Search results for: clinical decision support sytem

Authors: D. Tedesco, G. Feletti, P. Trucco

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The present study aims to develop a Decision Support System (DSS) to support the operational decision of the Emergency Medical Service (EMS) regarding the assignment of medical emergency requests to Emergency Departments (ED). In the literature, this problem is also known as “hospital selection” and concerns the definition of policies for the selection of the ED to which patients who require further treatment are transported by ambulance. The employed research methodology consists of the first phase of revision of the technical-scientific literature concerning DSSs to support the EMS management and, in particular, the hospital selection decision. From the literature analysis, it emerged that current studies are mainly focused on the EMS phases related to the ambulance service and consider a process that ends when the ambulance is available after completing a request. Therefore, all the ED-related issues are excluded and considered as part of a separate process. Indeed, the most studied hospital selection policy turned out to be proximity, thus allowing to minimize the transport time and release the ambulance in the shortest possible time. The purpose of the present study consists in developing an optimization model for assigning medical emergency requests to the EDs, considering information relating to the subsequent phases of the process, such as the case-mix, the expected service throughput times, and the operational capacity of different EDs in hospitals. To this end, a Discrete Event Simulation (DES) model was created to evaluate different hospital selection policies. Therefore, the next steps of the research consisted of the development of a general simulation architecture, its implementation in the AnyLogic software and its validation on a realistic dataset. The hospital selection policy that produced the best results was the minimization of the Time To Provider (TTP), considered as the time from the beginning of the ambulance journey to the ED at the beginning of the clinical evaluation by the doctor. Finally, two approaches were further compared: a static approach, which is based on a retrospective estimate of the TTP, and a dynamic approach, which is based on a predictive estimate of the TTP determined with a constantly updated Winters model. Findings reveal that considering the minimization of TTP as a hospital selection policy raises several benefits. It allows to significantly reduce service throughput times in the ED with a minimum increase in travel time. Furthermore, an immediate view of the saturation state of the ED is produced and the case-mix present in the ED structures (i.e., the different triage codes) is considered, as different severity codes correspond to different service throughput times. Besides, the use of a predictive approach is certainly more reliable in terms of TTP estimation than a retrospective approach but entails a more difficult application. These considerations can support decision-makers in introducing different hospital selection policies to enhance EMSs performance.

Keywords: discrete event simulation, emergency medical services, forecast model, hospital selection

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Authors: Pejman Hosseinioun, Hasan Shakeri, Ghasem Ghorbanirostam

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In recent years, we have seen an increasing importance of research and study on knowledge source, decision support systems, data mining and procedure of knowledge discovery in data bases and it is considered that each of these aspects affects the others. In this article, we have merged information source and knowledge source to suggest a knowledge based system within limits of management based on storing and restoring of knowledge to manage information and improve decision making and resources. In this article, we have used method of data mining and Apriori algorithm in procedure of knowledge discovery one of the problems of Apriori algorithm is that, a user should specify the minimum threshold for supporting the regularity. Imagine that a user wants to apply Apriori algorithm for a database with millions of transactions. Definitely, the user does not have necessary knowledge of all existing transactions in that database, and therefore cannot specify a suitable threshold. Our purpose in this article is to improve Apriori algorithm. To achieve our goal, we tried using fuzzy logic to put data in different clusters before applying the Apriori algorithm for existing data in the database and we also try to suggest the most suitable threshold to the user automatically.

Keywords: decision support system, data mining, knowledge discovery, data discovery, fuzzy logic

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Authors: Avinash S. Jagtap, Sharad D. Gore, Rajendra G. Gurao

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Decision rules become more and more complex as the number of conditions increase. As a consequence, the complexity of the decision rule also influences the time complexity of computer implementation of such a rule. Consider, for example, a decision that depends on four conditions A, B, C and D. For simplicity, suppose each of these four conditions is binary. Even then the decision rule will consist of 16 lines, where each line will be of the form: If A and B and C and D, then action 1. If A and B and C but not D, then action 2 and so on. While executing this decision rule, each of the four conditions will be checked every time until all the four conditions in a line are satisfied. The minimum number of logical comparisons is 4 whereas the maximum number is 64. This paper proposes to present a complex decision rule in the form of a decision tree. A decision tree divides the cases into branches every time a condition is checked. In the form of a decision tree, every branching eliminates half of the cases that do not satisfy the related conditions. As a result, every branch of the decision tree involves only four logical comparisons and hence is significantly simpler than the corresponding complex decision rule. The conclusion of this paper is that every complex decision rule can be represented as a decision tree and the decision tree is mathematically equivalent but computationally much simpler than the original complex decision rule

