Search results for: preventive healthcare

Authors: Mingyang Sun, Guozheng Yan, Dasheng Liu, Lei Yang

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Driven by the demand of intelligent monitoring in rehabilitation centers or hospitals, a high accuracy real-time location system based on UWB (ultra-wideband) technology was proposed. The system measures precise location of a specific person, traces his movement and visualizes his trajectory on the screen for doctors or administrators. Therefore, doctors could view the position of the patient at any time and find them immediately and exactly when something emergent happens. In our design process, different algorithms were discussed, and their errors were analyzed. In addition, we discussed about a , simple but effective way of correcting the antenna delay error, which turned out to be effective. By choosing the best algorithm and correcting errors with corresponding methods, the system attained a good accuracy. Experiments indicated that the ranging error of the system is lower than 7 cm, the locating error is lower than 20 cm, and the refresh rate exceeds 5 times per second. In future works, by embedding the system in wearable IoT (Internet of Things) devices, it could provide not only physical parameters, but also the activity status of the patient, which would help doctors a lot in performing healthcare.

Keywords: intelligent monitoring, ultra-wideband technology, real-time location, IoT devices, smart healthcare

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Authors: Etta Conteh, Tracy Macintosh

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Introduction: Restraints are often used in the Emergency Department when it is necessary for a patient to be restrained in order to decrease their agitation and better treat them. Chemical and physical restraints may be used on these patients at the discretion of the medical provider. Racism and injustice are rampant within our country, and medicine and healthcare are not spared. While racism and racial bias in medicine and healthcare have been studied, information on the differences in the use of restraints by race are scarce. Objective: The objective of this study is to determine if African Americans and Hispanic-American patients are restrained at higher rates compared to their White counterparts. Methods: This study will be carried out through a retrospective analysis utilizing the Hospital Corporation of America (HCA) national Emergency Department (ED) and inpatient database with patient visits from 2016-2019. All patient visits, with patients aged 18 years or older, will be reviewed, looking specifically for the race and the use and type of restraints. Other factors, such a pre-existing psychiatric condition, will be used for sub-analysis. Rationale: The outcome of this project will demonstrate the absence or presence of a racial disparity in the use of restraints in the Emergency Department. These results can be used as a foundation for improving racial equity in healthcare treatment.

Keywords: emergency medicine, public health, racism, restraint use

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Authors: Esther M. Folarin, Evans Osabuohien, Ademola Onabote

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Agriculture constitutes an important part of development and poverty mitigation in lower-middle-income countries, like Nigeria. The level of agricultural productivity in the Nigerian economy in line with the level of demand necessary to meet the desired expectation of the Nigerian populace is threatening to meeting the standard of the United Nations (UN) Sustainable Development Goals (SDGs); This includes the SDG-2 (achieve food security through agricultural productivity). The overall objective of the study is to reveal the performance of the interaction variable in the model among other factors that help in the achievement of greater Nigerian agricultural productivity. The study makes use of Wave 4 (2018/2019) of the Living Standard Measurement Studies, Integrated Survey on Agriculture (LSMS-ISA). Qualitative analysis of the information was also used to provide complimentary answers to the quantitative analysis done in the study. The study employed human capital theory and Grossman’s theory of health Demand in explaining the relationships that exist between the variables within the model of the study. The study engages the Instrumental Variable Regression technique in achieving the broad objectives among other techniques for the other specific objectives. The estimation results show that there exists a positive relationship between female healthcare and the level of female agricultural productivity in Nigeria. In conclusion, the study emphasises the need for more provision and empowerment for greater female access to healthcare and educational attainment levels that aids higher female agricultural productivity and consequently an improvement in the total agricultural productivity of the Nigerian economy.

Keywords: agricultural productivity, education, female, healthcare, investment

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Authors: Sulaiman D. Al Sabei, Amy M. Ross, Christopher S. Lee

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Nurse leaders play a fundamental role in transforming healthcare system and improving quality of patient care. Several healthcare organizations have called to increase the number of nurse leaders across all levels and in every practice setting. Identification of factors influencing nurses’ willingness to lead can inform healthcare leaders and policy makers of potentially illuminating strategies for establishing favorable work environments that motivate nurses to engage in leadership roles. The aim of this study was to investigate determinants of nurses’ willingness to engage in future leadership roles. The study was conducted at a public hospital in the Sultanate of Oman. A total of 171 registered nurses participated. A multilevel modeling was conducted. Findings revealed that 80% of nurses were likely to seek out opportunities to engage in leadership roles. The quality of the nurse-physician collegial relationships was a significant predictor of nurses’ willingness to lead. Establishing a work environment’s culture of positive nurse-physician relationships is critical to enhance nurses’ work attitude and engage them in leadership roles.

