Open Data

Open data is freely usable, reusable, or redistributable by anybody, provided there are safeguards in place that protect the data’s integrity and transparency. This book describes how data retrieved from public open data repositories can improve the learning qualities of digital networking, particularly performance and reliability. Chapters address such topics as knowledge extraction, Open Government Data (OGD), public dashboards, intrusion detection, and artificial intelligence in healthcare

COMPREHENSIVE FRAMEWORKS FOR DECISION MAKING SUPPORT IN MEDICAL EQUIPMENT MANAGEMENT

Throughout medical equipment life cycle, hospitals need to take decisions on medical equipment management based upon a set of different criteria. In fact, medical equipment acquisition, preventive maintenance, and replacement are considered the most important phases, accordingly a properly planned management for these issues is considered a key decision of medical equipment management. In this thesis, a set of frameworks were developed regarding acquisition, preventive maintenance, and replacement to improve management process of medical equipment. In practice, quality function deployment was proposed as a core method around which the frameworks were developed

Risk-based maintenance of critical and complex systems

Tableau d’honneur de la Faculté des études supérieures et postdoctorales, 2016-2017.De nos jours, la plupart des systèmes dans divers secteurs critiques tels que l'aviation, le pétrole et les soins de santé sont devenus très complexes et dynamiques, et par conséquent peuvent à tout moment s'arrêter de fonctionner. Pour éviter que cela ne se reproduise et ne devienne incontrôlable ce qui engagera des pertes énormes en matière de coûts et d'indisponibilité; l'adoption de stratégies de contrôle et de maintenance s'avèrent plus que nécessaire et même vitale. Dans le génie des procédés, les stratégies optimales de maintenance pour ces systèmes pourraient avoir un impact significatif sur la réduction des coûts et sur les temps d'arrêt, sur la maximisation de la fiabilité et de la productivité, sur l'amélioration de la qualité et enfin pour atteindre les objectifs souhaités des compagnies. En outre, les risques et les incertitudes associés à ces systèmes sont souvent composés de plusieurs relations de cause à effet de façon extrêmement complexe. Cela pourrait mener à une augmentation du nombre de défaillances de ces systèmes. Par conséquent, un outil d'analyse de défaillance avancée est nécessaire pour considérer les interactions complexes de défaillance des composants dans les différentes phases du cycle de vie du produit pour assurer les niveaux élevés de sécurité et de fiabilité. Dans cette thèse, on aborde dans un premier temps les lacunes des méthodes d'analyse des risques/échec et celles qui permettent la sélection d'une classe de stratégie de maintenance à adopter. Nous développons ensuite des approches globales pour la maintenance et l'analyse du processus de défaillance fondée sur les risques des systèmes et machines complexes connus pour être utilisées dans toutes les industries. Les recherches menées pour la concrétisation de cette thèse ont donné lieu à douze contributions importantes qui se résument comme suit: Dans la première contribution, on aborde les insuffisances des méthodes en cours de sélection de la stratégie de maintenance et on développe un cadre fondé sur les risques en utilisant des méthodes dites du processus de hiérarchie analytique (Analytical Hierarchy Process (AHP), de cartes cognitives floues (Fuzzy Cognitive Maps (FCM)), et la théorie des ensembles flous (Fuzzy Soft Sets (FSS)) pour sélectionner la meilleure politique de maintenance tout en considérant les incertitudes. La deuxième contribution aborde les insuffisances de la méthode de l'analyse des modes de défaillance, de leurs effets et de leur criticité (AMDEC) et son amélioration en utilisant un modèle AMDEC basée sur les FCM. Les contributions 3 et 4, proposent deux outils de modélisation dynamique des risques et d'évaluation à l'aide de la FCM pour faire face aux risques de l'externalisation de la maintenance et des réseaux de collaboration. Ensuite, on étend les outils développés et nous proposons un outil d'aide à la décision avancée pour prédire l'impact de chaque risque sur les autres risques ou sur la performance du système en utilisant la FCM (contribution 5).Dans la sixième contribution, on aborde les risques associés à la maintenance dans le cadre des ERP (Enterprise Resource Planning (ERP)) et on propose une autre approche intégrée basée sur la méthode AMDEC floue pour la priorisation des risques. Dans les contributions 7, 8, 9 et 10, on effectue une revue de la littérature concernant la maintenance basée sur les risques des dispositifs médicaux, puisque ces appareils sont devenus très complexes et sophistiqués et l'application de modèles de maintenance et d'optimisation pour eux est assez nouvelle. Ensuite, on développe trois cadres intégrés pour la planification de la maintenance et le remplacement de dispositifs médicaux axée sur les risques. Outre les contributions ci-dessus, et comme étude de cas, nous avons réalisé un projet intitulé “Mise à jour de guide de pratique