Keywords: strategic, tactical, operational, adaptive, innovative

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Authors: Szilvia Halmos

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Hungary was one of the first countries to sign and ratify the UN Convention on the Rights of Persons with Disabilities (hereinafter: CRPD). Consequently, Hungary assumed an obligation under international law to review the national law in the light of the Article 12 of the CRPD requiring the States parties to guarantee the equality of persons with disabilities in terms of legal capacity, and to replace the regimes of substitute decision-making by the instruments of supported decision-making. This article is often characterized as one of the key norms of the CRPD, since the legal autonomy of the persons with disabilities is an essential precondition of their participation in the social life on an equal basis with others, envisaged by the social paradigm of disability. This paper examines the impact of the CRPD on the relevant Hungarian national legal norms, with special focus on the relevant rules of the recently codified Civil Code. The employed research methodologies include (1) the specification of the implementation requirements imposed by the Article 12 of the CRPD, (2) the determination of the indicators of the appropriate implementation, (3) the critical analysis of compliance of the relevant Hungarian legal regulation with the indicators, (4) with respect to the relevant case law of the Hungarian Constitutional Court and ordinary courts, the European Court of Human Rights and the Committee of Rights of Persons with Disabilities and (5) to the available empirical figures on the functioning of substitute and supported decision-making regimes. It will be established that the new Civil Code has made large steps toward the equality of persons with disabilities in terms of legal capacity and the support model of decision-making by the introduction of some specific instruments of supported decision-making and the restriction of the application of guardianship. Nevertheless, the regulation currently in effect fails to represent some crucial principles of the Article 12 of the CRPD, such as the non-discrimination of persons with psycho-social disabilities, the support of the articulation of the will and preferences of the individual instead of his/her best interest in the course of decision-making. The changes in the practice of the substitute and the support model brought about by the new legal norms can also be assessed as significant, however, so far unsatisfactory. The number of registered supporters is rather low, and the preconditions of the effective functioning of the support (e.g. the proper training of the supporters) are not ensured.

Keywords: Article 12 of the UN CRPD, Hungarian law on legal capacity, persons with intellectual and psycho-social disabilities, supported decision-making

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Authors: Rebecca Greenberg, Nipa Chauhan, Rashad Rehman

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Paternalism, in its traditional form, seems largely incompatible with Western medicine. In contrast, Family-Centred Care, a partial response to historically authoritative paternalism, carries its own challenges, particularly when operationalized as family-directed care. Specifically, in neonatology, decision-making is left entirely to Substitute Decision Makers (most commonly parents). Most models of shared decision-making employ both the parents’ and medical team’s perspectives but do not recognize the inherent asymmetry of information and experience – asking parents to act like physicians to evaluate technical data and encourage physicians to refrain from strong medical opinions and proposals. They also do not fully appreciate the difficulties in adjudicating which perspective to prioritize and, moreover, how to mitigate disagreement. Introducing a mild form of paternalism can harness the unique skillset both parents and clinicians bring to shared decision-making and ultimately work towards decision-making in the best interest of the child. The notion expressed here is that within the model of shared decision-making, mild paternalism is prioritized inasmuch as optimal care is prioritized. This mild form of paternalism is known as Beneficent Paternalism and justifies our encouragement for physicians to root down in their own medical expertise to propose treatment plans informed by medical expertise, standards of care, and the parents’ values. This does not mean that we forget that paternalism was historically justified on ‘beneficent’ grounds; however, our recommendation is that a re-integration of mild paternalism is appropriate within our current Western healthcare climate. Through illustrative examples from the NICU, this paper explores the appropriateness and merits of Beneficent Paternalism and ultimately its use in promoting family-centered care, patient’s best interests and reducing moral distress. A distinctive feature of the NICU is the fact that communication regarding a patient’s treatment is exclusively done with substitute decision-makers and not the patient, i.e., the neonate themselves. This leaves the burden of responsibility entirely on substitute decision-makers and the clinical team; the patient in the NICU does not have any prior wishes, values, or beliefs that can guide decision-making on their behalf. Therefore, the wishes, values, and beliefs of the parent become the map upon which clinical proposals are made, giving extra weight to the family’s decision-making responsibility. This leads to why Family Directed Care is common in the NICU, where shared decision-making is mandatory. However, the zone of parental discretion is not as all-encompassing as it is currently considered; there are appropriate times when the clinical team should strongly root down in medical expertise and perhaps take the lead in guiding family decision-making: this is just what it means to adopt Beneficent Paternalism.

Keywords: care, ethics, expertise, NICU, paternalism

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Authors: Islah Ud Din, Amna Bibi

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The current study was carried out to examine the perceived social support, resilience and relapse risk in recovered addicts. A purposive sampling technique was used to collect data from recovered addicts. A multidimensional scale of perceived social support by was used to measure the perceived social support. The brief Resilience Scale (BRS) was used to assess resilience. The Stimulant Relapse Risk Scale (SRRS) was used to examine the relapse risk. Resilience and Perceived social support have substantial positive correlations, whereas relapse risk and perceived social support have significant negative associations. Relapse risk and resilience have a strong inverse connection. Regression analysis was used to check the mediating effect of resilience between perceived social support and relapse risk. The findings revealed that perceived social support negatively predicted relapse risk. Results showed that Resilience plays a role as partial mediation between perceived social support and relapse risk. This Research will allow us to explore and understand the relapse risk factor and the role of perceived social support and resilience in recovered addicts. The study's findings have immediate consequences in the prevention of relapse. The study will play a significant part in drug rehabilitation centers, clinical settings and further research.

