Search results for: healthcare costs

Authors: Alia Aldarmaki, Ahmad Elshennawy

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There is a global shift in healthcare systems’ emphasizing engaging different stakeholders in selecting quality improvement initiatives and incorporating their preferences to improve the healthcare efficiency and outcomes. Although experts bring scientific knowledge based on the scientific model and their personal experience, other stakeholders can bring new insights and information into the decision-making process. This study attempts to explore the impact of incorporating different stakeholders’ preference in identifying the most significant criteria that should be considered in healthcare for electing the improvement projects. A Framework based on a modified Fuzzy Delphi Method (FDM) was built. In addition to, the subject matter experts, doctors/physicians, nurses, administrators, and managers groups contribute to the selection process. The research identifies potential criteria for evaluating projects in healthcare, then utilizes FDM to capture expertise knowledge. The first round in FDM is intended to validate the identified list of criteria from experts; which includes collecting additional criteria from experts that the literature might have overlooked. When an acceptable level of consensus has been reached, a second round is conducted to obtain experts’ and other related stakeholders’ opinions on the appropriate weight of each criterion’s importance using linguistic variables. FDM analyses eliminate or retain the criteria to produce a final list of the critical criteria to select improvement projects in healthcare. Finally, reliability and validity were investigated using Cronbach’s alpha and factor analysis, respectively. Two case studies were carried out in a public hospital in the United Arab Emirates to test the framework. Both cases demonstrate that even though there were common criteria between the experts and the stakeholders, still stakeholders’ perceptions bring additional critical criteria into the evaluation process, which can impact the outcomes. Experts selected criteria related to strategical and managerial aspects, while the other participants preferred criteria related to social aspects such as health and safety and patients’ satisfaction. The health and safety criterion had the highest important weight in both cases. The analysis showed that Cronbach’s alpha value is 0.977 and all criteria have factor loading greater than 0.3. In conclusion, the inclusion of stakeholders’ perspectives is intended to enhance stakeholders’ engagement, improve transparency throughout the decision process, and take robust decisions.

Keywords: Fuzzy Delphi Method, fuzzy number, healthcare, stakeholders

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Authors: Lucy Ampaw-Asiedu, Terri R. Norton

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In the wake of recent disasters happening around the world such as earthquake in Italy (January, 2017); hurricanes in the United States (US) (September 2016 and September 2017); and compounding disasters in Haiti (September 2010 and September 2016); to our best knowledge, never has the world seen the need to work on preemptive rather than reactionary measures to salvage this situation than now. Tornadoes are natural hazards that mostly affect mid-western and central states in the US. Tornadoes, like all natural hazards such as hurricanes, earthquakes, floods and others, are very destructive and result in massive destruction to homes, cause billions of dollars in damage and claims many lives. Healthcare facilities in general are vulnerable to disasters, and therefore, the safety of patients, health workers and those who come in to seek shelter should be a priority. The focus of this study is to assess disaster management measures instituted by healthcare facilities. Thus, the sole aim of the study is to examine the vulnerabilities and the design of safe spaces in healthcare facilities in Central US. Objectives that guide the study are to primarily identify the impacts of tornadoes in hospitals and to assess the structural design or specifications of safe spaces. St. John’s Regional Medical Center, now Mercy Hospital in Joplin, is used as a case study. Preliminary results show that the lateral base shear of the proposed design to be 684.24 ton (1508.49kip) for the safe space. Findings from this work will be used to make recommendations about the design of safe spaces for health care facilities in Central US.

Keywords: disaster management, safe spaces, structural design, tornado, vulnerability

Procedia PDF Downloads 181

Authors: Noorulain Khalid, Unsaar Hayat, Muhammad Chaudhary, Christos Iosifidis, Felipe Dhawahir-Scala, Fiona Carley

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Dry eye disease (DED) is a common condition seen in the emergency eye department (EED) at Manchester Royal Eye Hospital (MREH). However, there is variability in the prescription of lubricating eye drops among different healthcare providers. The aim of this study was to develop an up-to-date, standardized algorithm for the prescription of lubricating eye drops in the EED at MREH based on international and national guidelines. The study also aimed to assess the impact of implementing the guideline on the rate of inappropriate lubricant prescriptions. Primarily, the impact was to be assessed in the form of the appropriateness of prescriptions for patients’ DED. The impact was secondary to be assessed through analysis of the cost to the hospital. Data from 845 patients who attended the EED over a 3-month period were analyzed, and 157 patients met the inclusion and exclusion criteria. After conducting a review of the literature and collaborating with the corneal team, an algorithm for the prescription of lubricants in the EED was developed. Three plan-do-study-act (PDSA) cycles were conducted, with interventions such as emails, posters, in-person reminders, and education for incoming trainees. The appropriateness of prescriptions was evaluated against the guidelines. Data were collected from patient records and analyzed using statistical methods. The appropriateness of prescriptions was assessed by comparing them to the guidelines and by clinical correlation with a specialized registrar. The study found a substantial improvement in the number of appropriate prescriptions, with an increase from 55% to 93% over the three PDSA cycles. There was additionally a 51% reduction in expenditure on lubricant prescriptions, resulting in cost savings for the hospital (approximate saving of £50/week). Theoretical importance: Appropriate prescription of lubricating eye drops improves disease management for patients and reduces costs for the hospital. The development and implementation of a standardized guideline facilitate the achievement of these goals. Conclusion: This study highlights the inconsistent management of DED in the EED and the potential lack of training in this area for healthcare providers. The implementation of a standardized, easy-to-follow guideline for lubricating eye drops can help to improve disease management while also resulting in cost savings for the hospital.

