Towards a Model for Inclusive Healthcare Access post COVID-19

The devastation caused by the COVID-19 pandemic has exposed years of cyclic inequalities faced by disadvantaged and minority communities. Unequal access to healthcare and a lack of financial resources further exacerbates their suffering, especially during a pandemic. In such critical conditions, information technology-based healthcare services can be an efficient way of increasing access to healthcare for these communities. In this paper, we put forward a decision model for guiding the distribution of IT-based healthcare services for racial minorities. We augment the Health Belief Model by adding financial and technology beliefs. We posit that financial inclusion of minority populations increases their ability to access technology and, by extension, IT-based healthcare services. Financial inclusion and the use of secure private technologies like federated learning can indeed enable greater access to healthcare services for minorities. Therefore, we incorporate financial, health, and technology tools to develop a model for equitable delivery of healthcare services and test its applicability in different use-case scenarios. © 2022 IEEE Computer Society. All rights reserved.

Minimizing population health loss due to scarcity in OR capacity: validation of quality of life input.

OBJECTIVES: A previously developed decision model to prioritize surgical procedures in times of scarce surgical capacity used quality of life (QoL) primarily derived from experts in one center. These estimates are key input of the model, and might be more context-dependent than the other input parameters (age, survival). The aim of this study was to validate our model by replicating these QoL estimates. METHODS: The original study estimated QoL of patients in need of commonly performed procedures in live expert-panel meetings. This study replicated this procedure using a web-based Delphi approach in a different hospital. The new QoL scores were compared with the original scores using mixed effects linear regression. The ranking of surgical procedures based on combined QoL values from the validation and original study was compared to the ranking based solely on the original QoL values. RESULTS: The overall mean difference in QoL estimates between the validation study and the original study was - 0.11 (95% CI: -0.12 - -0.10). The model output (DALY/month delay) based on QoL data from both studies was similar to the model output based on the original data only: The Spearman's correlation coefficient between the ranking of all procedures before and after including the new QoL estimates was 0.988. DISCUSSION: Even though the new QoL estimates were systematically lower than the values from the original study, the ranking for urgency based on health loss per unit of time delay of procedures was consistent. This underscores the robustness and generalizability of the decision model for prioritization of surgical procedures.

Not Only for Contact Tracing: Use of Belgium's Contact Tracing App among Young Adults

Many countries developed and deployed contact tracing apps to reduce the spread of the COVID-19 coronavirus. Prior research explored people's intent to install these apps, which is necessary to ensure effectiveness. However, adopting contact tracing apps is not enough on its own, and much less is known about how people actually use these apps. Exploring app use can help us identify additional failures or risk points in the app life cycle. In this study, we conducted 13 semi-structured interviews with young adult users of Belgium's contact-tracing app, Coronalert. The interviews were conducted approximately a year after the onset of the COVID-19 pandemic. Our findings offer potential design directions for addressing issues identified in prior work - such as methods for maintaining long-term use and better integrating with the local health systems - and offer insight into existing design tensions such as the trade-off between maintaining users' privacy (by minimizing the personal data collected) and users' desire to have more information about an exposure incident. We distill from our results and the results of prior work a framework of people's decision points in contact-tracing app use that can serve to motivate careful design of future contact tracing technology. © 2023 Owner/Author.

Decision models on therapies for intensive medicine

Decision support models are crucial in intensive care units as they allow intensivists to make faster and better decisions. The application of optimization models in these areas becomes challenging given its complexity and multidisciplinary nature. The main objective of this study is to use the stochastic Hill Climbing optimization model in order to identify the best medication to treat the Covid Pneumonia problem, considering the top 3 medications administered as well as the cost of treatment. It should be noted that the problem to be analyzed in the optimization model was selected considering that the extracted data is from the time when Covid-19 was ravaging the intensive care units, so it will be the most interesting. The results obtained in this study denote that the n_iterations parameter was crucial in obtaining the optimal solution since all scenarios with this parameter set to a value of 1000 were able to return the optimal solution, unlike the other ones. © 2022 Elsevier B.V.. All rights reserved.

BS Team: Finding Competence Gaps

The academy form competences to work in the routine, without worries, without unknown hazards. The rules and objectives in routine activities are clear and require operational discipline to control the cost of production and product quality. The current educational model does not prepare society and groups for an emergency or even for decisions in a crisis, where resources are scarce mainly because the necessary knowledge about danger and its mechanism of action is lacking. What really happens in the chain event scenario when the danger is unknown? What are the typical models of action of the emergency leader and his team? What are the required actions in crisis management required for a BS type event considering the scarce resources, the high level of stress and the direction of the danger energy? Which models are indicated for the situation of unknown danger and its intense energy flow with high impacts during these events? What is the appropriate mind map of those who lead and execute the actions considering the low level of visibility in the events and the dynamic of geopolitics in the BS scenario where, depending on the preparation for emergency, in case of intense demand for attention and action, possible modifications may occur in the map mental for decisions? This work intends to review the discussions already performed about new concepts and tools to be used in the crisis prevention area. Between this works we will understand the effect of the stress level on emergency decisions valuating human error and observing team response using LODA tool. The Human elements designed in the organizational culture, can stop the high danger energy that can flow from some industries. The principal aspects to be constructed and monitored are technology (risk and complexity);management (leadership and stress);and behavior (cooperation, commitment, competence, and communication). By the other hand, human factors are analyzed to avoid situations which hazard energy carriers during top events, as the effect of cultural aspects to chain reaction until the occurrence of disaster. Decision models for the emergency brigade (leader and team) indicate the motor and cognitive gaps that cause lack of control during contingencies. Finally, the analysis of simulation types, by rotating observation of field simulation allow find the deficiencies of the emergency team in a real situation in the future. The methodology divided in following steps are dynamic: first, rescue the discussions about stress and the BS events and, in second step, recognize the intense hazard energy flow through failure events, antecedents, elements and human factors. In third step, we try to locate the gaps and environmental conflicts influencing losses from accidents. Finally, we assess the current event of covid-19 pandemics to suggest correct emergency preparedness actions in the preparation of leaders and their teams regarding cognitive and motor characteristics in situations of high demand. When comparing the characteristics already described by TALEB about BS with the event COVID-19, we intend to carry out a case study to indicate the possible causes this global impact crisis, or even, understand the technological disaster causes where uncontrolled events from chemical, nuclear, and oil industry begins chain reactions until the disaster. Unfortunately, a Crisis situation can be caused from several intricated dimensions, making difficult the contingency and mitigation actions. © 36th Center for Chemical Process Safety International Conference, CCPS 2021 - Topical Conference at the 2021 AIChE Spring Meeting and 17th Global Congress on Process Safety.