Keywords: perceived social support, resilience, relapse risk, recovered addicts, drugs addiction

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Authors: Xuan Linh Nguyen, Tien Yin Chou, Yao Min Fang, Feng Cheng Lin, Thanh Van Hoang, Yin Min Huang

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In Vietnam, land use planning is the most important and powerful tool of the government for sustainable land use and land management. Nevertheless, many of land use planning locations are facing protests from surrounding households due to environmental impacts. In addition, locations are planned completely based on the subjective decisions of planners who are unsupported by tools or scientific methods. Hence, this research aims to assist the decision-makers in evaluating the rationality of planning locations by developing a Spatial Decision Support System (SDSS) using approaches of Geographic Information System (GIS)-based technology, Analytic Hierarchy Process (AHP) multi-criteria-based technique and Fuzzy set theory. An ArcGIS Desktop add-ins named SDSS-LUPA was developed to support users analyzing data and presenting results in friendly format. The Fuzzy-AHP method has been utilized as analytic model for this SDSS. There are 18 planned locations in Hung Ha district (Thai Binh province, Vietnam) as a case study. The experimental results indicated that the assessment threshold higher than 0.65 while the 18 planned locations were irrational because of close to residential areas or close to water sources. Some potential sites were also proposed to the authorities for consideration of land use planning changes.

Keywords: analytic hierarchy process, fuzzy set theory, land use planning, spatial decision support system

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Authors: Katejarinporn Chaiya, Jarumon Nookong, Nutthapat Kaewrattanapat

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The purposes of this research were to develop and find users’ satisfaction after using the Decision Support System for Examination Selection. This research presents the design of information systems. In order to find the necessary examination of the statistics. Based on the examination of the candidate and then taking the easy difficulty setting statistics applied to the test. In addition, research has also made performance appraisals from experts and user satisfaction. By results of analysis showed that the performance appraisals from experts on the system as a whole and at a good level. mean was 3.44 and S.D. was 0.55 and user satisfaction per system as a whole and the good level mean was 3.37 and S.D. was 0.42 can conclude that effective systems are in a good level. Work has been completed in accordance with the scope of work. The website used developing this project is PHP, MySQL.5.0.45 for database.

Keywords: secision support system, examination, PHP, information systems

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Authors: Giuseppe Timperio, Robert de Souza

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Logistics operations in the context of disaster response are characterized by a high degree of complexity due to the combined effect of a large number of stakeholders involved, time pressure, uncertainties at various levels, massive deployment of goods and personnel, and gigantic financial flow to be managed. It also involves several autonomous parties such as government agencies, militaries, NGOs, UN agencies, private sector to name few, to have a highly collaborative approach especially in the critical phase of the immediate response. This is particularly true in the context of L3 emergencies that are the most severe, large-scale humanitarian crises. Decision-making processes in disaster management are thus extremely difficult due to the presence of multiple decision-makers involved, and the complexity of the tasks being tackled. Hence, in this paper, we look at applying ICT based solutions to enable a speedy and effective decision making in the golden window of humanitarian operations. A high-level view of ICT based solutions in the context of logistics operations for humanitarian response in Southeast Asia is presented, and their viability in a real-life case about logistics network design is explored.

Keywords: decision support, disaster preparedness, humanitarian logistics, network design

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Authors: Elaine Llantos Elayda, John Mark S. Distor

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This paper explores the lived experiences of clinical psychology interns' who have encountered suicidal clients during their internship. Employing qualitative phenomenological investigation, semi-structured interviews were conducted and analyzed using interpretative phenomenological analysis (IPA). The study employed purposive sampling to gather valuable data. The results highlighted that those encounters with suicidal clients triggered various reactions among interns, leading to self-doubt and a sense of unpreparedness in handling such cases. Many interns struggled with managing their own emotions, especially when clients' traumas mirrored their own experiences. The study emphasized the importance of a robust support system in helping interns cope with the challenges of their work. Supervision and professional support played critical roles in interns' development, providing guidance and enhancing their confidence in managing distressing situations. Despite the challenges, the interns found purpose in witnessing significant client progress and emphasized the importance of self-care and ongoing training to prepare future clinicians for similar experiences.

Keywords: polytechnic university of the Philippines, clinical psychology interns, suicidal clients, clinical psychology training

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Authors: Simone Huber, Bianca Schnalzer, Baptiste Alcalde, Sten Hanke, Lampros Mpaltadoros, Thanos G. Stavropoulos, Spiros Nikolopoulos, Ioannis Kompatsiaris, Lina Pérez- Breva, Vallivana Rodrigo-Casares, Jaime Fons-Martínez, Jeroen de Bruin

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Developing new medicine and health solutions and improving patient health currently rely on the successful execution of clinical trials, which generate relevant safety and efficacy data. For their success, recruitment and retention of participants are some of the most challenging aspects of protocol adherence. Main barriers include: i) lack of awareness of clinical trials; ii) long distance from the clinical site; iii) the burden on participants, including the duration and number of clinical visits and iv) high dropout rate. Most of these aspects could be addressed with a new paradigm, namely the Remote Decentralized Clinical Trials (RDCTs). Furthermore, the COVID-19 pandemic has highlighted additional advantages and challenges for RDCTs in practice, allowing participants to join trials from home and not depend on site visits, etc. Nevertheless, RDCTs should follow the process and the quality assurance of conventional clinical trials, which involve several processes. For each part of the trial, the Building Blocks, existing software and technologies were assessed through a systematic search. The technology needed to perform RDCTs is widely available and validated but is yet segmented and developed in silos, as different software solutions address different parts of the trial and at various levels. The current paper is analyzing the availability of technology to perform RDCTs, identifying gaps and providing an overview of Basic Building Blocks and functionalities that need to be covered to support the described processes.

