized as a top tier outlet for operations management research. We identify research institutions in the operations management community that have played major roles in developing the journal based on the research of their faculty members and doctoral graduates. Our findings show that the constituency of the journal reflects the constituency of the society.     

A Retrospective Look at Production and Operations Management Articles on New Product Development

We present a retrospective look at the articles on New Product Development that appeared in the first 50 issues of Production and Operations Management (POM). We discuss some of the strengths and weaknesses of this POM literature stream. This article is not intended to be a literature review or an exhaustive review of the articles. Rather, we seek to identify new opportunities for rigorous and relevant research, research that has the potential of differentiating and enhancing POM within the Operations Management literature.     

Elwood Buffa's Pioneering Contributions to Production and Operations Management

Elwood Spencer Buffa, a pioneer in production and operations management (P/OM), passed away in the summer of 2005, leaving his legacy behind. During his academic career Buffa made lasting contributions to teaching and research of P/OM. We review those contributions and their impact on the evolution of the P/OM discipline.     

Introduction to the Special Issue on Marketing and Operations Management Interfaces and Coordination

In this special issue, the contributing authors address several emerging marketing and operations interface problems and develop innovative approaches for solving them. Specifically, by explicitly modeling active consumer behavior under different pricing schemes, the papers in this special issue examine how firms can coordinate their marketing and operations to improve their competitiveness and profit. The papers also provide insights on how to develop and operate new and innovative market mechanisms.     

Knowledge Creation and Dissemination in Operations and Supply Chain Management

During the last 25 years, the ecosystem of knowledge creation and dissemination in operations and supply chain management has improved remarkably. We now see OM as a vibrant community and an ecosystem in steady state. Yet, there are many opportunities ahead to revitalize our field and to expand our influence. In the spirit of continuous improvement, we propose that we focus our major efforts on accelerating the following four developments: First, having greatly expanded the domain of operations management, we should continue to expand its boundaries. Second, after a visible increase in exploratory studies, our community should accelerate our pursuit of such research. Third, we encourage OM faculty to develop programs that enable Ph.D. students to carry out part of their work in actual organizational settings. Fourth, we should further strengthen our interactions with the business community and create mechanisms to systematically disseminate our research to its members.     

Reducing Surgical Ward Congestion Through Improved Surgical Scheduling and Uncapacitated Simulation

High surgical bed occupancy levels often result in heightened staff stress, frequent surgical cancellations, and long surgical wait times. This congestion is in part attributable to surgical scheduling practices, which often focus on the efficient use of operating rooms but ignore resulting downstream bed utilization. This paper describes a transparent and portable approach to improve scheduling practices, which combines a Monte Carlo simulation model and a mixed integer programming (MIP) model. For a specified surgical schedule, the simulation samples from historical case records and predicts bed requirements assuming no resource constraints. The MIP model complements the simulation model by scheduling both surgeon blocks and patient types to reduce peak bed occupancies. Scheduling guidelines were developed from the optimized schedules to provide surgical planners with a simple and implementable alternative to the MIP model. This approach has been tested and delivered to planners in a health authority in British Columbia, Canada. The models have been used to propose new surgical schedules and to evaluate the impact of proposed system changes on ward congestion.     

On the Risk Management and Risk Governance of Petroleum Operations in the Barents Sea Area

In this article, we discuss issues of risk management and risk governance with respect to petroleum operations in the Barents Sea area. We will focus on the decision problems related to whether or not to open the Barents Sea for petroleum activities in special vulnerable areas. We will explore to what extent the International Risk Governance Council risk governance framework provides valuable insights for and assistance to the decisionmaker and other stakeholders (including the industry and NGOs). The study covers issues related to risk assessment and appraisal, risk acceptance and tolerability, the use of the precautionary principle, risk perception, stakeholder involvement, risk communication, and risk management. The overall aim of the article is to point to areas where the risk governance could have been and can be improved for these and similar decision problems.     