Keywords: lubrication, dry eye disease, guideline, prescription

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Authors: M. Nita-Lazar, E. Manea, C. Bumbac, A. Banciu, C. Stoica

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The population and economic growth have generated a significant new number of pollutant compounds which have to be degraded before reaching the environment. The wastewater treatment plants (WWTPs) have been the last barrier between the domestic and/or industrial wastewaters and the environment. At present, the conventional WWTPs have very high operational costs, most of them linked to the aeration process (60-65% from total energy costs related to wastewater treatment). In addition, they have had a low efficiency in pollutants removal such as pharmaceutical and other resilient anthropogenic compounds. In our study, we have been focused on new wastewater treatment strategies to enhance the efficiency of pollutants removal and decrease the wastewater treatment operational costs. The usage of mixed microalgae-bacteria granules technology generated high efficiency and low costs by a better harvesting and less expensive aeration. The intertrophic relationships between microalgae and bacteria have been characterized by the structure of the population community to their metabolic relationships. The results, obtained by microscopic studies, showed well-organized and stratified microalgae-bacteria granules where bacteria have been enveloped in the microalgal structures. Moreover, their population community structure has been modulated as well as their nitrification, denitrification processes (analysis based on qPCR genes expression) by the type of the pollutant compounds and amounts. In conclusion, the understanding and modulation of intertrophic relationships between microalgae and bacteria could be an economical and technological viable alternative to the conventional wastewater treatment. Acknowledgements: This research was supported by grant PN-III-P4-ID-PCE-2016-0865 from the Romanian National Authority for Scientific Research and Innovation CNCS/CCCDI-UEFISCDI.

Keywords: activated sludge, bacteria, granules, microalgae

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Authors: Durhane Wong-Rieger, Kawaldip Sehmi, Nicola Bedlington, Nicole Boice, Tamás Bereczky

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Patient-generated health data should be seen as the expression of the experience of patients, including the outcomes reflecting the impact a treatment or service had on their physical health and wellness. We discuss how the healthcare system can reach a place where digital is a determinant of health - where data is generated by patients and is respected and which acknowledges their contribution to science. We explore the biggest barriers facing this. The International Experience Exchange with Patient Organisation’s Position Paper is based on a global patient survey conducted in Q3 2021 that received 304 responses. Results were discussed and validated by the 15 patient experts and supplemented with literature research. Results are a subset of this. Our research showed patient communities want to influence how their data is generated, shared, and used. Our study concludes that a reasonable framework is needed to protect the integrity of patient data and minimise abuse, and build trust. Results also demonstrated a need for patient communities to have more influence and control over how health data is generated, shared, and used. The results clearly highlight that the community feels there is a lack of clear policies on sharing data.

Keywords: digital health, equitable access, humanise healthcare, patient data

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Authors: Yu-Hong Lin

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Background: An adverse drug reaction (ADR) reported is an injury which caused by taking medicines. Sometimes the severity of ADR reported may be minor, but sometimes it could be a life-threatening situation. In order to provide healthcare professionals as a better reference in clinical practice, we do data collection and analysis from our hospital. Methods: This was a retrospective study of ADRs reported performed from 2014 to 2015 in our hospital in Taiwan. We collected assessment items of ADRs reported, which contain gender and age, occurring sources, Anatomical Therapeutic Chemical (ATC) classification of suspected drugs, types of adverse reactions, Naranjo score calculating by Naranjo Adverse Drug Reaction Probability Scale and so on. Results: The investigation included two hundred and seven ADRs reported. Most of ADRs reported were occurring in outpatient department (92%). The average age of ADRs reported was 65.3 years. Less than 65 years of age were in the majority in this study (54%). Majority of all ADRs reported were males (51%). According to ATC classification system, the major classification of suspected drugs was cardiovascular system (19%) and antiinfectives for systemic use (18%) respectively. Among the adverse reactions, Dermatologic Effects (35%) were the major type of ADRs. Also, the major Naranjo scores of all ADRs reported ranged from 1 to 4 points (91%), which represents a possible correlation between ADRs reported and suspected drugs. Conclusions: Definitely, ADRs reported is still an extremely important information for healthcare professionals. For that reason, we put all information of ADRs reported into our hospital's computer system, and it will improve the safety of medication use. By hospital's computer system, it can remind prescribers to think of information about patient's ADRs reported. No drugs are administered without risk. Therefore, all healthcare professionals should have a responsibility to their patients, who themselves are becoming more aware of problems associated with drug therapy.

Keywords: adverse drug reaction, Taiwan, healthcare professionals, safe use of medicines

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Authors: Nadine Wills

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The whole life thinking of buildings (independent if these are commercial properties or residential properties) will raise if incentive systems are provided to investors, planners and users. The Use of Building Information Modelling (BIM)-Systems offers planners the possibility to plan and re-plan buildings for decades after a period of utilization without spending many capacities. The strategy-incentive should be to plan the building in a way that makes rescheduling possible by changing just parameters in the system and not re-planning the whole building. If users receive the chance to patient incentive systems, the building stock will have a long life period. Business models of tenant electricity or self-controlled operating costs are incentive systems for building –users to let fixed running costs decline without producing damages due to wrong purposes. BIM is the controlling body to ensure that users do not abuse the incentive solution and take negative influence on the building stock. The investor benefits from the planner’s and user’s incentives: the fact that the building becomes useful for the whole life without making unnecessary investments provides possibilities to make investments in different assets. Moreover, the investor gains the facility to achieve higher rents by merchandise the property with low operating costs. To execute BIM offers whole property life cycles.