Keywords: architectures and frameworks for health informatics systems, clinical trials, information and communications technology, remote decentralized clinical trials, technology availability

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Authors: Hamid Reza Behnood, Esmaeel Ayati, Tom Brijs, Mohammadali Pirayesh Neghab

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Investment projects in road safety planning can benefit from an effectiveness evaluation regarding their expected safety outcomes. The objective of this study is to develop a decision support system (DSS) to support policymakers in taking the right choice in road safety planning based on the efficiency of previously implemented safety measures in a set of regions in Iran. The measures considered for each region in the study include performance indicators about (1) police operations, (2) treated black spots, (3) freeway and highway facility supplies, (4) speed control cameras, (5) emergency medical services, and (6) road lighting projects. To this end, inefficiency measure is calculated, defined by the proportion of fatality rates in relation to the combined measure of road safety performance indicators (i.e., road safety measures) which should be minimized. The relative inefficiency for each region is modeled by the Data Envelopment Analysis (DEA) technique. In a next step, a fuzzy decision-making system is constructed to convert the information obtained from the DEA analysis into a rule-based system that can be used by policy makers to evaluate the expected outcomes of certain alternative investment strategies in road safety.

Keywords: performance indicators, road safety, decision support system, data envelopment analysis, fuzzy reasoning

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Authors: Ben Clapperton, Daniel Stahl, Kimberley Goldsmith, Trudie Chalder

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Chronic fatigue syndrome (CFS) is a condition characterised by chronic disabling fatigue and other symptoms that currently can't be explained by any underlying medical condition. Although clinical trials support the effectiveness of cognitive behaviour therapy (CBT), the success rate for individual patients is modest. Patients vary in their response and little is known which factors predict or moderate treatment outcomes. The aim of the project is to develop a prediction model from baseline characteristics of patients, such as demographics, clinical and psychological variables, which may predict likely treatment outcome and provide guidance for clinical decision making and help clinicians to recommend the best treatment. The project is aimed at identifying subgroups of patients with similar baseline characteristics that are predictive of treatment effects using modern cluster analyses and data mining machine learning algorithms. The characteristics of these groups will then be used to inform the types of individuals who benefit from a specific treatment. In addition, results will provide a better understanding of for whom the treatment works. The suitability of different clustering methods to identify subgroups and their response to different treatments of CFS patients is compared.

Keywords: chronic fatigue syndrome, latent class analysis, prediction modelling, self-organizing maps

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Authors: Ange Weinrabe, James Tran, Ian B. Hickie

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Risk-taking behaviour is common during youth. In the time between adolescence and early adulthood, young people (aged 15-25 years) are more vulnerable to mood disorders, such as anxiety and depression. What impact does an emerging mood disorder have on decision-making in youth at critical decision points in their lives? In this article, we explore the impact of risk and ambiguity on youth decision-making in a clinical setting using a well-known economic experiment. At two time points, separated by six to eight weeks, we measured risky and ambiguous choices concurrently with findings from three psychological questionnaires, the 10-item Kessler Psychological Distress Scale (K10), the 17-item Quick Inventory of Depressive Symptomatology Adolescent Version (QIDS-A17), and the 12-item Somatic and Psychological Health Report (SPHERE-12), for young help seekers aged 16-25 (n=30, mean age 19.22 years, 19 males). When first arriving for care, we found that 50% (n=15) of participants experienced severe anxiety (K10 ≥ 30) and were severely depressed (QIDS-A17 ≥ 16). In Session 2, taking attrition rates into account (n=5), we found that 44% (n=11) remained severe across the full battery of questionnaires. When applying multiple regression analyses of the pooled sample of observations (N=55), across both sessions, we found that participants who rated severely anxious avoided making risky decisions. We suggest there is some statistically significant (although weak) (p=0.09) relation between risk and severe anxiety scores as measured by K10. Our findings may support working with novel tools with which to evaluate youth experiencing an emerging mood disorder and their cognitive capacities influencing decision-making.

Keywords: anxiety, decision-making, risk, adolescence

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Authors: Anli Du Preez, James Bekker

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Data is currently one of the most critical and influential emerging technologies. However, the true potential of data is yet to be exploited since, currently, about 1% of generated data are ever actually analyzed for value creation. There is a data gap where data is not explored due to the lack of data analytics infrastructure and the required data analytics skills. This study developed a decision support framework for data analytics by following Jabareen’s framework development methodology. The study focused on machine learning algorithms, which is a subset of data analytics. The developed framework is designed to assist data analysts with little experience, in choosing the appropriate machine learning algorithm given the purpose of their application.

Keywords: Data analytics, Industrial engineering, Machine learning, Value creation

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Authors: Ozgu Turgut

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Water scarcity is a problem for many regions which requires immediate action, and solutions cannot be postponed for a long time. It is known that farming consumes a significant portion of usable water. Although in recent years, the efforts to make the transition to dripping or spring watering systems instead of using surface watering started to pay off. It is also known that this transition is not necessarily translated into an increase in the capacity dedicated to other water consumption channels such as city water or power usage. In order to control and allocate the water resource more purposefully, new watering systems have to be used with monitoring abilities that can limit the usage capacity for each farm. In this study, a decision support model which relies on a bi-objective stochastic linear optimization is proposed, which takes crop yield and price volatility into account. The model generates annual planting plans as well as water usage limits for each farmer in the region while taking the total value (i.e., profit) of the overall harvest. The mathematical model is solved using the L-shaped method optimally. The decision support model can be especially useful for regional administrations to plan next year's planting and water incomes and expenses. That is why not only a single optimum but also a set of representative solutions from the Pareto set is generated with the proposed approach.