Keywords: interprofessional relationship, leadership, motivation, nurses

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Authors: Sohail Imran, Tariq Mahmood

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In complex healthcare diagnostic investigation process, medical practitioners have to focus on ways to standardize their processes to perform high quality care and optimize the time and costs. Process mining techniques can be applied to extract process related knowledge from data without considering causal and dynamic dependencies in business domain and processes. The application of process mining is effective in diagnostic investigation. It is very helpful where a treatment gives no dispositive evidence favoring it. In this paper, we applied process mining to discover important process flow of diagnostic investigation for hepatitis patients. This approach has some benefits which can enhance the quality and efficiency of diagnostic investigation processes.

Keywords: process mining, healthcare, diagnostic investigation process, process flow

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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

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Authors: Valentina Manna, Oscar Pisanti

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The term sibling has been adopted by Italian brothers and sisters of people with disabilities, to define themselves as a group with shared features. This choice is due to the importance of underlying the centrality of what being a brother/sister means to these people because of and beyond the disability. Being a sibling offers great opportunities to develop empathy and relational skills but it may also amplify the typical dynamics of fraternal relationships dealing with envy, rivalry and concern. This outlines a condition of potential developmental risk for the non-disabled sibling, being at the same time a great resource for the child with special needs, as actor of an intimate relationship usually lasting after that one with parents. However, young siblings are often unheeded in their needs for comprehension of disability and not considered as persons requiring attention themselves. Moreover, scholars have scarcely undertaken an exploration of siblings’ perspective as competent contributors for producing knowledge useful to the benefit of families with special needs children. This contribution describes a preventive intervention for young siblings (6 – 16 years) of children with Down syndrome, by means of a psychodynamic-oriented group where participants could communicate, explore and share their emotional experiences as siblings. Based on a participatory approach, the program represents an action-research project, involving siblings as key experts for our understanding of siblings’ lives. The initiative used social media and video technologies to rise children’s voice: as a final product, participants were involved in the realization of a video campaign –which they defined ‘a difficult advertising’– built on the insights generated by the program and addressed to other siblings to help them facing and recognizing resources and difficulties related to their status. The final video campaign realized by the participants summarizes the main themes emerged during the intervention; as revealed by a thematic analysis, they are related to the difficulty in feeling to have a personal identity, to face disability as a form of ‘untought known’ and to integrate ambivalent emotions. In conclusion, the group device revealed its efficacy as a preventive tool: it allowed participants to deeply reflect on their own experiences and to communicate them for the first time in a verbal and mentalized form.

Keywords: down syndrome, group, siblings, prevention

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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: Junqi Zou

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As one of the world’s most tech-ready countries, Singapore has initiated the Smart Nation plan to harness the full power and potential of digital technologies to transform the way people live and work, through the more efficient government and business processes, to make the economy more productive. The key evolutions of digital technology transformation in healthcare and the increasing deployment of Internet of Things (IoTs), Big Data, AI/cognitive, Robotic Process Automation (RPA), Electronic Health Record Systems (EHR), Electronic Medical Record Systems (EMR), Warehouse Management System (WMS in the most recent decade have significantly stepped up the move towards an information-driven healthcare ecosystem. The advances in information technology not only bring benefits to patients but also act as a key force in changing management accounting in healthcare sector. The aim of this study is to investigate the impacts of digital technology transformation on Singapore’s healthcare sector from a management accounting perspective. Adopting a Balanced Scorecard (BSC) analysis approach, this paper conducted an exploratory case study of a newly launched Singapore public hospital, which has been recognized as amongst the most digitally advanced healthcare facilities in Asia-Pacific region. Specifically, this study gains insights on how the new technology is changing healthcare organizations’ management accounting from four perspectives under the Balanced Scorecard approach, 1) Financial Perspective, 2) Customer (Patient) Perspective, 3) Internal Processes Perspective, and 4) Learning and Growth Perspective. Based on a thorough review of archival records from the government and public, and the interview reports with the hospital’s CIO, this study finds the improvements from all the four perspectives under the Balanced Scorecard framework as follows: 1) Learning and Growth Perspective: The Government (Ministry of Health) works with the hospital to open up multiple training pathways to health professionals that upgrade and develops new IT skills among the healthcare workforce to support the transformation of healthcare services. 2) Internal Process Perspective: The hospital achieved digital transformation through Project OneCare to integrate clinical, operational, and administrative information systems (e.g., EHR, EMR, WMS, EPIB, RTLS) that enable the seamless flow of data and the implementation of JIT system to help the hospital operate more effectively and efficiently. 3) Customer Perspective: The fully integrated EMR suite enhances the patient’s experiences by achieving the 5 Rights (Right Patient, Right Data, Right Device, Right Entry and Right Time). 4) Financial Perspective: Cost savings are achieved from improved inventory management and effective supply chain management. The use of process automation also results in a reduction of manpower costs and logistics cost. To summarize, these improvements identified under the Balanced Scorecard framework confirm the success of utilizing the integration of advanced ICT to enhance healthcare organization’s customer service, productivity efficiency, and cost savings. Moreover, the Big Data generated from this integrated EMR system can be particularly useful in aiding management control system to optimize decision making and strategic planning. To conclude, the new digital technology transformation has moved the usefulness of management accounting to both financial and non-financial dimensions with new heights in the area of healthcare management.

