Search results for: healthcare

Authors: Hussain Darraj

Abstract:

Background: Healthcare workers, especially nurses, are subjected to a great risk of psychological stress, mostly moral distress. Therefore, it is crucial to address moral distress in nurses. Objectives: The aim of this study is to study the extent of moral distress among hospital nurses in Jazan. Methods: This study used a cross-sectional study design, which included 419 nurses from Jazan hospitals. A questionnaire was used to measure moral distress and its related factors. Results: The average total score for moral distress among the study participants is 134.14, with a standard deviation of 53.94. Moreover, the current study findings indicate that those over the age of 35 years who work as nurse managers, working in critical departments, have the intention to leave a position, have received ethical training or workshops, have provided care for COVID-19 cases, or work in a department with staff shortages are associated with the experience of higher-level moral stress. Conclusion: Nurses are recommended to be provided with ongoing education and resources in order to reduce moral distress and create a positive work atmosphere for nurses. Moreover, the current study sheds light on the importance of organizational support to provide enough resources and staffing in order to reduce moral distress among nurses. Further research is needed to focus on other health professionals and moral distress. Moreover, future studies are also required to explore the strategies to reduce moral distress levels among nurses.

Keywords: moral distress, Jazan, nurses, hospital

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Authors: Claire Song

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Background: TikTok is an emerging social media platform creating an outlet for nurses to express and communicate their nursing experiences and stress related to nursing. Purpose: This study investigates the lived experiences of nursing burnout shared on TikTok. Method: The cross-sectional content analysis examines the video content, format, type, and quantitative indicators, including the number of likes and comments. Results: A total of 35 videos and 18616 comments were examined, published between November 2020 and May 2023. Combined, these 35 videos received 24859 comments and 1159669 of likes. Most of the videos included nurses, and 12 included nurses in professional attire. Three videos included interviewers in the video, but the rest of the videos were self-recorded. Four themes of nurses’ burnout experiences were identified: 1) high-intensity work environment, 2) negative internal perception, 3) culture of nursing work, and 4) poor teamwork experience. Conclusion: This study explored the description of nurses’ burnout experiences via a creative platform. Social media, such as TikTok, is a valuable outlet for healthcare providers to express and share their experiences. Future research might consider using the social media platform to explore coping strategies and resilience in nurses who experienced burnout.

Keywords: burnout, emotional wellbeing, nursing, social media

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Authors: Aditya Karade, Sharada Falane, Dhananjay Deshmukh, Vijaykumar Mantri

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Brain tumors pose a significant challenge in healthcare due to their complex nature and impact on patient outcomes. The application of deep learning (DL) algorithms in medical imaging have shown promise in accurate and efficient brain tumour detection. This paper explores the performance of various pre-trained DL models ResNet50, Xception, InceptionV3, EfficientNetB0, DenseNet121, NASNetMobile, VGG19, VGG16, and MobileNet on a brain tumour dataset sourced from Figshare. The dataset consists of MRI scans categorizing different types of brain tumours, including meningioma, pituitary, glioma, and no tumour. The study involves a comprehensive evaluation of these models’ accuracy and effectiveness in classifying brain tumour images. Data preprocessing, augmentation, and finetuning techniques are employed to optimize model performance. Among the evaluated deep learning models for brain tumour detection, ResNet50 emerges as the top performer with an accuracy of 98.86%. Following closely is Xception, exhibiting a strong accuracy of 97.33%. These models showcase robust capabilities in accurately classifying brain tumour images. On the other end of the spectrum, VGG16 trails with the lowest accuracy at 89.02%.

Keywords: brain tumour, MRI image, detecting and classifying tumour, pre-trained models, transfer learning, image segmentation, data augmentation

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Authors: Mohammad Tahir Yousafzai, Amna Rehana Siddiqui, Naveed Zafar Janjua