Keywords: decision support, farming, water, tactical planning, optimization, stochastic, pareto

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Authors: Rawan A. Abdelrazeq, Ahmed M. Khalafallah, Nabil A. Kartam

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Selection of competent contractors for construction projects is usually accomplished through competitive bidding or negotiated contracting in which the contract bid price is the basic criterion for selection. The evaluation of contractor’s safety performance is still not a typical criterion in the selection process, despite the existence of various safety prequalification procedures. There is a critical need for practical and automated systems that enable owners and decision makers to evaluate contractor safety performance, among other important contractor selection criteria. These systems should ultimately favor safety-conscious contractors to be selected by the virtue of their past good safety records and current safety programs. This paper presents an exploratory sequential mixed-methods approach to develop a framework for an automated decision support system that evaluates contractor safety performance based on a multitude of indicators and metrics that have been identified through a comprehensive review of construction safety research, and a survey distributed to domain experts. The framework is developed in three phases: (1) determining the indicators that depict contractor current and past safety performance; (2) soliciting input from construction safety experts regarding the identified indicators, their metrics, and relative significance; and (3) designing a decision support system using relational database models to integrate the identified indicators and metrics into a system that assesses and rates the safety performance of contractors. The proposed automated system is expected to hold several advantages including: (1) reducing the likelihood of selecting contractors with poor safety records; (2) enhancing the odds of completing the project safely; and (3) encouraging contractors to exert more efforts to improve their safety performance and practices in order to increase their bid winning opportunities which can lead to significant safety improvements in the construction industry. This should prove useful to decision makers and researchers, alike, and should help improve the safety record of the construction industry.

Keywords: construction safety, contractor selection, decision support system, relational database

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Authors: J. Magerman, P. Martin

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Nursing students' clinical abilities is highly dependent on the quality of the clinical experience obtained while placed in the clinical environment. The clinical environment has amongst other, key role players which include the clinical supervisor. The primary role of the clinical supervisor is to guide nursing students to become the best practice nursing professionals. However, globally literature alludes to the failure of educating institutions to deliver competent nursing professionals to meet the needs of patients and deliver quality patient care. At the participating university, this may be due to various factors such as large student numbers and social and environmental challenges experienced by clinical supervisors. The aim of this study was to explore and describe the lived experiences of clinical supervisors who supervise nursing students at a higher education institution. The study employed a qualitative research approach utilizing a descriptive phenomenological design. Purposive sampling was used to select participants, who supervised first and second year nursing studnets at the higher education institution under study. TH esample comprised of eight clinical supervisors who supervise first and secon year nursing studnets at teh institution under study. Data was collected by means of in-depht interviews. Data was analysed using Collaizzi's seven steps method of qualitative analysis. Five major themes identified , focussed on the experiences regarding time a sa constraint to job productivity, the impact of teh organisational culture on the fluidity of support, interpersonal relationships a sa dynamic communication process, impact on the self, and limited resources. Trustworthiness of the data was ensured by means of applying Guba's model of truth value, applicability, consistency and neutrality. Reflexivity was also used by the researcher to further enhance trustworthiness.

Keywords: clinical supervision, clinical supervisors, nursing students, clinical placements

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Authors: Andrés I. Ávila, Patricia Aros, César San Martín, Elizabeth Kehr, Yovana Leal

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We consider a linear programming model to help farmers to decide if it is convinient to choose among three kinds of export fruits for their future investment. We consider area, investment, water, productivitiy minimal unit, and harvest restrictions and a monthly based model to compute the average income in five years. Also, conditions on the field as area, water availability and initia investment are required. Using the Chilean costs and dollar-peso exchange rate, we can simulate several scenarios to understand the possible risks associated to this market.

Keywords: mixed integer problem, fruit production, support decision model, fruit tree farms

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Authors: Jacqueline M. Dias, Amina A Khowaja

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Clinical education is one of the most important components of a nursing curriculum as it develops the students’ cognitive, psychomotor and affective skills. Clinical teaching ensures the integration of knowledge into practice. As the numbers of students increase in the field of nursing coupled with the faculty shortage, clinical preceptors are the best choice to ensure student learning in the clinical settings. The clinical preceptor role has been introduced in the undergraduate nursing programme. In Pakistan, this role emerged due to a faculty shortage. Initially, two clinical preceptors were hired. This study will explore clinical preceptors views and experiences of precepting Bachelor of Science in Nursing (BScN) students in an undergraduate program. A case study design was used. As case studies explore a single unit of study such as a person or very small number of subjects; the two clinical preceptors were fundamental to the study and served as a single case. Qualitative data were obtained through an iterative process using in depth interviews and written accounts from reflective journals that were kept by the clinical preceptors. The findings revealed that the clinical preceptors were dedicated to their roles and responsibilities. Another, key finding was that clinical preceptors’ prior knowledge and clinical experience were valuable assets to perform their role effectively. The clinical preceptors found their new role innovative and challenging; it was stressful at the same time. Findings also revealed that in the clinical agencies there were unclear expectations and role ambiguity. Furthermore, clinical preceptors had difficulty integrating theory into practice in the clinical area and they had difficulty in giving feedback to the students. Although this study is localized to one university, generalizations can be drawn from the results. The key findings indicate that the role of a clinical preceptor is demanding and stressful. Clinical preceptors need preparation prior to precepting students on clinicals. Also, institutional support is fundamental for their acceptance. This paper focuses on the views and experiences of clinical preceptors undertaking a newly established role and resonates with the literature. The following recommendations are drawn to strengthen the role of the clinical preceptors: A structured program for clinical preceptors is needed along with mentorship. Clinical preceptors should be provided with formal training in teaching and learning with emphasis on clinical teaching and giving feedback to students. Additionally, for improving integration of theory into practice, clinical modules should be provided ahead of the clinical. In spite of all the challenges, ten more clinical preceptors have been hired as the faculty shortage continues to persist.