Keywords: balanced scorecard, digital technology transformation, healthcare ecosystem, integrated information system

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Authors: Issa M. Hweidi, Saba W. Al-Ibraheem

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This study aimed to assess the increased hospital length of stay and healthcare costs associated with SSIs among ventriculoperitoneal shunting surgery patients in Jordan. This study adopted a retrospective and nested 1:1 matched case-control design. A non-probability convenient sample of 48 VP shunt patients was recruited for the purpose of the study. The targeted groups of the study basically used to cross-match the variables investigated to minimize the risk of confounding. Information was extracted from the text of patients' electronic health records. As compared to the non-SSI group, the SSI group had an extra mean healthcare cost of $13,696.53 (p=0.001) and longer hospital length of stay (22.64 mean additional days). Furthermore, Acinetobacter baumannii and Klebsiella pneumonia were identified as being the most predominant causative agents of SSIs. The results of this study may provide baseline data for national and regional benchmarking to evaluate the quality of care provided to likewise patients. Adherence to infection control strategies and protocols considering new surveillance methods of SSIs is encouraged.

Keywords: ventriculoperitoneal shunt, health care cost, length of stay, neurosurgery, surgical site infections

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Authors: A. Anastasiou, K. S. Tingay

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Background: Discovering suitable datasets is an important part of health research, particularly for projects working with clinical data from patients organized in cohorts (cohort data), but with the proliferation of so many national and international initiatives, it is becoming increasingly difficult for research teams to locate real world datasets that are most relevant to their project objectives. We present a method for identifying healthcare institutes in the European Union (EU) which may hold haemato-oncology (HO) data. A key enabler of this research was the bibInsight platform, a scientometric data management and analysis system developed by the authors at Swansea University. Method: A PubMed search was conducted using HO clinical terms taken from previous work. The resulting XML file was processed using the bibInsight platform, linking affiliations to the Global Research Identifier Database (GRID). GRID is an international, standardized list of institutions, including the city and country in which the institution exists, as well as a category of the main business type, e.g., Academic, Healthcare, Government, Company. Countries were limited to the 28 current EU members, and institute type to 'Healthcare'. An article was considered valid if at least one author was affiliated with an EU-based healthcare institute. Results: The PubMed search produced 21,310 articles, consisting of 9,885 distinct affiliations with correspondence in GRID. Of these articles, 760 were from EU countries, and 390 of these were healthcare institutes. One affiliation was excluded as being a veterinary hospital. Two EU countries did not have any publications in our analysis dataset. The results were analysed by country and by individual healthcare institute. Networks both within the EU and internationally show institutional collaborations, which may suggest a willingness to share data for research purposes. Geographical mapping can ensure that data has broad population coverage. Collaborations with industry or government may exclude healthcare institutes that may have embargos or additional costs associated with data access. Conclusions: Data reuse is becoming increasingly important both for ensuring the validity of results, and economy of available resources. The ability to identify potential, specific data sources from over twenty thousand articles in less than an hour could assist in improving knowledge of, and access to, data sources. As our method has not yet specified if these healthcare institutes are holding data, or merely publishing on that topic, future work will involve text mining of data-specific concordant terms to identify numbers of participants, demographics, study methodologies, and sub-topics of interest.