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We assessed the frequency and predictors of sharp injuries (SIs) among health care workers (HCWs) at first level care facilities (FLCF) in rural Pakistan. HCWs working at public clinic (PC), privately owned licensed practitioners’ clinic (LPC) and non-licensed practitioners’ clinic (NLC) were interviewed on universal precautions (UPs) and constructs of health belief model (HBM) to assess their association with SIs through negative-binomial regression. From 365 clinics, 485 HCWs were interviewed. Overall annual rate of Sis was 192/100 HCWs/year; 78/100 HCWs among licensed prescribers, 191/100 HCWs among non-licensed prescribers, 248/100 HCWs among qualified assistants, and 321/100 HCWs among non-qualified assistants. Increasing knowledge score about bloodborne pathogens (BBPs) transmission (rate-ratio (RR): 0.93; 95%CI: 0.89–0.96), fewer years of work experience, being a non-licensed prescriber (RR: 2.02; 95%CI: 1.36–2.98) licensed (RR: 2.86; 9%CI: 1.81–4.51) or non-licensed assistant (RR: 2.78; 95%CI: 1.72–4.47) compared to a licensed prescriber, perceived barriers (RR: 1.06;95%CI: 1.03–1.08), and compliance with UPs scores (RR: 0.93; 95%CI: 0.87–0.97) were significant predictors of SIs. Improved knowledge about BBPs, compliance with UPs and reduced barriers to follow UPs could reduce SIs to HCWs.

Keywords: health belief model, sharp injuries, needle stick injuries, healthcare workers

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Authors: Anasuya Ghosh, Subhramoy Chaudhury

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During routine cadaveric dissection at gross anatomy lab of our institution, a radial artery was found with unusual origin and superficial course. Normally the radial artery takes its origin as one of the terminal branches of brachial artery at the level of the neck of radius. It usually lies along the lateral border of fore arm deep to the brachioradialis muscle. While dissecting a 72-year-old Caucasian female cadaver, it was found that the right sided radial artery originated from the upper part of brachial artery of arm, 2 cm below the lower border of teres major muscle, from the lateral aspect of brachial artery. Then the radial artery superficially crossed the brachial artery and median nerve from lateral to medial direction and rested superficially at the cubital fossa. Embryologically, it can be explained as a failure of disappearance, or abnormal persistence of some insignificant embryonic vessels may give rise to this kind of vascular anomalies. As radial artery is one of the most important upper limb arteries, its variation and related complications are clinically significant. This unusual origin and course of radial artery should be kept in mind by all healthcare providers including surgeons and radiologists during routine venipuncture, orthopedic and plastic surgeries of arm, coronary angiographic procedures in radial approach etc. to prevent unwanted complications.

Keywords: brachial artery anomalies, brachio-radial artery, high origin radial artery, superficial radial artery

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Authors: Rami S. Alasmari, Abdullah Al Zahrani, Hattan A. Hassani, Hattan A. Hassani, Nawwaf A. Almalky, Abdullah F. Bokhari, Alwalied A. Hafez

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Diabetes mellitus type 2 (DMT2) is a major chronic condition that is considered common among elderly people, with multiple potential complications that could contribute to falls. However, this concept is not well understood, thus, the aim of this study is to determine whether diabetes is an independent risk factor for falls in elderly. In this observational cross-sectional study, 309 diabetic patients aged 60 or more who visited the primary healthcare centers of the Ministry of National Guard Health Affairs in Jeddah were chosen via convenience sampling method. To collect the data, Semi-structured Fall Risk Assessment questionnaire and Fall Efficacy Score scale were used. The mean age of the participants was estimated to be 68.5 (SD:7.4) years. Among the participants, 48.2% experienced falling before, and 63.1% of them suffered falls in the past 12-months. The results showed that gait problems were independently associated with a higher likelihood of fall among the elderly patients (OR = 1.98, 95%CI, 1.08 to 3.62, p = 0.026. This paper suggests that diabetes mellitus is an independent fall risk factor among elderly. Therefore, identifying such patients as being at higher risk and prompt referral to a specialist falls clinic is recommended.

Keywords: diabetes, fall, elderly, risk factors

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Authors: Tery Nehemia Nugraha Joseph, J. D. P. Wisnubroto