Keywords: BIM, incentives, life cycle, sustainability

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Authors: Vasile Caunii, Andreea D. Serban, Mihaela Ivancia

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The paper presents a new approach in terms of the circular economy of technologies for feeding and aeration of accumulations and water basins for fish farming and aquaculture. Because fish is and will be one of the main foods on the planet, the use of bio-eco-technologies is a priority for all producers. The technologies proposed in the paper want to reduce by a substantial percentage the costs of operation of ponds and water accumulation, using non-polluting technologies with minimal impact on the environment. The paper proposes two innovative, intelligent systems, fully automated that use a common platform, completely eco-friendly. One system is intended to aerate the water of the fish pond, and the second is intended to feed the fish by dispersing an optimal amount of fodder, depending on population size, age and habits. Both systems use a floating platform, regenerative energy sources, are equipped with intelligent and innovative systems, and in addition to fully automated operation, significantly reduce the costs of aerating water accumulations (natural or artificial) and feeding fish. The intelligent system used for feeding, in addition, to reduce operating costs, optimizes the amount of food, thus preventing water pollution and the development of bacteria, microorganisms. The advantages of the systems are: increasing the yield of fish production, these are green installations, with zero pollutant emissions, can be arranged anywhere on the water surface, depending on the user's needs, can operate autonomously or remotely controlled, if there is a component failure, the system provides the operator with accurate data on the issue, significantly reducing maintenance costs, transmit data about the water physical and chemical parameters.

Keywords: bio-eco-technologies, economy, environment, fish

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Authors: Ali Mohammadi

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Every construction that is done, the most important part of attention for employers and contractors is its cost, and they always try to reduce costs so that they can compete in the market, so they estimate the cost of construction before starting their activities. The costs can be generally divided into four parts: the materials used, the equipment used, the manpower required, and the time required. In this article, we are trying to talk about the three items of equipment, manpower, and time, and examine how the use of apps can reduce the cost of construction, while due to various reasons, it has received less attention in the field of app design. Also, because we intend to use these apps in construction and they are used by engineers and experts, we define these apps as engineering apps because the idea of ​​their design must be by an engineer who works in that field. Also, considering that most engineers are familiar with programming during their studies, they can design the apps they need using simple programming software.

Keywords: layout, as-bilt, monitoring, maps

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Authors: Chanchai Supaartagorn

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E-retailing is the sale of goods online that takes place over the Internet. The Internet has shrunk the entire World. The world e-retailing is growing at an exponential rate in the Americas, Europe, and Asia. However, e-retailing costs require expensive investment, such as hardware, software, and security systems. Cloud computing technology is internet-based computing for the management and delivery of applications and services. Cloud-based e-retailing application models allow enterprises to lower their costs with their effective implementation of e-retailing activities. In this paper, we describe the concept of cloud computing and present the architecture of cloud computing, combining the features of e-retailing. In addition, we propose a strategy for implementing cloud computing with e-retailing. Finally, we explain the benefits from the architecture.

Keywords: architecture, cloud computing, e-retailing, internet-based

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Authors: Mahla Azimi

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Introduction: Post-bladder catheter infection is a common and significant healthcare-associated infection that affects individuals with indwelling urinary catheters. These infections can lead to various complications, including urinary tract infections (UTIs), bacteremia, sepsis, and increased morbidity and mortality rates. This article aims to provide a comprehensive review of post-bladder catheter infections, including their causes, risk factors, clinical presentation, diagnosis, treatment options, and preventive measures. Causes and Risk Factors: Post-bladder catheter infections primarily occur due to the colonization of microorganisms on the surface of the urinary catheter. The most common pathogens involved are Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa, and Enterococcus species. Several risk factors contribute to the development of these infections, such as prolonged catheterization duration, improper insertion technique, poor hygiene practices during catheter care, compromised immune system function in patients with underlying conditions or immunosuppressive therapy. Clinical Presentation: Patients with post-bladder catheter infections may present with symptoms such as fever, chills, malaise, suprapubic pain or tenderness, and cloudy or foul-smelling urine. In severe cases or when left untreated for an extended period of time, patients may develop more severe symptoms like hematuria or signs of systemic infection. Diagnosis: The diagnosis of post-bladder catheter infection involves a combination of clinical evaluation and laboratory investigations. Urinalysis is crucial in identifying pyuria (presence of white blood cells) and bacteriuria (presence of bacteria). A urine culture is performed to identify the causative organism(s) and determine its antibiotic susceptibility profile. Treatment Options: Prompt initiation of appropriate antibiotic therapy is essential in managing post-bladder catheter infections. Empirical treatment should cover common pathogens until culture results are available. The choice of antibiotics should be guided by local antibiogram data to ensure optimal therapy. In some cases, catheter removal may be necessary, especially if the infection is recurrent or associated with severe complications. Preventive Measures: Prevention plays a vital role in reducing the incidence of post-bladder catheter infections. Strategies include proper hand hygiene, aseptic technique during catheter insertion and care, regular catheter maintenance, and timely removal of unnecessary catheters. Healthcare professionals should also promote patient education regarding self-care practices and signs of infection. Conclusion: Post-bladder catheter infections are a significant healthcare concern that can lead to severe complications and increased healthcare costs. Early recognition, appropriate diagnosis, and prompt treatment are crucial in managing these infections effectively. Implementing preventive measures can significantly reduce the incidence of post-bladder catheter infections and improve patient outcomes. Further research is needed to explore novel strategies for prevention and management in this field.