Keywords: data reuse, data discovery, data linkage, journal articles, text mining

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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: Walter Bernhofer, Peter Haber, Tobias Mayer, Manfred Mayr, Markus Ziegler

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Current preventive maintenance measures are cost intensive and not efficient. With the available sensor data of state of the art internet of things devices new possibilities of automated data processing emerge. Current advances in data science and in machine learning enable new, so called predictive maintenance technologies, which empower data scientists to forecast possible system failures. The goal of this approach is to cut expenses in preventive maintenance by automating the detection of possible failures and to improve efficiency and quality of maintenance measures. Additionally, a centralization of the sensor data monitoring can be achieved by using this approach. This paper describes the approach of three students to define a reference architecture for a predictive maintenance solution in the internet of things domain with a connected smartphone app for service technicians. The reference architecture is validated by a case study. The case study is implemented with current Microsoft Azure cloud technologies. The results of the case study show that the reference architecture is valid and can be used to achieve a system for predictive maintenance execution with the cloud components of Microsoft Azure. The used concepts are technology platform agnostic and can be reused in many different cloud platforms. The reference architecture is valid and can be used in many use cases, like gas station maintenance, elevator maintenance and many more.

Keywords: case study, internet of things, predictive maintenance, reference architecture

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Authors: Amiraa Ali Mansor, Haslinda Abdullah, Angela Chan Nguk Fong, Norhaida Hanim Binti Ahmad Tajudin, Asnarulkhadi Abu Samah

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Obesity has risen sharply over the past three decades, posing a grave public health concern globally. In Malaysia, it has also emerged as a significant health threat. While the second Sustainable Development Goal, "Zero Hunger", aims to ensure equitable access to nutritious food for all, a key challenge lies in addressing food insecurity. Food insecurity not only pertains to the quantity but also the quality of food, with both dimensions playing a pivotal role in health outcomes. To date, much of the research on food security has focused on household levels. There remains a research gap concerning university students, a population transitioning to independence from parental support and grappling with limited resources. This study seeks to bridge this gap by extending the Food Security Theory to incorporate the psychological dimension of self-esteem. Using a quantitative approach, data was collected from 452 public university students in Malaysia through a cross-sectional research design and a multi-stage cluster sampling technique. The anticipated findings will provide novel insights by linking food security with self-esteem. Such insights have implications for healthcare policy and the framing of preventive strategies against obesity. It is hoped that this research will not only contribute to the academic discourse on Food Security Theory but also serve as a foundation for refining national health policies and programs aimed at fostering a healthier lifestyle.

Keywords: obesity, food security, body image, self-esteem

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Authors: Muhammad Saad Aslam

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In 2021, our organization has launched our proprietary mobile App i.e. Farm Intelligence platform, an industrial-first precision agriculture solution, to Pakistan. It was piloted at 47 locations (spanning around 1,200 hectares of land), addressing growers’ pain points by bringing the benefits of precision agriculture to their doorsteps. This year, we have extended its reach by more than 10 times (nearly 130,000 hectares of land) in almost 600 locations across the country. The project team selected highly infested areas to set up traps, which then enabled the sales team to initiate evidence-based conversations with the grower community about preventive crop protection products that includes pesticides and insecticides. Mega farmer meeting field visits and demonstrations plots coupled with extensive marketing activities, were setup to include farmer community. With the help of App real-time pest monitoring (using heat maps and infestation prediction through predictive analytics) we have equipped our growers with on spot insights that will help them optimize pesticide applications. Heat maps allow growers to identify infestation hot spots to fine-tune pesticide delivery, while predictive analytics enable preventive application of pesticides before the situation escalates. Ultimately, they empower growers to keep their crops safe for a healthy harvest.