clinique (GPC) qui est un cadre axé sur les priorités pour la mise à jour des guides de pratique cliniques existantes” au centre interdisciplinaire de recherche en réadaptation et intégration sociale du Québec (CIRRIS). Nos travaux au sein du CIRRIS ont amené à deux importantes contributions. Dans ces deux contributions (11e et 12e) nous avons effectué un examen systématique de la littérature pour identifier les critères potentiels de mise à jour des GPCs. Nous avons validé et pondéré les critères identifiés par un sondage international. Puis, sur la base des résultats de la onzième contribution, nous avons développé un cadre global axé sur les priorités pour les GPCs. Ceci est la première fois qu'une telle méthode quantitative a été proposée dans la littérature des guides de pratiques cliniques. L'évaluation et la priorisation des GPCs existants sur la base des critères validés peuvent favoriser l'acheminement des ressources limitées dans la mise à jour de GPCs qui sont les plus sensibles au changement, améliorant ainsi la qualité et la fiabilité des décisions de santé.Today, most systems in various critical sectors such as aviation, oil and health care have become very complex and dynamic, and consequently can at any time stop working. To prevent this from reoccurring and getting out of control which incur huge losses in terms of costs and downtime; the adoption of control and maintenance strategies are more than necessary and even vital. In process engineering, optimal maintenance strategies for these systems could have a significant impact on reducing costs and downtime, maximizing reliability and productivity, improving the quality and finally achieving the desired objectives of the companies. In addition, the risks and uncertainties associated with these systems are often composed of several extremely complex cause and effect relationships. This could lead to an increase in the number of failures of such systems. Therefore, an advanced failure analysis tool is needed to consider the complex interactions of components’ failures in the different phases of the product life cycle to ensure high levels of safety and reliability. In this thesis, we address the shortcomings of current failure/risk analysis and maintenance policy selection methods in the literature. Then, we develop comprehensive approaches to maintenance and failure analysis process based on the risks of complex systems and equipment which are applicable in all industries. The research conducted for the realization of this thesis has resulted in twelve important contributions, as follows: In the first contribution, we address the shortcomings of the current methods in selecting the optimum maintenance strategy and develop an integrated risk-based framework using Analytical Hierarchy Process (AHP), fuzzy Cognitive Maps (FCM), and fuzzy Soft set (FSS) tools to select the best maintenance policy by considering the uncertainties.The second contribution aims to address the shortcomings of traditional failure mode and effect analysis (FMEA) method and enhance it using a FCM-based FMEA model. Contributions 3 and 4, present two dynamic risk modeling and assessment tools using FCM for dealing with risks of outsourcing maintenance and collaborative networks. Then, we extend the developed tools and propose an advanced decision support tool for predicting the impact of each risk on the other risks or on the performance of system using FCM (contribution 5). In the sixth contribution, we address the associated risks in Enterprise Resource Planning (ERP) maintenance and we propose another integrated approach using fuzzy FMEA method for prioritizing the risks. In the contributions 7, 8, 9, and 10, we perform a literature review regarding the risk-based maintenance of medical devices, since these devices have become very complex and sophisticated and the application of maintenance and optimization models to them is fairly new. Then, we develop three integrated frameworks for risk-based maintenance and replacement planning of medical devices. In addition to above contributions, as a case study, we performed a project titled “Updating Clinical Practice Guidelines; a priority-based framework for updating existing guidelines” in CIRRIS which led to the two important contributions. In these two contributions (11th and 12th) we first performed a systematic literature review to identify potential criteria in updating CPGs. We validated and weighted the identified criteria through an international survey. Then, based on the results of the eleventh contribution, we developed a comprehensive priority-based framework for updating CPGs based on the approaches that we had already developed and applied success fully in other industries. This is the first time that such a quantitative method has been proposed in the literature of guidelines. Evaluation and prioritization of existing CPGs based on the validated criteria can promote channelling limited resources into updating CPGs that are most sensitive to change, thus improving the quality and reliability of healthcare decisions made based on current CPGs. Keywords: Risk-based maintenance, Maintenance strategy selection, FMEA, FCM, Medical devices, Clinical practice guidelines