Keywords: baccalaureate nursing education, clinical education, clinical preceptors, nursing curriculum

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Authors: A. Hol

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Nowadays, within quickly changing business environments, companies are often faced with specific problems where knowledge required to make timely decisions is often available however is not always readily accessible by the decision makers, in a required form. To identify if in any way via innovative system development companies could be assisted so that they can make quicker industry specific decisions in a given time and space, researchers conducted in depth case study investigation during which they studied company’s e-transformation recommendations, company’s current issues and problems as well as the nature of company’s pressing decisions. This study utilizes Scenario Based Analysis with the aim to help identify parameters crucial for the development of the system that could support decision making in a given time and space. Based on the findings, Context Specific e-transformation decision making framework is proposed.

Keywords: e-transformation, business context, decision making, e-T Guide, ICT

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Authors: Aliaksei Patsekha, Michael Hohenberger, Harald Raupenstrauch

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An effective emergency response to accidents with chemical, biological, radiological, nuclear, or explosive materials (CBRNE) that represent highly dynamic situations needs immediate actions within limited time, information and resources. The aim of the study is to provide the foundation for division of unsafe area into risk zones according to the impact of hazardous parameters (heat radiation, thermal dose, overpressure, chemical concentrations). A decision on the boundary values for three risk zones is based on the vulnerability analysis that covered a variety of accident scenarios containing the release of a toxic or flammable substance which either evaporates, ignites and/or explodes. Critical values are selected for the boundary definition of the Red, Orange and Yellow risk zones upon the examination of harmful effects that are likely to cause injuries of varying severity to people and different levels of damage to structures. The obtained results provide the basis for creating a comprehensive real-time risk map for a decision support at CBRNE operations.

Keywords: boundary values, CBRNE threats, decision making process, hazardous effects, vulnerability analysis, risk zones

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Authors: Marta Fernández Batalla, José María Santamaría García, Maria Lourdes Jiménez Rodríguez, Roberto Barchino Plata, Adriana Cercas Duque, Enrique Monsalvo San Macario

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Background: Primary Care Nursing is taking more autonomy in clinical decisions. One of the most frequent therapies to solve is related to the problems of maintaining a sufficient supply of food. Nursing diagnoses related to food are addressed by the nurse-family and community as the first responsible. Objectives and interventions are set according to each patient. To improve the goal setting and the treatment of these care problems, a technological tool is developed to help nurses. Objective: To evaluate the computational tool developed to support the clinical decision in feeding problems. Material and methods: A cross-sectional descriptive study was carried out at the Meco Health Center, Madrid, Spain. The study population consisted of four specialist nurses in primary care. These nurses tested the tool on 30 people with ‘need for nutritional therapy’. Subsequently, the usability of the tool and the satisfaction of the professional were sought. Results: A simple and convenient computational tool is designed for use. It has 3 main entrance fields: age, size, sex. The tool returns the following information: BMI (Body Mass Index) and caloric consumed by the person. The next step is the caloric calculation depending on the activity. It is possible to propose a goal of BMI or weight to achieve. With this, the amount of calories to be consumed is proposed. After using the tool, it was determined that the tool calculated the BMI and calories correctly (in 100% of clinical cases). satisfaction on nutritional assessment was ‘satisfactory’ or ‘very satisfactory’, linked to the speed of operations. As a point of improvement, the options of ‘stress factor’ linked to weekly physical activity. Conclusion: Based on the results, it is clear that the computational tools of decision support are useful in the clinic. Nurses are not only consumers of computational tools, but can develop their own tools. These technological solutions improve the effectiveness of nutrition assessment and intervention. We are currently working on improvements such as the calculation of protein percentages as a function of protein percentages as a function of stress parameters.

Keywords: feeding behavior health, nutrition therapy, primary care nursing, technology assessment

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Authors: Kamalendu Pal

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This paper describes the main features of a knowledge-based system evaluation method. System evaluation is placed in the context of a hybrid legal decision-support system, Advisory Support for Home Settlement in Divorce (ASHSD). Legal knowledge for ASHSD is represented in two forms, as rules and previously decided cases. Besides distinguishing the two different forms of knowledge representation, the paper outlines the actual use of these forms in a computational framework that is designed to generate a plausible solution for a given case, by using rule-based reasoning (RBR) and case-based reasoning (CBR) in an integrated environment. The nature of suitability assessment of a solution has been considered as a multiple criteria decision making process in ASHAD evaluation. The evaluation was performed by a combination of discussions and questionnaires with different user groups. The answers to questionnaires used in this evaluations method have been measured as a combination of linguistic variables, fuzzy numbers, and by using defuzzification process. The results show that the designed evaluation method creates suitable mechanism in order to improve the performance of the knowledge-based system.