Keywords: post-bladder catheter infection, urinary tract infection, bacteriuria, indwelling urinary catheters, prevention

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Authors: Yi-Fan Lin, Peter P. Howley, Frank A. Tuyl

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Quality measurement and reporting systems are used in healthcare internationally. In Australia, the Australian Council on Healthcare Standards records and reports hundreds of clinical indicators (CIs) nationally across the healthcare system. These CIs are measures of performance in the clinical setting, and are used as a screening tool to help assess whether a standard of care is being met. Existing analysis and reporting of these CIs incorporate Bayesian methods to address sampling variation; however, such assessments are retrospective in nature, reporting upon the previous six or twelve months of data. The use of Bayesian methods within statistical process control for monitoring systems is an important pursuit to support more timely decision-making. Our research has developed and assessed a new graphical monitoring tool, similar to a control chart, based on the beta-binomial posterior predictive (BBPP) distribution to facilitate the real-time assessment of health care organizational performance via CIs. The BBPP charts have been compared with the traditional Bernoulli CUSUM (BC) chart by simulation. The more traditional “central” and “highest posterior density” (HPD) interval approaches were each considered to define the limits, and the multiple charts were compared via in-control and out-of-control average run lengths (ARLs), assuming that the parameter representing the underlying CI rate (proportion of cases with an event of interest) required estimation. Preliminary results have identified that the BBPP chart with HPD-based control limits provides better out-of-control run length performance than the central interval-based and BC charts. Further, the BC chart’s performance may be improved by using Bayesian parameter estimation of the underlying CI rate.

Keywords: average run length (ARL), bernoulli cusum (BC) chart, beta binomial posterior predictive (BBPP) distribution, clinical indicator (CI), healthcare organization (HCO), highest posterior density (HPD) interval

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Authors: Usama Abdulwahab, Mohammed Wahab

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This paper presents the application of uncapacitated facility location problems (UFLP) and 1-median problems to support decision making in blood supply chain networks. A plethora of factors make blood supply-chain networks a complex, yet vital problem for the regional blood bank. These factors are rapidly increasing demand; criticality of the product; strict storage and handling requirements; and the vastness of the theater of operations. As in the UFLP, facilities can be opened at any of $m$ predefined locations with given fixed costs. Clients have to be allocated to the open facilities. In classical location models, the allocation cost is the distance between a client and an open facility. In this model, the costs are the allocation cost, transportation costs, and inventory costs. In order to address this problem the median algorithm is used to analyze inventory, evaluate supply chain status, monitor performance metrics at different levels of granularity, and detect potential problems and opportunities for improvement. The Euclidean distance data for some Ontario cities (demand nodes) are used to test the developed algorithm. Sitation software, lagrangian relaxation algorithm, and branch and bound heuristics are used to solve this model. Computational experiments confirm the efficiency of the proposed approach. Compared to the existing modeling and solution methods, the median algorithm approach not only provides a more general modeling framework but also leads to efficient solution times in general.

Keywords: approximate dynamic programming, facility location, perishable product, inventory model, blood platelet, P-median problem

Procedia PDF Downloads 482

Authors: Md. Abu Sufian, Robiqul Islam, Imam Hossain Shajid, Mahesh Hanumanthu, Jarasree Varadarajan, Md. Sipon Miah, Mingbo Niu

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Coronary Heart Disease (CHD) remains a principal cause of global morbidity and mortality, characterized by atherosclerosis—the build-up of fatty deposits inside the arteries. The study introduces an innovative methodology that leverages cloud-based platforms like AWS Live Streaming and Artificial Intelligence (AI) to early detect and prevent CHD symptoms in web applications. By employing novel simulation processes and AI algorithms, this research aims to significantly mitigate the health and societal impacts of CHD. Methodology: This study introduces a novel simulation process alongside a multi-phased model development strategy. Initially, health-related data, including heart rate variability, blood pressure, lipid profiles, and ECG readings, were collected through user interactions with web-based applications as well as API Integration. The novel simulation process involved creating synthetic datasets that mimic early-stage CHD symptoms, allowing for the refinement and training of AI algorithms under controlled conditions without compromising patient privacy. AWS Live Streaming was utilized to capture real-time health data, which was then processed and analysed using advanced AI techniques. The novel aspect of our methodology lies in the simulation of CHD symptom progression, which provides a dynamic training environment for our AI models enhancing their predictive accuracy and robustness. Model Development: it developed a machine learning model trained on both real and simulated datasets. Incorporating a variety of algorithms including neural networks and ensemble learning model to identify early signs of CHD. The model's continuous learning mechanism allows it to evolve adapting to new data inputs and improving its predictive performance over time. Results and Findings: The deployment of our model yielded promising results. In the validation phase, it achieved an accuracy of 92% in predicting early CHD symptoms surpassing existing models. The precision and recall metrics stood at 89% and 91% respectively, indicating a high level of reliability in identifying at-risk individuals. These results underscore the effectiveness of combining live data streaming with AI in the early detection of CHD. Societal Implications: The implementation of cloud-based AI for CHD symptom detection represents a significant step forward in preventive healthcare. By facilitating early intervention, this approach has the potential to reduce the incidence of CHD-related complications, decrease healthcare costs, and improve patient outcomes. Moreover, the accessibility and scalability of cloud-based solutions democratize advanced health monitoring, making it available to a broader population. This study illustrates the transformative potential of integrating technology and healthcare, setting a new standard for the early detection and management of chronic diseases.

Keywords: coronary heart disease, cloud-based ai, machine learning, novel simulation techniques, early detection, preventive healthcare

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Authors: Boukelkoul Lahcen

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The cumulative costs for O&M may represent as much as 65%-90% of the turbine's investment cost. Nowadays the cost effectiveness concept becomes a decision-making and technology evaluation metric. The cost of energy metric accounts for the effect replacement cost and unscheduled maintenance cost parameters. One key of the proposed approach is the idea of maintaining the WTs which can be captured via use of a finite state Markov chain. Such a model can be embedded within a probabilistic operation and maintenance simulation reflecting the action to be done. In this paper, an approach of estimating the cost of O&M is presented. The finite state Markov model is used for decision problems with number of determined periods (life cycle) to predict the cost according to various options of maintenance.

