Graph Matching Based Decision Support Tools For Mitigating Spread Of Infectious Diseases Like H1N1

Diseases like H1N1 can be prevented from becoming a wide spread epidemic through timely detection and containment measures. Similarity of H1N1 symptoms to any common flu and its alarming rate of spread through animals and humans complicate the deployment of such strategies. We use dynamic implementation of graph matching methods to overcome these challenges. Specifically, we formulate a mixed integer programming model (MIP) that analyzes patient symptom data available at hospitals to generate patient graph match scores. Successful matches are then used to update counters that generate alerts to the Public Health Department when the counters surpass the threshold values. Since multiple factors like age, health status, etc., influence vulnerability of exposed population and severity of those already infected, a heuristic that dynamically updates patient graph match scores based on the values of these factors is developed. To better understand the gravity of the situation at hand and achieve timely containment, the rate of infection and size of infected population in a specific region needs to be estimated. To this effect, we propose an algorithm that clusters the hospitals in a region based on the population they serve. Hospitals grouped together affect counters that are local to the population they serve. Analysis of graph match scores and counter values specific to the cluster helps identify the region that needs containment attention and determine the size and severity of infection in that region. We demonstrate the application of our models via a case study on emergency department patients arriving at hospitals in Buffalo, NY

An Empirical Analysis of the Impact of Certificate of Need Law on Utilization of Inpatient Services

We investigate the impact of Certificate of Need (CON) Law and its stringency on Inpatient service utilization measured by hospital occupancy. We show that on average the CON legislation reduces utilization in Inpatient units. Besides, we do not find sufficient statistical evidence to reject the exogenous assumption of CON and its features. Furthermore, we confirm the qualitative nature of these key findings by an analysis featuring Inpatient length of stay (LOS). Other findings include the following: Inpatient utilization is positively related to proportion of females in a state and the proportion of Asian-Americans; a statistically significant positive relationship exists between GDP and utilization and a negative one is noted between utilization and proportion of population on Medicare; a statistically significant positive relationship is noted between population availing ED services in a state and Inpatient utilization; as the number of democratic senators in a state increases, it has a negative impact on utilization of Inpatient services

National security vs. human rights: A game theoretic analysis of the tension between these objectives

We explore why human rights violations take place in the midst of a rebellion. Authoritarian governments may not care for human rights but surprisingly several democratic governments have also condoned such violations. We show that the primary cause of such violations is faulty intelligence. There are two type of defective intelligence that can occur viz., missed alarm and false alarm. We consider each of these cases and determine the optimal human rights standard of the government. We then examine the effect of a decrease in the human rights standard on the probability of quelling the rebellion. In our theoretical model, this effect is indeterminate (i.e. can be positive or negative). We empirically quantify this effect using the case of Armed Forces Special Powers Act in India. Since the probability of quelling the rebellion is not directly observable, we use the magnitude of violence as its indicator. The magnitude of violence should be negatively related to the probability of the government’s success. We find that a lowering of the standard of human rights increases violence (i.e. reduces the chance of quelling the rebellion) and this effect is statistically significant

Espionage and the Optimal Standard of the Customs-Trade Partnership against Terrorism (C-TPAT) Program in Maritime Security

We examine the design of a trusted trader program in the U.S. known as C-TPAT (Customs-Trade Partnership against Terrorism). For this, we consider a game between the government, an importer and a terrorist group. The government provides maritime security using three policies: (i) Standard of the C-TPAT program, that is, the degree of security of the supply chain that is required of a member, (ii) Quality of intelligence about the terrorist group, and (iii) Inspection of Cargo. In equilibrium, the government sets the standard of the program at a level that minimizes congestion. However, the optimal espionage expenditure is less than the level that minimizes congestion. We also endogenously determine the membership size of the program and show that it depends non-monotonically on policies such as the standard of the program or the quality of intelligence. Finally, we examine the impact of parametric changes on these policies

Models for Improving Patient Throughput and Waiting at Hospital Emergency Departments