LINCS : Linking Information for Nonfatal Crash Surveillance : a guide for integrating motor vehicle crash data to help keep Americans safe on the road

The Linking Information for Nonfatal Crash Surveillance (LINCS) Guide is intended to help states start a data linkage program or expand their current program to help prevent motor vehicle crash-related injuries and deaths. The guide discusses the key components of successful linkage programs and details each step in the data linkage process.Motor vehicle crashes (MVCs) are a leading cause of death for people aged 1-54 years in the United States (U.S.). More than 100 people die in MVCs each day and thousaOne method to better understand MVCs is to effectively use existing data sources, such as police, hospital, and emergency medical services (EMS) records. These data sources contain different information and the data sets are generally collected and stored separately. Therefore, linking the data sets together can create a more comprehensive understanding of MVCs by pulling all of the data together into one linked data set. A linked data set will include information about what happened before (e.g., impaired driving), during (e.g., seat belt was being used), and after a crash (e.g., medical outcomes and costs).nds more are injured. Understanding the risk factors and ways to address them can help prevent MVC-related injuries and deaths and reduce costs.The CDC\u2019s National Center for Injury Prevention and Control (NCIPC) enlisted the Centers for Medicare & Medicaid Services (CMS) Alliance to Modernize Healthcare (CAMH)\u2014a federally funded research and development center operated by The MITRE Corporation\u2014to create a guide to help states start or enhance data linkage programs. Linking MVC data sets creates a more comprehensive set of linked data for each MVC incident and for each individual involved in the MVC. Comprehensive MVC linked data can enable analysis of the relationships among contributing factors, interventions, outcomes, and impacts. For example, one advantage of linking police MVC records to hospital records is to assess the magnitude of nonfatal MVC injuries and associated healthcare costs.CS 302338-APublication date from document properties.CDC_LINCS_GUIDE_2019-F.pdfExecutive Summary -- Motor Vehicle Crashes and LINCS -- Introduction -- The LINCS Guide -- Section 1. Establishing a Motor Vehicle Crash Data Linkage Program -- Section 2. Building Partnerships -- Section 3. Developing a Business Model -- Section 4. Establishing the Data Linkage Process -- Conclusion -- Appendix A. National Systems for Motor Vehicle Crash Data -- Appendix B. Literature Review of Published Motor Vehicle Crash Research Using Linked Data -- Appendix C. Crash Outcome -- Data Evaluation System (CODES) -- Appendix D. Stakeholder Listening Sessions -- Appendix E. Select Data Linkage Method(s) -- Appendix F. Select Data Linkage Tools. -- Appendix G. State Motor Vehicle Crash Data Linkage Programs -- Appendix H. Motor Vehicle Crash Data Linkage Program Resources -- Appendix I. Department of Transportation Traffic Records Coordinating Committee Technical Assistance Resources -- Appendix J. Security Program Activities -- Appendix K. Privacy Program Activities. -- Appendix L. Sample Data Use Agreement -- Appendix M. Reduce Computational Requirements. -- Appendix N. Multiple Imputation and Missing Data -- Appendix O. Assessing Data Quality: Variation -- Appendix P. Evaluating Data Linkage Processes -- Appendix Q. Examples of MVC Data Content Standards -- Appendix R. Explanation of Figures for Accessibility -- Acknowledgments -- Acronyms. -- Glossary \u2013 References.2019674

Utilizing artificial intelligence in perioperative patient flow:systematic literature review