Keywords: cost, finite state, Markov model, operation and maintenance

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Authors: Waleerak Sittisom

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The objectives of this research were to analyze transportation route management, to identify potential cost reductions in logistic operation. In-depth interview techniques and small group discussions were utilized with 25 participants from various backgrounds in the areas of logistics. The findings of this research revealed that there were four areas that companies are able to effectively manage a logistic cost reduction: managing the space within the transportation vehicles, managing transportation personnel, managing transportation cost, and managing control of transportation. On the other hand, there were four areas that companies were unable to effectively manage a logistic cost reduction: the working process of transportation, the route planning of transportation, the service point management, and technology management. There are five areas that cost reduction is feasible: personnel management, process of working, map planning, service point planning, and technology implementation. To be able to reduce costs, the transportation companies should suggest that customers use a file system to save truck space. Also, the transportation companies need to adopt new technology to manage their information system so that packages can be reached easy, safe, and fast. Staff needs to be trained regularly to increase knowledge and skills. Teamwork is required to effectively reduce the costs.

Keywords: cost reduction, management, logistics, transportation

Procedia PDF Downloads 471

Authors: A. Shirazibeheshti, T. Radwan, A. Ettefaghian, G. Wilson, C. Luca, Farbod Khanizadeh

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Anticholinergic medication has been associated with events such as falls, delirium, and cognitive impairment in older patients. To further assess this, anticholinergic burden scores have been developed to quantify risk. A risk model based on clustering was deployed in a healthcare management system to cluster patients into multiple risk groups according to anticholinergic burden scores of multiple medicines prescribed to patients to facilitate clinical decision-making. To do so, anticholinergic burden scores of drugs were extracted from the literature, which categorizes the risk on a scale of 1 to 3. Given the patients’ prescription data on the healthcare database, a weighted anticholinergic risk score was derived per patient based on the prescription of multiple anticholinergic drugs. This study was conducted on over 300,000 records of patients currently registered with a major regional UK-based healthcare provider. The weighted risk scores were used as inputs to an unsupervised learning algorithm (mean-shift clustering) that groups patients into clusters that represent different levels of anticholinergic risk. To further evaluate the performance of the model, any association between the average risk score within each group and other factors such as socioeconomic status (i.e., Index of Multiple Deprivation) and an index of health and disability were investigated. The clustering identifies a group of 15 patients at the highest risk from multiple anticholinergic medication. Our findings also show that this group of patients is located within more deprived areas of London compared to the population of other risk groups. Furthermore, the prescription of anticholinergic medicines is more skewed to female than male patients, indicating that females are more at risk from this kind of multiple medications. The risk may be monitored and controlled in well artificial intelligence-equipped healthcare management systems.

Keywords: anticholinergic medicines, clustering, deprivation, socioeconomic status

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Authors: Ali Abdi Kordani, Meysam Rooyintan, Sid Mohammad Boroomandrad

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Nowadays, one the most important problems in megacities is public transportation and satisfying citizens from this system in order to decrease the traffic congestions and air pollution. Accordingly, to improve the transit passengers and increase the travel safety, new transportation systems such as Bus Rapid Transit (BRT), tram, and monorail have expanded that each one has different merits and demerits. That is why comparing different systems for a systematic selection of public transportation systems in a big city like Tehran, which has numerous problems in terms of traffic and pollution, is essential. In this paper, it is tried to investigate the advantages and feasibility of using monorail, tram and BRT systems, which are widely used in most of megacities in all over the world. In Tehran, by using SPSS statistical analysis software and TOPSIS method, these three modes are compared to each other and their results will be assessed. Experts, who are experienced in the transportation field, answer the prepared matrix questionnaire to select each public transportation mode (tram, monorail, and BRT). The results according to experts’ judgments represent that monorail has the first priority, Tram has the second one, and BRT has the third one according to the considered indices like execution costs, wasting time, depreciation, pollution, operation costs, travel time, passenger satisfaction, benefit to cost ratio and traffic congestion.

Keywords: BRT, costs, monorail, pollution, tram

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Authors: Wesam Darawsheh

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Background: there are scarcity of studies done to investigate the level of knowledge and the level of awareness and perception of Jordanians about occupational therapy (OT). Aim: to investigate the level of awareness of lay people, clients receiving services and healthcare professionals of OT, identify the common misconceptions about OT, and to explore ways whereby the knowledge and awareness about OT can be increased. Methodology: a cross sectional design was employed in this study where a survey was distributed in the Northern, Southern, Western, Eastern provinces and the Middle (capital city: Amman) province of Jordan. The survey consisted of eight section and 61 questions that aims to investigate the demographics of participants, self evaluation concerning knowledge and awareness about OT, sources of knowledge about OT, the perception of the aims, fields of practice, OT settings, misconceptions about OT, and suggestion to improve knowledge and awareness about OT. Results: A total of 829 participants were enrolled in this study: 459 lay people, 155 clients who are currently receiving OT services, 215 healthcare professionals. About 57% of the participants did not hear about OT, and 48% of those who reported to hear about OT did not have sufficient knowledge about it. There are several misconceptions associated with OT. The statistical analysis was executed using IBM SPSS software, Version 22.0 (SPSS, Chicago, USA). Conclusion: it is the responsibility of OTRs to increase the knowledge and awareness about OT in Jordan. This is required for the profession to proliferate and to be given its status.