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Thyroid cancer is a healthcare problem with high morbidity and mortality. Follicular adenoma and follicular carcinoma are thyroid tumors from the thyroid follicular cells differentiation with a microfollicular pattern that consists of follicular cuboidal cells. vascular endothelial growth factor (VEGF) is a potent and powerful mitogen for endothelial cells and increases vascular permeability. Therefore, due to an increase in thyroid-stimulating hormone (TSH), VEGF production is activated in the thyroid that leads to the end of mitogenic TSH stimulation and initiation of angiogenesis. The differences in VEGF levels in the follicular carcinoma of thyroid tissue with follicular adenoma thyroid can be used as a basis in differentiating the two types of neoplasms. This study aims to analyze VEGF in the serum so that it can be used to differentiate the types of thyroid carcinoma before surgery. This study uses a cross-sectional research design. Samples were carried out by taking serum samples, and the VEGF levels were calculated. Data were analyzed using the Mann-Whitney test. The results found a significant difference between VEGF levels in the follicular carcinoma thyroid group and VEGF levels in the follicular adenoma thyroid group with a value of p = 0.007 (p < 0.05). The results obtained are 560,427 ± 160,506 ng/mL in the type of follicular carcinoma thyroid and 320.943 ± 134.573 ng/mL in the type of follicular adenoma thyroid. VEGF levels between follicular adenoma and follicular carcinoma are different. VEGF levels are higher in follicular carcinoma thyroid than follicular adenoma thyroid.

Keywords: follicular adenoma thyroid, follicular carcinoma thyroid, thyroid, VEGF

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Authors: Mirza Mujtaba Baig

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Artificial Intelligence (AI) is evolving rapidly, and one of the areas in which this field has influenced is automation. The automobile, healthcare, education, and robotic industries deploy AI technologies constantly, and the automation of tasks is beneficial to allow time for knowledge-based tasks and also introduce convenience to everyday human endeavors. The paper reviews the challenges faced with the current implementations of autonomous self-driving cars by exploring the machine learning, robotics, and artificial intelligence techniques employed for the development of this innovation. The controversy surrounding the development and deployment of autonomous machines, e.g., vehicles, begs the need for the exploration of the configuration of the programming modules. This paper seeks to add to the body of knowledge of research assisting researchers in decreasing the inconsistencies in current programming modules. Blockchain is a technology of which applications are mostly found within the domains of financial, pharmaceutical, manufacturing, and artificial intelligence. The registering of events in a secured manner as well as applying external algorithms required for the data analytics are especially helpful for integrating, adapting, maintaining, and extending to new domains, especially predictive analytics applications.

Keywords: artificial intelligence, automation, big data, self-driving cars, machine learning, neural networking algorithm, blockchain, business intelligence

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Authors: Subhash Nerella, Ziyuan Guan, Azra Bihorac, Parisa Rashidi

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Intensive care units (ICUs) provide care to critically ill patients in severe and life-threatening conditions. However, patient monitoring in the ICU is limited by the time and resource constraints imposed on healthcare providers. Many critical care indices such as mobility are still manually assessed, which can be subjective, prone to human errors, and lack granularity. Other important aspects, such as environmental factors, are not monitored at all. For example, critically ill patients often experience circadian disruptions due to the absence of effective environmental “timekeepers” such as the light/dark cycle and the systemic effect of acute illness on chronobiologic markers. Although the occurrence of delirium is associated with circadian disruption risk factors, these factors are not routinely monitored in the ICU. Hence, there is a critical unmet need to develop systems for precise and real-time assessment through novel enabling technologies. We have developed the mobility and circadian disruption quantification system (Mobi-DiQ) by augmenting biomarker and clinical data with pervasive sensing data to generate mobility and circadian cues related to mobility, nightly disruptions, and light and noise exposure. We hypothesize that Mobi-DiQ can provide accurate mobility and circadian cues that correlate with bedside clinical mobility assessments and circadian biomarkers, ultimately important for delirium risk assessment and prevention. The collected multimodal dataset consists of depth images, Electromyography (EMG) data, patient extremity movement captured by accelerometers, ambient light levels, Sound Pressure Level (SPL), and indoor air quality measured by volatile organic compounds, and the equivalent CO₂ concentration. For delirium risk assessment, the system recognizes mobility cues (axial body movement features and body key points) and circadian cues, including nightly disruptions, ambient SPL, and light intensity, as well as other environmental factors such as indoor air quality. The Mobi-DiQ system consists of three major components: the pervasive sensing system, a data storage and analysis server, and a data annotation system. For data collection, six local pervasive sensing systems were deployed, including a local computer and sensors. A video recording tool with graphical user interface (GUI) developed in python was used to capture depth image frames for analyzing patient mobility. All sensor data is encrypted, then automatically uploaded to the Mobi-DiQ server through a secured VPN connection. Several data pipelines are developed to automate the data transfer, curation, and data preparation for annotation and model training. The data curation and post-processing are performed on the server. A custom secure annotation tool with GUI was developed to annotate depth activity data. The annotation tool is linked to the MongoDB database to record the data annotation and to provide summarization. Docker containers are also utilized to manage services and pipelines running on the server in an isolated manner. The processed clinical data and annotations are used to train and develop real-time pervasive sensing systems to augment clinical decision-making and promote targeted interventions. In the future, we intend to evaluate our system as a clinical implementation trial, as well as to refine and validate it by using other data sources, including neurological data obtained through continuous electroencephalography (EEG).