Abstract. The purpose of this thesis was to map the existing landscape of artificial intelligence (AI) applications used in secondary healthcare, with a focus on perioperative care. The goal was to find out what systems have been developed, and how capable they are at controlling perioperative patient flow. The review was guided by the following research question: How is AI currently utilized in patient flow management in the context of perioperative care? This systematic literature review examined the current evidence regarding the use of AI in perioperative patient flow. A comprehensive search was conducted in four databases, resulting in 33 articles meeting the inclusion criteria. Findings demonstrated that AI technologies, such as machine learning (ML) algorithms and predictive analytics tools, have shown somewhat promising outcomes in optimizing perioperative patient flow. Specifically, AI systems have proven effective in predicting surgical case durations, assessing risks, planning treatments, supporting diagnosis, improving bed utilization, reducing cancellations and delays, and enhancing communication and collaboration among healthcare providers. However, several challenges were identified, including the need for accurate and reliable data sources, ethical considerations, and the potential for biased algorithms. Further research is needed to validate and optimize the application of AI in perioperative patient flow. The contribution of this thesis is summarizing the current state of the characteristics of AI application in perioperative patient flow. This systematic literature review provides information about the features of perioperative patient flow and the clinical tasks of AI applications previously identified

Onshore Cross Country Pipelines Risk Assessment and Decision Making Under Uncertainty

Onshore cross-country pipelines are a critical component of refined product transportation in the oil and gas industry. The integrity of those pipelines is key to maintaining supply security, protecting the environment and human life. However, due to incessant pipeline damages and resultant consequences of fires, explosion and environmental pollution because of third-party events in Nigeria, stakeholders are looking at solutions to reduce the human, environmental and the financial losses. The main objective of this research is to develop risk-based models for identifying and assessing the oil and gas pipelines failures, including risk reduction decision-making framework and cost-benefit estimates. One of the major challenges of carrying out a pipeline risk assessment in some regions is the lack of reliable and objective data for data-driven analysis. The models developed in this thesis addressed this shortcoming and allowed the subjective data to be incorporated into the analysis. Hazards identification and ranking of the failure modes have been carried out using a modified FMEA based Fuzzy Rules Base (FRB) and Grey Relations Theory (GRT) to accommodate the uncertainty in terms of inadequate data. The results of modified approach serve as an input to developing the failure likelihood and this involves a Bayesian Network (BN) model of the identified failure mode. The BN model has been developed using Hugin software. The results of the BN feeds into the Evidential Reasoning (ER) model to aid risk management decision-making. Also, cost benefit estimates have been carried out to assess the cost benefit of implementing any risk reduction options. All the objectives set out in the thesis have been achieved. The research has contributed to the stated challenges by identifying the parameters for high failure incidences and develop various models and assess contributing failure factors and the risk control options to reducing the likelihood of the failure including cost benefit estimates

Local Understanding and Practices Related to IMCI Interventions in Eastern Tanzania