Keywords: knowledge, occupational therapy misconceptions, healthcare professionals, lay people, Jordan

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Authors: Antonio Lopez-Villegas, Rafael Bautista-Mesa, Emilio Robles-Musso, Daniel Catalan-Matamoros, Cesar Leal-Costa

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Objectives: The purpose of this trial was to evaluate the burden borne by and the costs to informal caregivers of users with telemonitoring of pacemakers. Methods: This is a controlled, non-randomised clinical trial, with data collected from informal caregivers, five years after implantation of pacemakers. The Spanish version of the Survey on Disabilities, Personal Autonomy, and Dependency Situations was used to get information on clinical and social characteristics, levels of professionalism, duration and types of care, difficulties in providing care, health status, economic and job aspects, impact on the family or leisure due to informal caregiving for patients with pacemakers. Results: After five years of follow-up, 55 users with pacemakers finished the study. Of which, 50 were helped by a caregiver, 18 were included in the telemonitoring group (TM) and 32 in the conventional follow-up group (HM). Overall, females represented 96.0% of the informal caregivers (88.89% in TM and 100.0% in HM group). The mean ages were 63.17 ± 15.92 and 63.13 ± 14.56 years, respectively (p = 0.83) in the groups. The majority (88.0%) of the caregivers declared that they had to provide their services between 6 and 7 days per week (83.33% in TM group versus 90.63% in HM group), without significant differences between both groups. The costs related to care provided by the informal caregivers were 47.04% higher in the conventional follow-up group than in the TM group. Conclusions: The results of this trial confirm that there were no significant differences between the informal caregivers regarding to baseline characteristics, workload and time worked in both groups of follow-up. The costs incurred by the informal caregivers providing care for users with pacemakers included in telemonitoring group are significantly lower than those in the conventional follow-up group. Trial registration: ClinicalTrials.gov NCT02234245. Funding: The PONIENTE study, has been funded by the General Secretariat for Research, Development and Innovation, Regional Government of Andalusia (Spain), project reference number PI/0256/2017, under the research call 'Development and Innovation Projects in the Field of Biomedicine and Health Sciences', 2017.

Keywords: costs, disease burden, informal caregiving, pacemaker follow-up, remote monitoring, telemedicine

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Authors: N. M. Sani, I. Bitrus, A. M. Sarki, N. S. Mujahid

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Hepatitis is one of the neglected infectious diseases in sub Saharan Africa, and most of the available data is based on blood donors. Health care workers (HCWs) often get infected as a result of their close contact with patients. A cross-sectional study was conducted to determine the prevalence of hepatitis B and C among this group of professionals with a view to improving the quality of care to their patients. Hepatitis B and C infections pose a major public health problem worldwide. While infection is highest in the developing world particularly Asia and sub-Saharan Africa, healthcare workers are at higher risk of acquiring blood-borne viral infections, particularly Hepatitis B and C which are mostly asymptomatic. This study was aimed at determining the prevalence of Hepatitis B and C infections and associated risk factors among health care workers in Dutse Metropolis, Jigawa State - Nigeria. A standard rapid immuno-chromatographic technique i.e. rapid ELISA was used to screen all sera for Hepatitis B surface antigen (HBsAg) and Hepatitis C viral antibody (HCVAb) respectively. Strips containing coated antibodies and antigens to HBV and HCV respectively were removed from the foil. Strips were labeled according to samples. Using a separate disposable pipette, 2 drops of the sample (plasma) were added into each test strip and allowed to run across the absorbent pad. Results were read after 15 minutes. The prevalence of HBV and HCV infection in 100 healthcare workers was determined by testing the plasma collected from the clients during their normal checkup using HBsAg and HCVAb test strips. Results were subjected to statistical analysis using chi-square test. The prevalence of HBV among HCWs was 19 out of 100 (19.0%) and that of HCV was 5 out of 100 (5.0%) where in both cases, higher prevalence was observed among female nurses. It was also observed that all HCV positive cases were recorded among nurses only. The study revealed that nurses are at greater risk of contracting HBV and HCV due to their frequent contact with patients. It is therefore recommended that effective vaccination and other infection control measures be encouraged among healthcare workers.

Keywords: prevalence, hepatitis, viruses, healthcare workers, infection

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Authors: Varsha Reddy Jayar

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Background: Our elderly family members deserve our best care. It's our responsibility to ensure they're healthy and safe. The population of India is increasing rapidly. People are literally being born in the streets, and there is a high growth on taxes and healthcare costs. Indian families are challenged with taking care of everyone. When you have elderly parents and a demanding job, it can be difficult to take care of them. You might not have enough time to care for them when you're already working or dealing with emotional difficulties. Living alone in old age can cause older individuals to face many health risks. Many seniors find living and caring for themselves challenging when they live by themselves. This study explored the factors that affect whether or not elderly people choose to live in old age homes. Methods: This study was carried out on 123 elderly people living in different old age homes in Karnataka, India. The reason for their residence at the home was explored using an interview. Results: It was found that the most common reason for living in an old age home is due to abuse from children and grandchildren; the majority reported were Daughter in law issues in the family specific to the adjustment and understanding amongst them. Conclusion: More and more elderly people in India are choosing to stay in old age homes as they get older. The government and voluntary agencies must have some sort of arrangements for institutional support.