Keywords: case-based reasoning, fuzzy number, legal decision-support system, linguistic variable, rule-based reasoning, system evaluation

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Authors: Serhat Tüzün, Tufan Demirel

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Decision Support Systems (DSS) have been investigated by researchers and technologists for more than 35 years. This paper analyses the developments in the architecture and software of these systems, provides a systematic analysis for different Web-based DSS approaches and Intelligent Decision-making Technologies (IDT), with the suggestion for future studies. Decision Support Systems literature begins with building model-oriented DSS in the late 1960s, theory developments in the 1970s, and the implementation of financial planning systems and Group DSS in the early and mid-80s. Then it documents the origins of Executive Information Systems, online analytic processing (OLAP) and Business Intelligence. The implementation of Web-based DSS occurred in the mid-1990s. With the beginning of the new millennia, intelligence is the main focus on DSS studies. Web-based technologies are having a major impact on design, development and implementation processes for all types of DSS. Web technologies are being utilized for the development of DSS tools by leading developers of decision support technologies. Major companies are encouraging its customers to port their DSS applications, such as data mining, customer relationship management (CRM) and OLAP systems, to a web-based environment. Similarly, real-time data fed from manufacturing plants are now helping floor managers make decisions regarding production adjustment to ensure that high-quality products are produced and delivered. Web-based DSS are being employed by organizations as decision aids for employees as well as customers. A common usage of Web-based DSS has been to assist customers configure product and service according to their needs. These systems allow individual customers to design their own products by choosing from a menu of attributes, components, prices and delivery options. The Intelligent Decision-making Technologies (IDT) domain is a fast growing area of research that integrates various aspects of computer science and information systems. This includes intelligent systems, intelligent technology, intelligent agents, artificial intelligence, fuzzy logic, neural networks, machine learning, knowledge discovery, computational intelligence, data science, big data analytics, inference engines, recommender systems or engines, and a variety of related disciplines. Innovative applications that emerge using IDT often have a significant impact on decision-making processes in government, industry, business, and academia in general. This is particularly pronounced in finance, accounting, healthcare, computer networks, real-time safety monitoring and crisis response systems. Similarly, IDT is commonly used in military decision-making systems, security, marketing, stock market prediction, and robotics. Even though lots of research studies have been conducted on Decision Support Systems, a systematic analysis on the subject is still missing. Because of this necessity, this paper has been prepared to search recent articles about the DSS. The literature has been deeply reviewed and by classifying previous studies according to their preferences, taxonomy for DSS has been prepared. With the aid of the taxonomic review and the recent developments over the subject, this study aims to analyze the future trends in decision support systems.

Keywords: decision support systems, intelligent decision-making, systematic analysis, taxonomic review

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Authors: Sheikh Shams Azam, Manoj Raju, Venkatesh Pagidimarri, Vamsi Kasivajjala

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Over the past decade, there has been a steep rise in the data-driven analysis in major areas of medicine, such as clinical decision support system, survival analysis, patient similarity analysis, image analytics etc. Most of the data in the field are well-structured and available in numerical or categorical formats which can be used for experiments directly. But on the opposite end of the spectrum, there exists a wide expanse of data that is intractable for direct analysis owing to its unstructured nature which can be found in the form of discharge summaries, clinical notes, procedural notes which are in human written narrative format and neither have any relational model nor any standard grammatical structure. An important step in the utilization of these texts for such studies is to transform and process the data to retrieve structured information from the haystack of irrelevant data using information retrieval and data mining techniques. To address this problem, the authors present Q-Map in this paper, which is a simple yet robust system that can sift through massive datasets with unregulated formats to retrieve structured information aggressively and efficiently. It is backed by an effective mining technique which is based on a string matching algorithm that is indexed on curated knowledge sources, that is both fast and configurable. The authors also briefly examine its comparative performance with MetaMap, one of the most reputed tools for medical concepts retrieval and present the advantages the former displays over the latter.

Keywords: information retrieval, unified medical language system, syntax based analysis, natural language processing, medical informatics

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Authors: Dina Farran, Mark Ashworth, Fiona Gaughran