Keywords: precision pest management, precision agriculture, real time pest tracking, pest forecasting

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Authors: Nabil Hameed Al-Farsi

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This study’s main goal is to develop a model and a maintenance strategy for a cement factory called Arabian Cement Company, Rabigh Plant. The proposed work here depends on Reliability centric maintenance approach to develop a strategy and maintenance schedule that ensures increasing the reliability of the production system components, thus ensuring continuous productivity. The cost-effective maintenance of the plant’s dependability performance is the key goal of durability-based maintenance is. The cement plant consists of 7 important steps, so, developing a maintenance plan based on Reliability centric maintenance (RCM) method is made up of 10 steps accordingly starting from selecting units and data until performing and updating the model. The processing unit chosen for the analysis of this case is the calcinatory unit regarding model’s validation and the Travancore Titanium Products Ltd (TTP) using the claimed data history acquired from the maintenance department maintenance from the mentioned company. After applying the proposed model, the results of the maintenance simulation justified the plant's existing scheduled maintenance policy being reconsidered. Results represent the need for preventive maintenance for all Class A criticality equipment instead of the planned maintenance and the breakdown one for all other equipment depends on its criticality and an FMEA report. Consequently, the additional cost of preventive maintenance would be offset by the cost savings from breakdown maintenance for the remaining equipment.

Keywords: engineering, reliability, strategy, maintenance, failure modes, effects and criticality analysis (FMEA)

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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: 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: 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: 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: Sonia Butalia, Huong Luu, Alexis Guigue, Karen J. B. Martins, Khanh Vu, Scott W. Klarenbach

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Obesity-related health conditions impose a substantial economic burden on payers due to increased healthcare use. Estimates of healthcare resource use and costs associated with obesity-related comorbidities are needed to inform policies and interventions targeting these conditions. Methods: Adults living with obesity were identified (a procedure-related body mass index code for class 2/3 obesity between 2012 and 2019 in Alberta, Canada; excluding those with bariatric surgery), and outcomes were compared over 1-year (2019/2020) between those who had and did not have specific obesity-related comorbidities. The probability of using a healthcare service (based on the odds ratio of a zero [OR-zero] cost) was compared; 95% confidence intervals (CI) were reported. Logistic regression and a generalized linear model with log link and gamma distribution were used for total healthcare cost comparisons ($CDN); cost ratios and estimated cost differences (95% CI) were reported. Potential socio-demographic and clinical confounders were adjusted for, and incremental cost differences were representative of a referent case. Results: A total of 220,190 adults living with obesity were included; 44% had hypertension, 25% had osteoarthritis, 24% had type-2 diabetes, 17% had cardiovascular disease, 12% had insulin resistance, 9% had chronic back pain, and 4% of females had polycystic ovarian syndrome (PCOS). The probability of hospitalization, ED visit, and ambulatory care was higher in those with a following obesity-related comorbidity versus those without: chronic back pain (hospitalization: 1.8-times [OR-zero: 0.57 [0.55/0.59]] / ED visit: 1.9-times [OR-zero: 0.54 [0.53/0.56]] / ambulatory care visit: 2.4-times [OR-zero: 0.41 [0.40/0.43]]), cardiovascular disease (2.7-times [OR-zero: 0.37 [0.36/0.38]] / 1.9-times [OR-zero: 0.52 [0.51/0.53]] / 2.8-times [OR-zero: 0.36 [0.35/0.36]]), osteoarthritis (2.0-times [OR-zero: 0.51 [0.50/0.53]] / 1.4-times [OR-zero: 0.74 [0.73/0.76]] / 2.5-times [OR-zero: 0.40 [0.40/0.41]]), type-2 diabetes (1.9-times [OR-zero: 0.54 [0.52/0.55]] / 1.4-times [OR-zero: 0.72 [0.70/0.73]] / 2.1-times [OR-zero: 0.47 [0.46/0.47]]), hypertension (1.8-times [OR-zero: 0.56 [0.54/0.57]] / 1.3-times [OR-zero: 0.79 [0.77/0.80]] / 2.2-times [OR-zero: 0.46 [0.45/0.47]]), PCOS (not significant / 1.2-times [OR-zero: 0.83 [0.79/0.88]] / not significant), and insulin resistance (1.1-times [OR-zero: 0.88 [0.84/0.91]] / 1.1-times [OR-zero: 0.92 [0.89/0.94]] / 1.8-times [OR-zero: 0.56 [0.54/0.57]]). After fully adjusting for potential confounders, the total healthcare cost ratio was higher in those with a following obesity-related comorbidity versus those without: chronic back pain (1.54-times [1.51/1.56]), cardiovascular disease (1.45-times [1.43/1.47]), osteoarthritis (1.36-times [1.35/1.38]), type-2 diabetes (1.30-times [1.28/1.31]), hypertension (1.27-times [1.26/1.28]), PCOS (1.08-times [1.05/1.11]), and insulin resistance (1.03-times [1.01/1.04]). Conclusions: Adults with obesity who have specific disease-related health conditions have a higher probability of healthcare use and incur greater costs than those without specific comorbidities; incremental costs are larger when other obesity-related health conditions are not adjusted for. In a specific referent case, hypertension was costliest (44% had this condition with an additional annual cost of $715 [$678/$753]). If these findings hold for the Canadian population, hypertension in persons with obesity represents an estimated additional annual healthcare cost of $2.5 billion among adults living with obesity (based on an adult obesity rate of 26%). Results of this study can inform decision making on investment in interventions that are effective in treating obesity and its complications.

