41 research outputs found

    Using RealOpt-POD© to determine staffing capabilities during an infectious disease emergency

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    In the event of an infectious disease emergency, the Allegheny County Health Department (ACHD) may have to open Points-of-Dispensing (PODs) in order to administer life-saving medical countermeasures to the public. Under Centers for Disease Control and Prevention guidelines, local public health agencies are expected to demonstrate their ability to dispense medication or vaccine to everyone in their identified population within 48 hours. ACHD has designated 50 schools as public PODs throughout the county. In the event that all sites are activated, ACHD would need to supplement its workforce in order to provide adequate staffing to meet this capability. ACHD used RealOpt-POD©, a software tool designed to assist public health agencies, to determine optimal resource allocation for PODs, aiding in predicting staffing shortages and establish limitations on dispensing throughput. The public health significance of this project is in planning for infectious disease emergencies. RealOpt-POD© was used to model an influenza outbreak requiring mass vaccination. Information about ACHD’s workforce, including licensures, was inputted into RealOpt-POD©. Data about 548 Medical Reserve Corps (MRC) members was also included to supplement the workforce. RealOpt-POD© took into account whether or not an individual was licensed to give a vaccine. The model estimated the maximum number of people that can be treated with the available workforce within 48 hours at 50 PODs. In addition, RealOpt-POD© projected the minimum number of personnel needed to vaccinate the entire county. With 50 open PODs, the minimum number of workers needed to vaccinate the Allegheny County population (1.2 million) within 48 hours is 3,514. Assuming that 10% of MRC volunteers would assist, an additional 3,110 workers are needed. 45% of these workers should be licensed to give a vaccine. The maximum number of citizens that can be treated without the additional workers is 71,112. With its workforce alone, ACHD will not be able to provide vaccinations to the entire county within 48 hours. These results demonstrate that recruiting medically-oriented individuals should be a priority for the MRC and the ACHD may have to look to alternative staffing pools to ensure the ability to operate all 50 sites

    Optimization models for patient allocation during a pandemic influenza outbreak.

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    Pandemic influenza has been an important public health concern. During the 20th century, three major pandemics of influenza occurred in 1918, 1957, and 1968. The pandemic of 1918 caused 40 to 50 million deaths worldwide and more than 500,000 deaths in the United States. The 1957 pandemic, during a time with much less globalization than now, spread to the U.S. within 4 to 5 months of its origination in China, causing more than 70,000 deaths in the U.S., and the 1968 pandemic spread to the U.S. from Hong Kong within 2 to 3 months, causing 34,000 deaths. Pandemic influenza is considered to be a relatively high probability event, even inevitable by many experts. During a pandemic influenza outbreak, some key preparedness tasks cannot be accomplished by hospitals individually; regional resource allocation, patient redistribution, and use of alternative care sites all require collaboration among hospitals both in planning and in response. The research presented in this dissertation develops optimization models to be used by decision makers (e.g. hospital associations, emergency management agency, etc.) to determine how best to manage medical resources as well as suggest patient allocation among hospitals and alternative healthcare facilities. Both single-objective and multi-objective optimization models are developed to determine the patient allocation and resource allocation among healthcare facilities. The single-objective optimization models are developed to optimize the patient allocation in terms of minimizing the travel distance between patients and healthcare facilities while considering medical resource capacity constraints. During the pandemic, the surge demand most likely would exhaust all the medical resources, at which time the models can help predict the potential resource shortage so an appropriate contingency plan can be developed. If additional resource quantities become available, the models help to determine the best allocation of these resources among healthcare facilities. Various methods are proposed to conduct the sensitivity analysis to help decision makers determine the impact of different level of each type resource on the patient service. The multi-objective optimization model not only considers the objective of minimization of the total travel distance by patients to healthcare facilities, but also considers the minimization of maximum patient travel distance. A case study from Metro Louisville, Kentucky is presented to demonstrate how the models would aid in patient allocation and resource allocation during a pandemic influenza outbreak. A web-based application based on the optimization models developed in this dissertation is presented as an initial tool for decision makers