Keywords: deep learning, delirium, healthcare, pervasive sensing

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Authors: Babak Nemat

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Background: Exercise behavior (EB) has a significant impact on infertility, but the magnitude of the effect is not easily determined. The aim of the present study was to assess the effect of social support and self-regulation, as external and internal factors, on changes in exercise behavior among infertile women. Methods: For a cross-sectional study conducted in Sanandaj (Iran) in 2023, we recruited infertile women (n=483) from 35 comprehensive healthcare centers by means of convenience sampling. Standardized face-to-face interviews were conducted using established and reliable instruments for the assessment of EB, social support, and self-regulation. Logistic regression models were applied to assess the association between EB, social support and self-regulation. Results: The majority of the participants (56.7%) had secondary infertility, while 70.8% of them did not perform any exercise. Self-regulation and social support were significantly higher in women with secondary infertility than in those with primary infertility (p < 0.01). Self-regulation was significantly lower in women whose height was below 160 centimeters (cm) (p<0.05). Social support was significantly higher among participants aged ≥ 35 years and weighing ≥ 60 kilograms (kg) (p < 0.01). The odds of EB adoption increased with self-regulation and social support (OR=1.05, 95% CI=1.02-1.09, p <0.01), (OR=1.06, 95% CI=1.02-1.11, p <0.01). Conclusion: Social support and self-regulation almost equally influenced EB in infertile women. Designing support and consultation programs can be considered in encouraging infertile women to exercise in future research.

Keywords: social support, regulation, infertility, women

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Authors: Komal Fizza

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All around the world in every field professionals are taking great support from their computers. Computer assisted strategies not only increase the efficiency of the professionals but also in case of healthcare they help in life-saving interventions. The background of this current research is aimed towards two things; first to find out if computer assisted strategies are useful for Pharmacist for not and secondly how much these assist a Pharmacist to do quality interventions. Shifa International Hospital is a 500 bedded hospital, and it is running Antimicrobial Stewardship, during their stewardship rounds pharmacists observed that a lot of wrong doses of antibiotics were coming at times those were being overlooked by the other pharmacist even. So, with the help of MIS team the patients were categorized into adult and peads depending upon their age. Minimum and maximum dose of every single antibiotic present in the pharmacy that could be dispensed to the patient was developed. These were linked to the order entry window. So whenever pharmacist would type any order and the dose would be below or above the therapeutic limit this would give an alert to the pharmacist. Whenever this message pop-up this was recorded at the back end along with the antibiotic name, pharmacist ID, date, and time. From 14th of January 2015 and till 14th of March 2015 the software stopped different users 350 times. Out of this 300 were found to be major errors which if reached to the patient could have harmed them to the greater extent. While 50 were due to typing errors and minor deviations. The pilot study showed that computer assisted strategies can be of great help to the pharmacist. They can improve the efficacy and quality of interventions.

Keywords: antibiotics, computer assisted strategies, pharmacist, stewardship

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Authors: Dena Alhaloul

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The Middle East and North Africa (MENA) region is characterized by diverse cultures, economies, and social structures. Fertility rates in MENA have seen significant changes over time, with variations among countries and subregions. Understanding fertility patterns in this region is essential due to its impact on demographic dynamics, healthcare, labor markets, and social policies. Rising or declining fertility rates have far-reaching consequences for the region's socioeconomic development. The main thrust of this study is to comprehensively examine fertility rates in the Middle East and North Africa (MENA) region. It aims to understand the distribution, determinants, and temporal trends of fertility rates in MENA countries. The study seeks to provide insights into the factors influencing fertility decisions, assess how fertility rates have evolved over time, and potentially develop statistical models to characterize these trends. As for the methodology of the study, the study uses descriptive statistics to summarize and visualize fertility rate data. It also uses regression analyses to identify determinants of fertility rates as well as statistical modeling to characterize temporal trends in fertility rates. The conclusion of this study The research will contribute to a deeper understanding of fertility dynamics in the MENA region, shedding light on the distribution of fertility rates, their determinants, and historical trends.