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Atrial fibrillation (AF), the most prevalent cardiac arrhythmia, is associated with an increased risk of stroke, contributing to heart failure and death. In this project, we aim to improve patient safety by screening for stroke risk among people with AF and co-morbid mental illness. To do so, we started by conducting a systematic review and meta-analysis on prevalence, management, and outcomes of AF in people with Serious Mental Illness (SMI) versus the general population. We then evaluated oral anticoagulation (OAC) prescription trends in people with AF and co-morbid SMI in King’s College Hospital. We also evaluated the association between mental illness severity and OAC prescription in eligible patients in South London and Maudsley (SLaM) NHS Foundation Trust. Next, we implemented an electronic clinical decision support system (eCDSS) consisting of a visual prompt on patient electronic Personal Health Records to screen for AF-related stroke risk in three Mental Health of Older Adults wards at SLaM. Finally, we assessed the feasibility and acceptability of the eCDSS by qualitatively investigating clinicians’ perspectives of the potential usefulness of the eCDSS (pre-intervention) and their experiences and their views regarding its impact on clinicians and patients (post-intervention). The systematic review showed that people with SMI had low reported rates of AF. AF patients with SMI were less likely to receive OAC than the general population. When receiving warfarin, people with SMI, particularly bipolar disorder, experienced poor anticoagulation control compared to the general population. Meta-analysis showed that SMI was not significantly associated with an increased risk of stroke or major bleeding when adjusting for underlying risk factors. The main findings of the first observational study were that among AF patients having a high stroke risk, those with co-morbid SMI were less likely than non-SMI to be prescribed any OAC, particularly warfarin. After 2019, there was no significant difference between the two groups. In the second observational study, patients with AF and co-morbid SMI were less likely to be prescribed any OAC compared to those with dementia, substance use disorders, or common mental disorders, adjusting for age, sex, stroke, and bleeding risk scores. Among AF patients with co-morbid SMI, warfarin was less likely to be prescribed to those having alcohol or substance dependency, serious self-injury, hallucinations or delusions, and activities of daily living impairment. In the intervention, clinicians were asked to confirm the presence of AF, clinically assess stroke and bleeding risks, record risk scores in clinical notes, and refer patients at high risk of stroke to OAC clinics. Clinicians reported many potential benefits for the eCDSS, including improving clinical effectiveness, better identification of patients at risk, safer and more comprehensive care, consistency in decision making and saving time. Identified potential risks included rigidity in decision-making, overreliance, reduced critical thinking, false positive recommendations, annoyance, and increased workload. This study presents a unique opportunity to quantify AF patients with mental illness who are at high risk of severe outcomes using electronic health records. This has the potential to improve health outcomes and, therefore patients' quality of life.

Keywords: atrial fibrillation, stroke, mental health conditions, electronic clinical decision support systems

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Authors: Dimitrios J. Dimitriou, Maria F. Sartzetaki, Anastasia Kalamakidou

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Transport infrastructure assets are key components of the national asset portfolio. The decision to invest in a new infrastructure in transports could take from a few years to some decades. This is mainly because of the need to reserve and spent many capitals, the long payback period, the number of the stakeholders involved in the decision process and –many times- the investment and business risks are high. Decision makers and stakeholders need to define the framework and the outputs of the decision process taking into account the project characteristics, the business uncertainties, and the different expectations. Therefore, the decision assessment framework is an essential challenge linked with the key decision factors meet the stakeholder expectations highlighting project trade-offs, financial risks, business uncertainties and market limitations. This paper examines the decision process for new transport infrastructure projects in cross-border regions, where a wide range of stakeholders with different expectation is involved. According to a consequences analysis systemic approach, the relationship of transport infrastructure development, economic system development and stakeholder expectation is analysed. Adopting the on system of system methodological approach, the decision making the framework, variables, inputs and outputs are defined, highlighting the key shareholder’s role and expectations. The application provides the methodology outputs presenting the proposed decision framework for a strategic railway project in north Greece deals with the upgrade of the existing railway corridor connecting Greece, Turkey, and Bulgaria.

Keywords: system of system decision making, managing decisions for transport projects, decision support framework, defining decision process

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Authors: Natacha Fery, Guilherme L. Dalledonne, Xiangyang Zheng, Cheng Tang, Roberto Mayerle

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A Decision Support System (DSS) for supporting decision makers in the management of the Shandong Peninsula has been developed. Emphasis has been given to coastal protection, coastal cage aquaculture and harbors. The investigations were done in the framework of a joint research project funded by the German Ministry of Education and Research (BMBF) and the Chinese Academy of Sciences (CAS). In this paper, a description of the DSS, the development of its components, and results of its application are presented. The system integrates in-situ measurements, process-based models, and a database management system. Numerical models for the simulation of flow, waves, sediment transport and morphodynamics covering the entire Bohai Sea are set up based on the Delft3D modelling suite (Deltares). Calibration and validation of the models were realized based on the measurements of moored Acoustic Doppler Current Profilers (ADCP) and High Frequency (HF) radars. In order to enable cost-effective and scalable applications, a database management system was developed. It enhances information processing, data evaluation, and supports the generation of data products. Results of the application of the DSS to the management of coastal protection, coastal cage aquaculture and harbors are presented here. Model simulations covering the most severe storms observed during the last decades were carried out leading to an improved understanding of hydrodynamics and morphodynamics. Results helped in the identification of coastal stretches subjected to higher levels of energy and improved support for coastal protection measures.

Keywords: coastal protection, decision support system, in-situ measurements, numerical modelling

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Authors: Zhen Wu, David Lupien St-Pierre, Georges Abdul-Nour

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In decision making under strict uncertainty, decision makers have to choose a decision without any information about the states of nature. The classic criteria of Laplace, Wald, Savage, Hurwicz and Starr are introduced and compared in a case study of sewer network planning. Furthermore, results from different criteria are discussed and analyzed. Moreover, this paper discusses the idea that decision making under strict uncertainty (DMUSU) can be viewed as a two-player game and thus be solved by a solution concept in game theory: Nash equilibrium.

Keywords: decision criteria, decision making, sewer network planning, decision making, strict uncertainty

Procedia PDF Downloads 559