    Predicting the Impact of Placing Pre-event Pharmaceuticals for Anthrax

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    Finding feasible strategies to distribute antibiotics quickly to the general public in response to an anthrax attack remains a difficult challenge. Among the proposed strategies is the pre-event placement of pharmaceuticals in individual households for use only as directed by public health authorities. These medications (known as “MedKits”) would allow many exposed persons to begin treatment quickly while reducing the number who visit on points of dispensing, the primary distribution strategy. This paper describes a model that estimates the expected number of deaths in an anthrax attack by modeling the logistics of the response and the use of MedKits. The results show that increasing the number of MedKits distributed can reduce the expected number of deaths. When the population has more potential exposures, deploying MedKits is more effective. The MedKits reduce the number of potential exposures who seek prophylaxis, which allows those truly exposed (but without MedKits) to receive medication sooner, which saves lives. Beyond the scenarios considered here, the ability to predict this benefit in other scenarios will be valuable to public health officials who are considering this option

    Examining the feasibility of using a modelling tool to assess resilience across a health-care system and assist with decisions concerning service reconfiguration

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    Changes in medical practice, demographic shifts and financial pressures are all examples of factors that may contribute to demand for periodic changes in the configuration of health services. When reconfiguring a service, health planners often take into account projected demand for services, patient access criteria and budgetary constraints (among other things), but typically give little consideration regarding its resilience to deliver services during and after external disruptions to its capability to deliver. In this paper we discuss a study conducted in response to a direct request from the National Health Service (NHS) Resilience Project within the Department of Health to explore the feasibility of assessing resilience across local services within the NHS and developing a computer software tool to assess resilience of different service reconfigurations. We give an account of the modelling process used, including the analytical framework we developed using both optimisation and heuristic methods, and an illustrative example of usage of a prototype software tool. We also highlight the key lessons that emerged during this project, which may be helpful to OR analysts working on similar projects regarding resilience in the public sector