Emergency Decision Model by Combining Preference Relations with Trapezoidal Pythagorean Fuzzy Probabilistic Linguistic Priority Weighted Averaging PROMETHEE Approach

The outbreak of COVID-19 in 2019 has brought greater international attention to emergency decision making and management. Since emergency situations are often uncertain, prevention and control are crucial. For better prevent and control, according to the characteristics of emergency incidents, the paper proposes a new form of linguistic expression trapezoidal Pythagorean fuzzy probabilistic linguistic variables to express decision-making information. Next, the paper develops the operational rules, value index and ambiguity of trapezoidal Pythagorean fuzzy probabilistic linguistic variables. Then, the new trapezoidal Pythagorean fuzzy probabilistic linguistic priority weighted averaging PROMETHEE approach is introduced to aggregate the trapezoidal Pythagorean fuzzy probabilistic linguistic information combining with preference relation. Finally, an emergency decision making case of prevention of infectious diseases analysis illustrate the necessity and effectiveness of this method, the results of comparative and experimental analyses demonstrate that the constructed new trapezoidal Pythagorean fuzzy probabilistic linguistic priority weighted averaging PROMETHEE approach owns better performances in terms of effectiveness and reasonability. © 2022. International Journal of Advanced Computer Science and Applications. All Rights Reserved.

COVID-19 vaccine distribution: exploring strategic alternatives for the greater good

The dire state of the COVID-19 pandemic crisis symbolized the urgency for efficient distribution and administration of vaccines to combat the virus as the most urgent public health service. This paper presents a prototype multi-criteria decision support model based on goal programming that can effectively support vaccination plans for the greater good of society. The optimization goals of the model include minimizing the number of fatalities and risk of spreading the disease, while complying with government health agency’s priority guidelines for vaccination. This study applied the model to a real-world dataset to demonstrate how it can be effectively applied as a decision support tool for vaccine distribution plans and manage future pandemics. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

Using gravity model to make store closing decisions: A data driven approach.

Many studies propose methods for finding the best location for new stores and facilities, but few studies address the store closing problem. As a result of the recent COVID-19 pandemic, many companies have been facing financial issues. In this situation, one of the most common solutions to prevent loss is to downsize by closing one or more chain stores. Such decisions are usually made based on single-store performance; therefore, the under-performing stores are subject to closures. This study first proposes a multiplicative variation of the well-known Huff gravity model and introduces a new attractiveness factor to the model. Then a forward-backward approach is used to train the model and predict customer response and revenue loss after the hypothetical closure of a particular store from a chain. In this research the department stores in New York City are studied using large-scale spatial, mobility, and spending datasets. The case study results suggest that the stores recommended being closed under the proposed model may not always match the single store performance, and emphasizes the fact that the performance of a chain is a result of interaction among the stores rather than a simple sum of their performance considered as isolated and independent units. The proposed approach provides managers and decision-makers with new insights into store closing decisions and will likely reduce revenue loss due to store closures.

Planning the supply of emergency medical products to cope with pandemics

The COVID-19 pandemic exposed inadequate planning in the supply of emergency medical products (EMP) worldwide. In what followed, an exponential growth in EMP demand during the first months of the pandemic proved extremely challenging for manufacturers to adapt to. This put healthcare workers, our first line of defense, in jeopardy and stretched healthcare systems beyond their capacities. Many governments realized the deficiency of their emergency stockpile policies, and as global demand outstripped supply, they struggled to meet their population's basic EMP needs using offshore suppliers. In this work, we present a game theoretical approach for the planning of EMP supplies using a game that models the interaction between governments and private manufacturers to secure such critical supplies in the case of pandemics, while reducing the overall cost to taxpayers, and taking into consideration manufacturers profit objectives. On one hand, a policymaker can decide the strategic stockpile size for EMPs and use subsidies to encourage manufacturers to onshore some or all of their EMP manufacturing capacity to improve their domestic crisis management capabilities in case of a pandemic. On the other hand, private manufactures can evaluate offshoring cost savings compared to subsidies offered by the government on the condition of onshoring production of subsidized products and offering such items to the public at contracted pricing in pandemics. We detail the two models, present a solution to balance the competing objectives, and discuss insights from the model's analysis. © 2021 IISE Annual Conference and Expo 2021. All rights reserved.