Background: Overcrowding diminishes Emergency Department (ED) care delivery capabilities. Objectives: We developed a generic methodology to investigate the causes of overcrowding and to identify strategies to resolve them, and applied it in the ED of a hospital participating in the study. Methods: We utilized Discrete Event Simulation (DES) to capture the complex ED operations. Using DES results, we developed parametric models for checking the effectiveness and quantifying the potential gains from various improvement alternatives. We performed a follow-up study to compare the outcomes before and after the model recommendations were put into effect at the hospital participating in the study. Results: Insufficient physicians during peak hours, the slow process of admitting patients to inpatient floors, and laboratory and radiology test turnaround times were identified as the causes of reduced ED throughput. Addition of a physician resulted in an almost 18% reduction in the ED Main discharged patient length of stay. Conclusion: The case study results demonstrated the effectiveness of the generic methodology. The research contributions were validated through statistically significant improvements seen in patient throughput and waiting time at the hospital participating in the study

Civil liberties and terrorism in Middle East, North Africa, Afghanistan, and PakistanNo Title

This article investigates impact of the lack of civil liberties on terrorism in Middle Eastern and North African (MENAP) countries based on terrorism incidents per capita for the period 1998-2010. We control for endogeneity by using oil revenue, military expenditure and under-five mortality rate as instruments and find that we cannot reject the null hypothesis that civil liberties is exogenous. Our findings from exogenous models indicate that an improvement of civil liberties reduces domestic terrorism but not transnational terrorism. Apart from civil liberties, there is also evidence that rule of law decreases domestic terrorism. We also find that political stability reduces transnational terrorism

Efficient Operating Room Redesign through Process Improvement and Optimal Handling of Scheduled and Emergent Surgeries

This article is focused on the benefits of reducing variability and the role of operations research techniques in efficient operating room (OR) redesign through process improvement and optimal management of scheduled and emergent surgeries at hospitals. Issues at a participant hospital are studied which are presented in this article where in the authors develop a three step OR redesign model to address them. Firstly, the process bottlenecks affecting OR performance were identified with the help of a discrete event simulation (DES) model. Once the DES model focusing on the \u27as-is\u27 operations of the OR was built and validated, it was used to evaluate various improvement strategies. Secondly, in order to efficiently deal with unscheduled surgeries, a simulated queuing model was used to determine the number of ORs to be reserved which would help in better managing natural variability. Finally, OR time (with the remaining ORs) was allocated for scheduled surgeries after accommodating various operational constraints including surgeon preferences with the help of a mixed integer programme (MIP) model. The empirical observations and results are presented as well

Evaluating Capacity Options for the North American West Coast Container Ports

As global trade continues to recover from the recent economic recession, US container port congestion experienced in the last decade will likely re-emerge. Yet there is limited research that examines network-wide port capacity in support of solutions for minimizing such congestion. To address this gap, we simulate the US West Coast container port network, quantifying the costs and benefits of different options to better utilize current port capacity across the entire network. We specifically assess both efficiency improvement and operational coordination options on historical and future container volumes. The results demonstrate the strength of efficiency as a means to alleviate future port congestion. However, the results also portray inequitable savings across different stakeholders as well as difficulty among these stakeholders in perceiving actual benefits. We discuss the impacts of these challenges on implementation of the capacity utilization options

Modeling the benefits of cross-training to address the nursing shortage

This paper seeks to offer insight into cross training strategies that could be effective in aiding in alleviating the nurse shortage issue and its potential to negatively impact on patient safety and mortality. We develop optimization models to evaluate the benefits of cross-training, in particular chaining practices, on nurse workforce planning under stochastic demand, and determine the optimal allocation of both regular and cross-trained staff at a minimum cost. We demonstrate the benefits of cross-training in terms of a reduction in the total number of nurses required to satisfy demand across multiple departments as well as from an economic (i.e. overall cost savings) perspective, while simultaneously meeting the hospitals service and quality of care requirements. In particular, the results indicate that cross-training strategies could help with optimal utilization of constrained nursing resources and thereby limit the negative implications of the growing nurse shortage crisis