Would Allowing Privately Funded Health Care Reduce Public Waiting Time? Theory and Empirical Evidence from Canadian Joint Replacement Surgery Data

This study develops a theoretical model and then, using Canadian joint replacement surgery data, empirically tests the relationship between government policies that promote privately funded health care and patients’ waiting time in the public health care system. Two policies are tested: one policy allows opt‐out physicians to extra‐bill private patients, and the other provides public subsidies to private patients. We find that both policies are associated with shorter public waiting time, and that the subsidy policy appears to be more effective in waiting time reduction than the extra‐billing policy. Our findings are consistent with a dominant demand‐side effect in that these policies would provide patients an option, and some incentive, to opt out of the public health system, shifting the demand from the public health system to the private care market.     

From knowledge to decision – a case study of sales and operations planning in health care

One of the most important challenges in health care management is balancing resources with fluctuating and uncertain demand. This study examines whether introducing a standardised process for sales and operations planning at a large university hospital improved specialty department managers’ knowledge of planning conditions and if so, whether decisions were made based on this knowledge. Using responses from a survey of 30 specialty department managers at Sahlgrenska University Hospital in Sweden, the analyses indicate that operational knowledge strengthens insights about the needs for strategic decisions, and vice versa. Moreover, knowledge is a necessary, but not sufficient, condition for making decisions at the department level. An overall planning and decision structure is required and should be implemented first at the hospital level to effectively allocate resources.     

基于患者两阶段医疗服务过程的病床资源优化

随着医疗需求的日益增长，供需不平衡的矛盾日益显著，病床资源短缺已经成为制约医疗服务发展的重要因素之一。针对病床资源供需失衡的问题，本文构建患者两阶段医疗服务过程的病床资源优化模型。考虑患者的医疗服务是一个两阶段串联排队过程，第一阶段是强制治疗阶段，第二阶段是康复阶段。在患者排队系统中，服务台总数固定的前提下，本文利用增补变量方法给出了该排队系统的概率等式，通过求解偏微分方程得出系统的状态概率，并推导出医院拒绝患者的概率、平均康复时间等相关指标。考虑部分患者因病床资源不足而无法入院和康复阶段患者提前出院两种风险因素，本文基于排队指标构建多病种间的病床分配模型，再利用动态规划的求解思路得到病床分配的最优解。最后，本文采用2017年卫生统计数据和模拟数据相结合进行数值分析。研究结果表明与传统单阶段模型相比，两阶段模型对不同病种间病床数差别影响显著，并且患者入院率对病床分配影响较大。进一步，基于数值结果给出了医疗管理建议和研究展望。     

Dynamic Policies for Optimal LEO Satellite Launches

Low‐earth orbit satellite (LEO) systems continue to provide mobile communication services. The issue of cost containment in system maintenance is a critical factor for continued operation. Satellite finite life‐times follow a stochastic process, and since satellite replenishment cost is the most significant on‐going cost of operation, finding optimal launch policies is of paramount importance. This paper formulates the satellite launch problem as a Markovian decision model that can be solved using dynamic programming. The policy space of the system is enormous and traditional action space dominance rules do not apply. In order to solve the dynamic program for realistic problem sizes, a novel procedure for limiting the state space considered in the dynamic program is developed. The viability of the proposed solution procedure is demonstrated in example problems using realistic system data. The policies derived by the proposed solution procedure are superior to those currently considered by LEO system operators, and result in substantial annual cost savings.     

Grocery Perishables Management

In this article, we study the joint pricing and inventory control problem for perishables when a retailer does not sell new and old inventory at the same time. At the beginning of a period, the retailer makes replenishment and pricing decisions, and at the end of a period, the retailer decides whether to dispose of ending inventory or carry it forward to the next period. The objective of the retailer is to maximize the long‐run average profit. Assuming zero lead time, we propose an efficient solution approach to the problem, which is also generalized to solve three extensions to the basic model. A feature of the present study is that we consider explicitly the influence of perishability on the demand. Among the insights gathered from the numerical analysis, we find that dynamic pricing aids extending shelf life and when disposal incurs a lower cost, or even a positive salvage value, the retailer is induced to dispose earlier since the benefit of selling new inventory offsets the loss due to disposal. We also observe that the faster the perceived rate of deterioration, the lower the threshold of the ending inventory for disposal. Perhaps a bit counter‐intuitive, maximizing profits does not mean eliminating disposals or expirations.