Keywords: old age home, elderly, Aging, challenges of aging

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Authors: Luciano Oliveira, Elsa Vásquez-Alvarez

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The increase in rail freight transport in Brazil in recent years requires new railway lines and the maintenance of existing ones, which generates high costs for concessionaires. It is in this context that this work is inserted, whose objective is to propose a method that uses Binary Linear Programming for the choice of sleeper and rail fastening, from various options, including the way to apply these materials, with focus to minimize costs. Unit value information, the life cycle each of material type, and service expenses are considered. The model was implemented in commercial software using real data for its validation. The formulated model can be replicated to support decision-making for other railway projects in the choice of sleepers and rail fastening with lowest cost.

Keywords: linear programming, rail fastening, rail sleeper, railway

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Authors: Emmanuel Chibuogu Asogwa, Tochukwu Sunday Belonwu

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An urgent demand for creative solutions has been created by the rapid expansion of medical knowledge, the complexity of patient care, and the requirement for more precise decision-making. As a solution to this problem, the creation of a Medical Intelligent Process Model (MIPM) utilizing ontology-based appears as a promising way to overcome this obstacle and unleash the full potential of healthcare systems. The development of a Medical Intelligent Process Model (MIPM) using ontology-based techniques is motivated by a lack of quick access to relevant medical information and advanced tools for treatment planning and clinical decision-making, which ontology-based techniques can provide. The aim of this work is to develop a structured and knowledge-driven framework that leverages ontology, a formal representation of domain knowledge, to enhance various aspects of healthcare. Object-Oriented Analysis and Design Methodology (OOADM) were adopted in the design of the system as we desired to build a usable and evolvable application. For effective implementation of this work, we used the following materials/methods/tools: the medical dataset for the test of our model in this work was obtained from Kaggle. The ontology-based technique was used with Confusion Matrix, MySQL, Python, Hypertext Markup Language (HTML), Hypertext Preprocessor (PHP), Cascaded Style Sheet (CSS), JavaScript, Dreamweaver, and Fireworks. According to test results on the new system using Confusion Matrix, both the accuracy and overall effectiveness of the medical intelligent process significantly improved by 20% compared to the previous system. Therefore, using the model is recommended for healthcare professionals.

Keywords: ontology-based, model, database, OOADM, healthcare

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Authors: Fatima Faraz

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BACKGROUND: While Artificial intelligence (AI) provides new opportunities across a wide variety of industries, healthcare is no exception. AI can lead to advancements in how the healthcare system functions and improves the quality of patient care. Developing countries like Pakistan are lagging in the implementation of AI-based solutions in healthcare. This demands increased knowledge and AI literacy among health care professionals. OBJECTIVES: To assess the level of awareness among medical students and faculty about AI in preparation for teaching AI basics and data science applications in clinical practice in an integrated medical curriculum. METHODS: An online 15-question semi-structured questionnaire, previously tested and validated, was delivered among participants through convenience sampling. The questionnaire composed of 3 parts: participant’s background knowledge, AI awareness, and attitudes toward AI applications in medicine. RESULTS: A total of 182 students and 39 faculty members from Rawalpindi Medical University, Pakistan, participated in the study. Only 26% of students and 46.2% of faculty members responded that they were aware of AI topics in clinical medicine. The major source of AI knowledge was social media (35.7%) for students and professional talks and colleagues (43.6%) for faculty members. 23.5% of participants answered that they personally had a basic understanding of AI. Students and faculty (60.1%) were interested in AI in patient care and teaching domain. These findings parallel similar published AI survey results. CONCLUSION: This survey concludes interest among students and faculty in AI developments and technology applications in healthcare. Further studies are required in order to correctly fit AI in the integrated modular curriculum of medical education.

Keywords: medical education, data science, artificial intelligence, curriculum

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Authors: Hossein Havaeji, Tony Wong, Thien-My Dao

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1. Research Problems and Research Objectives: Blockchain Technology-enabled Supply Chain System (BT-enabled SCS) is the system using BT to drive SCS transparency, security, durability, and process integrity as SCS data is not always visible, available, or trusted. The costs of operating BT in the SCS are a common problem in several organizations. The costs must be estimated as they can impact existing cost control strategies. To account for system and deployment costs, it is necessary to overcome the following hurdle. The problem is that the costs of developing and running a BT in SCS are not yet clear in most cases. Many industries aiming to use BT have special attention to the importance of BT installation cost which has a direct impact on the total costs of SCS. Predicting BT installation cost in SCS may help managers decide whether BT is to be an economic advantage. The purpose of the research is to identify some main BT installation cost components in SCS needed for deeper cost analysis. We then identify and categorize the main groups of cost components in more detail to utilize them in the prediction process. The second objective is to determine the suitable Supervised Learning technique in order to predict the costs of developing and running BT in SCS in a particular case study. The last aim is to investigate how the running BT cost can be involved in the total cost of SCS. 2. Work Performed: Applied successfully in various fields, Supervised Learning is a method to set the data frame, treat the data, and train/practice the method sort. It is a learning model directed to make predictions of an outcome measurement based on a set of unforeseen input data. The following steps must be conducted to search for the objectives of our subject. The first step is to make a literature review to identify the different cost components of BT installation in SCS. Based on the literature review, we should choose some Supervised Learning methods which are suitable for BT installation cost prediction in SCS. According to the literature review, some Supervised Learning algorithms which provide us with a powerful tool to classify BT installation components and predict BT installation cost are the Support Vector Regression (SVR) algorithm, Back Propagation (BP) neural network, and Artificial Neural Network (ANN). Choosing a case study to feed data into the models comes into the third step. Finally, we will propose the best predictive performance to find the minimum BT installation costs in SCS. 3. Expected Results and Conclusion: This study tends to propose a cost prediction of BT installation in SCS with the help of Supervised Learning algorithms. At first attempt, we will select a case study in the field of BT-enabled SCS, and then use some Supervised Learning algorithms to predict BT installation cost in SCS. We continue to find the best predictive performance for developing and running BT in SCS. Finally, the paper will be presented at the conference.