This PhD thesis presents findings of the health seeking component of the Tanzania Essential Health Intervention Project (TEHIP). It was carried out from 1998 to 2001 in two districts of southern Tanzania where Integrated Management of Childhood Illness (IMCI) was introduced in 1997. The rationale is that best IMCI services are of little benefit, if they do not reach community and household levels. Caregivers need to understand and comply with IMCI core principles, i.e. learn to recognize the correct danger signs and seek prompt and effective treatment. The goal of our study was to contribute to increasing “community effectiveness” (Tanner et al. 1993) of health care in the study districts. Our specific objectives were to generate local knowledge to better adjust the IMCI interventions to local health seeking behavior and to improve the ways in which caretakers identify and manage common childhood illness. We define health seeking to encompass three dimensions: 1) health concepts including signs and symptoms recognized by the community; 2) aetiology comprising interpretations and explanations of illness; and 3) help seeking referring to home management and all forms of seeking help from experts, whether these are neighbors, traditional healers or health care staff. We first investigated the local illness terminology and the relative importance of symptom recognition and labeling in care-seeking. We found that local illness terms overlap with biomedical classifications such as “malaria”, but this overlap does not constitute direct correspondence. Caregivers rarely see a link between malaria and convulsions and create new links between convulsions and polio, tetanus and epilepsy. We identified intra-cultural diversity in symptom recognition and severity ranking of the same illness. Caregivers search for illness labels which are not only a name but contain information about treatment. In this search they face difficulties due to two reasons: 1) different illnesses produce similar symptoms, and 2) different persons provide changing and even contradictory advice and information. We introduce the term “fuzzy concept” and suggest that fuzziness can be explained by the diverse manifestations of malaria, by intra-cultural variability and/or by culture change confronting individual persons with multiple meanings. In a second step we analyze local aetiologies which we consider equally important for appropriate care-seeking as prompt recognition of danger signs and symptoms. Community aetiologies of IMCI related illness encompass a wide spectrum ranging from natural to supernatural causes. Some caregivers act on these notions, others are not interested in causes, and the majority remains ambivalent and pragmatic. A closer analysis of malaria-related aetiology shows that caregivers clearly attribute malaria to mosquito bites but have fragmented knowledge about the aetiology of homa (fever) and degedege (convulsions). We suggest that aetiological uncertainty leads to difficulties in therapy choice and thus to pragmatic ambivalence. In a third step we assess care-seeking in actual illness episodes. Caregivers make extensive use of formal health care facilities, not only for homa and malaria but for most other IMCI related illnesses. Exceptions are the folk illnesses degedege and kimeo (elongated uvula). The basic distinction found in many parts of Africa also applies to our study sites: 1) mild and “normal” malaria is first treated at home and if not cured brought to a formal health care facility; 2) severe forms of the disease presenting convulsions are rarely considered as malaria but as a distinct illness entity requiring traditional treatment at home or from a traditional healer. Our most important finding is that many children who suffer and sometimes even die from convulsions have had not only a history of homa but have even been diagnosed and treated for malaria in a health facility before they developed convulsions. In the fourth and final step we examine the impact of malaria care-seeking patterns on childhood mortality. Our findings show that nearly 80 percent of malaria-attributable deaths used modern biomedical care as a first resort, both in the form of antimalarial pharmaceuticals from shops or formal health care services. If care was sought more than once in these fatal cases, modern care was included in the first or second resort in 90 percent with convulsions and 99 percent without convulsions. There clearly is an urgent need for a thorough analysis of what is happening in these cases. Health providers often formulate the problem of recurrent illness in terms of a delay in treatment or a lack of adherence to treatment regimes. We argue that victim blaming does not bring us any further. Our case studies demonstrate that many mothers make an enormous effort in time, energy and money searching for the best care for their child. They should be supported rather than blamed by the health system

Public Health

Public health can be thought of as a series of complex systems. Many things that individual living in high income countries take for granted like the control of infectious disease, clean, potable water, low infant mortality rates require a high functioning systems comprised of numerous actors, locations and interactions to work. Many people only notice public health when that system fails. This book explores several systems in public health including aspects of the food system, health care system and emerging issues including waste minimization in nanosilver. Several chapters address global health concerns including non-communicable disease prevention, poverty and health-longevity medicine. The book also presents several novel methodologies for better modeling and assessment of essential public health issues

Mechatronic Systems

Mechatronics, the synergistic blend of mechanics, electronics, and computer science, has evolved over the past twenty five years, leading to a novel stage of engineering design. By integrating the best design practices with the most advanced technologies, mechatronics aims at realizing high-quality products, guaranteeing at the same time a substantial reduction of time and costs of manufacturing. Mechatronic systems are manifold and range from machine components, motion generators, and power producing machines to more complex devices, such as robotic systems and transportation vehicles. With its twenty chapters, which collect contributions from many researchers worldwide, this book provides an excellent survey of recent work in the field of mechatronics with applications in various fields, like robotics, medical and assistive technology, human-machine interaction, unmanned vehicles, manufacturing, and education. We would like to thank all the authors who have invested a great deal of time to write such interesting chapters, which we are sure will be valuable to the readers. Chapters 1 to 6 deal with applications of mechatronics for the development of robotic systems. Medical and assistive technologies and human-machine interaction systems are the topic of chapters 7 to 13.Chapters 14 and 15 concern mechatronic systems for autonomous vehicles. Chapters 16-19 deal with mechatronics in manufacturing contexts. Chapter 20 concludes the book, describing a method for the installation of mechatronics education in schools