    Disaster management and its economic implications

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    Das Ziel dieser Arbeit ist es, aktuelle Forschungsschwerpunkte im Bereich des Katastrophenmanagements in der Operational Research Literatur aufzuzeigen. Katastrophenmanagement umfasst in diesem Zusammenhang einerseits Naturkatastrophen wie geophysikalische und hydro-meteorologische Katastrophen, technologische Katastrophen wie industrielle Unfälle, Transportunfälle und sonstige Unfälle, und andererseits die verschiedenen Formen des Terrorismus, allgemeinen Terrorismus sowie Bioterrorismus. Da die Anzahl und das Ausmaß von Katastrophen immer weiter zunehmen ist auch eine immer größere Notwendigkeit für die Entwicklung, den Einsatz und die wirtschaftliche Beurteilung der jeweiligen Strategien gegeben. Der erste Teil dieser Arbeit gibt einen Überblick über die Literatur im Bereich des Katastrophenmanagements und umfasst Simulation, Katastrophenmanagement in Krankenhäusern und die Rolle von Versicherungen im Katastrophenmanagementprozess. Im zweiten Teil wird eine Taxonomie entwickelt, deren Kategorien auf den Modellen und Ergebnissen der Literatur beruhen. Einerseits werden allgemeine Modelleigenschaften wie die Ebene im Katastrophenmanagementprozess, der Modelltyp und die Anwendungsgebiete der Modelle untersucht. Andererseits stellen die Art der Intervention und die Anwendbarkeit für die unterschiedlichen Katastrophenklassen weitere Kategorien der Taxonomie dar. Es wurden 90 Artikel, die beispielhaft für die Forschungsrichtungen im Bereich des Katastrophenmanagements der letzten 25 Jahre stehen, ausgewählt, und entsprechend den jeweiligen Kategorien der Taxonomie zugeordnet. Das Hauptaugenmerk der Taxonomie liegt auf der wirtschaftlichen Analyse, die wirksamkeitsbezogene, ressourcenbezogene und kostenbezogene Parameter umfasst. Es wird gezeigt ob und welche wirtschaftliche Analyse wie beispielsweise die Kosten-Nutzwert- Analyse, die Kosten-Wirksamkeits-Analyse und die Kosten-Nutzen-Analyse angewendet wird um die in den Artikeln beschriebenen Interventionen zu evaluieren. Es wird gezeigt, dass erhebliche Verbesserungen für die verschiedenen Katastrophentypen und in den verschiedenen Situationen erzielt werden können. Eingeschränkte Datenverfügbarkeit schränkt in vielen Fällen die Einsetzbarkeit der Modelle in realen Situationen ein. Im Allgemeinen ist erkennbar, dass Kooperation und Koordination zwischen den beteiligten Einheiten ausschlaggebend für den zeitgerechten und effizienten Einsatz der knappen Ressourcen sind. Oftmals erzielt der gemeinsame Einsatz mehrerer Maßnahme ein deutlich besseres Ergebnis als der Einsatz von lediglich einem einzigen Instrument. Die Taxonomie unterstreicht dass trotz der großen Fülle an Literatur im Bereich des Katastrophenmanagements nur wenige Autoren auf die Kosten-Nutzwert-Analyse, die Kosten-Wirksamkeits-Analyse und die Kosten-Nutzen-Analyse als Hilfsmittel zur wirtschaftlichen Analyse zurückgreifen. In Zukunft, um Interventionen erfolgreich evaluieren zu können oder die beste aus mehreren Interventionen bestimmen zu können wird es immer wichtiger werden, diese Art von wirtschaftlichen Analysen anzuwenden.This thesis intends to demonstrate current research directions in the field of disaster management in the Operational Research literature. Disaster management in this context comprises the management of natural, such as geophysical and hydro-meteorological, and technological disasters, such as industrial accidents, transportation accidents, and miscellaneous accidents, as well as the management of the different terrorism forms, general terrorism and bioterrorism. As the occurrence of disasters is getting more and more frequent and the accumulated loss of these events is getting higher and higher, there is a strong need for the development, implication and economic evaluation of strategies to counter these disasters. In the first part of the thesis, a general overview of the literature is given, including a focus on simulation, disaster management in hospitals, and the role of insurances in the disaster management process. The second part encompasses the taxonomy which focuses on models and outcomes presented in the literature. As a result of the review of the literature, appropriate categories for the disaster management taxonomy are derived. On the one hand, an overview of general model features, i.e., the level of disaster management, model type and methods of application is given. On the other hand, the type of intervention used and the practicability for different disaster types are discussed. 90 papers, illustrative main examples of the research directions of the last 25 years, were selected for deeper investigation and classified according to the main criteria analyzed in the articles. The main focus of the taxonomy lies on the economic analysis, which encompasses effectiveness-related, resource-related, and cost-related parameters and shows the type of economic analysis used in the literature. We analyze whether economic analysis, i.e., costutility, cost-effectiveness, and cost-benefit are used to investigate different interventions and what type of analysis has been chosen by the authors. Policy implications and results show that considerable improvements can be achieved for different disastrous events and in different situations. Limited data availability constrains the outcomes of the models and their applicability to real-world situations. In general, cooperation and coordination of the entities involved are crucial to guarantee timely and efficient assignment of scarce resources. Furthermore, different authors confirm that a combination of various measures often achieves a better outcome than if tools are used autonomously. The taxonomy has underlined that although there exists a vast disaster management literature dealing with various problems related to mitigation, preparedness, response and recovery from disasters, there are only a few authors evaluating the actions taken through economic analyses such cost-utility, cost-effectiveness, or cost-benefit analysis. In the future, to be able to evaluate interventions, or to figure out the most effective intervention among several interventions, it is crucial to stronger rely on the abovementioned economic analyses

    Healthy Iowans 2017-2021 Iowa’s Health Improvement Plan: 2018 Progress Report, July 2018

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    This report documents progress Iowa has made during the first year of implementing Healthy Iowans 2017- 2021, Iowa’s state health improvement plan. It is based on reports received from about 90 partners that have contributed goals, measurable objectives and strategies for protecting and improving the health of Iowans

    2008 October

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    Press releases for October of 2008

    Healthy Iowans: Iowa’s Health Improvement Plan 2017-2021: Taking Action to Improve Health in Iowa, July 2021

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    This report documents progress on measures of Iowa’s health status and shows areas where there is a need for continued concern. A companion report, Taking Action to Improve Health in Iowa, details the work of more than 90 partners that have taken on responsibility for objectives and strategies in the plan
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