Keywords: administrative data, healthcare cost, obesity-related comorbidities, real world evidence

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Authors: Aghasadeghi MR., Bahramali G., Sadat SM., Sadeghi SA., Yousefi M., Khodaei K., Ghorbani M., Sadat Larijani M.

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Background:The emerging COVID-19 pandemic is a serious concernfor the public health worldwide. Despite the many mutations in the virus genome, it is important to find an effective vaccine against viral mutations. Therefore, in current study, we aimed at immunoinformatic evaluation of the virus proteins immunogenicity to design a preventive vaccine candidate, which could elicit humoral and cellular immune responses as well. Methods:Three antigenic regions are included;Spike, Membrane, and Nucleocapsid amino acid sequences were obtained, and possible fusion proteins were assessed andcompared by immunogenicity, structural features, and population coverage. The best fusion protein was also evaluated for MHC-I and MHC-II T-cell epitopes and the linear and conformational B-cell epitopes. Results: Among the four predicted models, the truncated Spike protein in fusion with M and N proteins is composed of 24 highly immunogenic human MHC class I and 29 MHC class II, along with 14 B-cell linear and 61 discontinues epitopes. Also, the selected protein has high antigenicity and acceptable population coverage of 82.95% in Iran and 92.51% in Europe. Conclusion: The data indicate that the truncated Spike-M-N SARS-CoV-2form which could be potential targets of neutralizing antibodies. The protein also has the ability to stimulate humoral and cellular immunity. The in silico study provided the fusion protein as a potential preventive vaccine candidate for further in vivo evaluation.

Keywords: SARS-CoV-2, immunoinformatic, protein, vaccine

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Authors: Noor A. Hakim

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Several studies in the developed countries investigated the prevalence of diabetes and obesity among individuals from different socioeconomic levels and suggested lower rates among the higher socioeconomic groups. However, studies evaluating diabetes risk and prevalence of obesity among the population of middle- to high-income status in developing countries are limited. The aim of this study is to evaluate the risk of developing type-2 diabetes mellitus (T2DM) and the weight status of female students in private universities in Jeddah City, Saudi Arabia. This is a cross-sectional study of 121 female students aged ≤ 25 years old was conducted; participants were recruited from two private universities. Diabetes risk was evaluated using the Finnish Diabetes Risk Score. Anthropometric measurements were assessed, and body-mass-index (BMI) was calculated. Diabetes risk scores indicated that 35.5% of the female students had a slightly elevated risk, and 10.8% had a moderate to high risk to develop T2DM. One-third of the females (29.7%) were overweight or obese. The majority of the normal weight and underweight groups were classified to have a low risk of diabetes, 22.2% of the overweight participants were classified to have moderate to high risk, and over half of the obese participants (55.5%) were classified to be at the moderate to high-risk category. Conclusions: Given that diabetes risk is alarming among the population in Saudi Arabia, healthcare providers should utilize a simple screening tool to identify high-risk individuals and initiate diabetes preventive strategies to prevent, or delay, the onset of T2DM and improve the quality of life.

Keywords: risk of type 2 diabetes, weight status, college students, socioeconomic status

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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 259

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

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Authors: Aykut Bedük, Kemalettin Eryeşil, Osman Eşmen

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The aim of this study is to examine the relationship between organizational commitment which is defined as a strong belief in and acceptance of the organization’s goals and values, and burnout syndrome and organizational cynicism. Accordingly, a field research based on survey method was conducted on the employees of a health institution operating in the province of Konya. The findings of the research show that there is a positive statistically significant relationship between organizational cynicism and burnout while there is a negative statistically significant relationship between organizational commitment and burnout. Furthermore, it has been also realized that there is a negative and statistically significant relationship between organizational commitment and organizational cynicism.

Keywords: burnout, organizational commitment, organizational cynicism, healthcare management

Procedia PDF Downloads 277