Keywords: blockchain technology, blockchain technology-enabled supply chain system, installation cost, supervised learning

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Authors: Al Huuskonen, Clio Lake, K. M. Naude, Polina Petlitsyna, Sorsha Henning, Julia Wimmers-Klick

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This project presents the outcomes of a community-based participatory action initiative aimed at advocating for equitable healthcare and human rights for trans, two-spirit, and gender-diverse individuals, building upon the University of British Columbia (UBC) Trans Coalition's ongoing efforts. Participatory Action Research (PAR) was chosen as the research method with the goal of improving trans rights on the UBC campus, particularly regarding equitable access to healthcare. PAR involves active community contribution throughout the research process, which in this case was done by way of liaising with student resource groups and advocacy leaders. The goals of this project were as follows: a) identify gaps in gender-affirming healthcare for UBC students by consulting the community and collaborating with UBC services, b) develop an information package outlining provincial and university-based health insurance for gender-affirming care (including hormone therapy and surgeries), FAQs, and resources for UBC's trans students, c) make this package available to UBC students and other national transgender advocacy organizations. The initiative successfully expanded the UBC AMS Student Health and Dental Plan to include gender-affirming procedural coverage, developed a care access guide for students, and advocated for improved health records inclusivity, mechanisms for trans students to report negative care experiences, and increased access to gender-affirming primary care through the on-campus health clinic. Collaboration with other universities' pride organizations and Trans Care BC yielded positive outcomes through broader coalition building and resource sharing. Ongoing efforts are underway to update provincial policies, particularly through expanding coverage under fair pharma care and addressing the compounding effects of the primary care crisis for trans individuals. The project's tangible results include improved trans rights on campus, especially in terms of healthcare access. Expanding healthcare coverage through student care benefits thousands of students, making the ability to undergo important affirming procedures more affordable. Providing students with information on extended coverage options and communication with their doctors further removes barriers to care and positively impacts student wellbeing. This initiative demonstrates the effectiveness of community-based participatory action in advancing equitable healthcare for trans and gender-diverse individuals and serves as a model for other institutions and organizations striving to promote inclusivity and advocate for marginalized populations' rights.

Keywords: equitable healthcare, trans and gender-diverse individuals, inclusivity, participatory action research project

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Authors: Raphaël Weuts, Mykyta Petik, Anton Vedder

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Artificial Intelligence has the potential to create and already creates enormous value in healthcare. Prescriptive systems might be able to make the use of healthcare capacity more efficient. Such systems might entail interpretations that exclude the effect of confounders that brings risks with it. Those risks might be mitigated by regulation that prevents systems entailing such risks to come to market. One modality of regulation is that of legislation, and the European AI Act is an example of such a regulatory instrument that might mitigate these risks. To assess the risk mitigation potential of the AI Act for those risks, this research focusses on a case study of a hypothetical application of medical device software that entails the aforementioned risks. The AI Act refers to the harmonised norms for already existing legislation, here being the European medical device regulation. The issue at hand is a causal link between a confounder and the value the algorithm optimises for by proxy. The research identifies where the AI Act already looks at confounders (i.a. feedback loops in systems that continue to learn after being placed on the market). The research identifies where the current proposal by parliament leaves legal uncertainty on the necessity to check for confounders that do not influence the input of the system, when the system does not continue to learn after being placed on the market. The authors propose an amendment to article 15 of the AI Act that would require high-risk systems to be developed in such a way as to mitigate risks from those aforementioned confounders.

Keywords: AI Act, healthcare, confounders, risks

Procedia PDF Downloads 234

Authors: Hung-Chi Chang

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For an extended EPQ model with random yield, the existent study revealed that both the disaggregating and consolidating shipment policies for the imperfect quality items are independent of holding cost, and recommended a model with economic benefit by comparing the least total cost for each of the three models investigated. To better capture the real situation, we generalize the existent study to include different holding costs for perfect and imperfect quality items. Through analysis, we show that the above shipment policies are dependent on holding costs. Furthermore, we derive a simple decision rule solely based on the thresholds of problem parameters to select a superior model. The results are illustrated analytically and numerically.

Keywords: consolidating shipments, disaggregating shipments, EPQ, imperfect quality, inventory

Procedia PDF Downloads 349

Authors: Nizar Ghali, Bernard Fortin, Guy Lacroix

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In Quebec, colonoscopies volumes have continued to rise in recent years in the absence of effective monitoring mechanism for the appropriateness and the quality of these exams. In 2010, November, Quebec Government introduced the colorectal cancer-screening program in the objective to control for volume and cost imperfection. This program is based on clinical standards and was initiated for first group of institutions. One year later, Government adds financial incentives for participants institutions. In this analysis, we want to assess for the causal effect of the two components of this program: clinical pathways and financial incentives. Especially we assess for the reform effect on healthcare quality and population health in the context that medical remuneration is not directly dependent on this additional funding offered by the program. We have data on admissions episodes and deaths for 8 years. We use multistate model analog to difference in difference approach to estimate reform effect on the transition probability between different states for each patient. Our results show that the reform reduced length of stay without deterioration in hospital mortality or readmission rate. In the other hand, the program contributed to decrease the hospitalization rate and a less invasive treatment approach for colorectal surgeries. This is a sign of healthcare quality and population health improvement. We demonstrate in this analysis that physicians’ behavior can be affected by both clinical standards and financial incentives even if offered to facilities.

Keywords: multi-state and multi-episode transition model, healthcare quality, length of stay, transition probability, difference in difference

Procedia PDF Downloads 191