Keywords: fertility, distribution, modeling, regression

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Authors: Mona Nikidehaghani, Freda Hui

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In Australia, one-third of mental health carers provide 40 hours or more of unpaid care per week. These hidden workers contribute significantly to the Australian mental health workforce by providing unpaid services both direct and indirect to people in their care. However, carers are often neglected in the healthcare system because Government services focus on those with a mental health condition rather than those supporting them. The aim of this study is to evaluate the perceptions of mental health carers on the effectiveness of community services designed for carers and how these services could be improved. We collaborated with One Door Mental Health, a community organisation that supports mental health carers. Through semi-structured interviews with 27 mental health carers residing in the Illawarra region (NSW), we documented their daily challenges and evaluated outcomes of the current programs for carers. Our findings demonstrate that services such as education programs enable capacity building and improve the social life and mental health of carers. Drawing on the perceptions of mental health carers, this study maps pathways for making meaningful changes in the lives of carers and proposes an outcome framework to evaluate the impact of a community organisation on the lives of their clients. The framework prepared by this project would be replicable, allowing other community organisations to measure the outcomes and improve their services.

Keywords: capacity building, community development, community service, mental health carers

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Authors: Evelyn Castle, Adam Thompson

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Background: In 2013, the Kano State Primary Health Care Management Board redesigned its Routine immunization supply chain from diffused pull to direct delivery push. It addressed issues around stockouts and reduced time spent by health facility staff collecting, and reporting on vaccine usage. The health care board sought the help of a 3PL for twice-monthly deliveries from its cold store to 484 facilities across 44 local governments. eHA’s Health Delivery Systems group formed a 3PL to serve 326 of these new facilities in partnership with the State. We focused on designing and implementing a technology system throughout. Basic methodologies: GIS Mapping: - Planning the delivery of vaccines to hundreds of health facilities requires detailed route planning for delivery vehicles. Mapping the road networks across Kano and Bauchi with a custom routing tool provided information for the optimization of deliveries. Reducing the number of kilometers driven each round by 20%, - reducing cost and delivery time. Direct Delivery Information System: - Vaccine Direct Deliveries are facilitated through pre-round planning (driven by health facility database, extensive GIS, and inventory workflow rules), manager and driver control panel customizing delivery routines and reporting, progress dashboard, schedules/routes, packing lists, delivery reports, and driver data collection applications. Move: Last Mile Logistics Management System: - MOVE has improved vaccine supply information management to be timely, accurate and actionable. Provides stock management workflow support, alerts management for cold chain exceptions/stock outs, and on-device analytics for health and supply chain staff. Software was built to be offline-first with user-validated interface and experience. Deployed to hundreds of vaccine storage site the improved information tools helps facilitate the process of system redesign and change management. Findings: - Stock-outs reduced from 90% to 33% - Redesigned current health systems and managing vaccine supply for 68% of Kano’s wards. - Near real time reporting and data availability to track stock. - Paperwork burdens of health staff have been dramatically reduced. - Medicine available when the community needs it. - Consistent vaccination dates for children under one to prevent polio, yellow fever, tetanus. - Higher immunization rates = Lower infection rates. - Hundreds of millions of Naira worth of vaccines successfully transported. - Fortnightly service to 326 facilities in 326 wards across 30 Local Government areas. - 6,031 cumulative deliveries. - Over 3.44 million doses transported. - Minimum travel distance covered in a round of delivery is 2000 kms & maximum of 6297 kms. - 153,409 kms travelled by 6 drivers. - 500 facilities in 326 wards. - Data captured and synchronized for the first time. - Data driven decision making now possible. Conclusion: eHA’s Vaccine Direct delivery has met challenges in Kano and Bauchi State and provided a reliable delivery service of vaccinations that ensure t health facilities can run vaccination clinics for children under one. eHA uses innovative technology that delivers vaccines from Northern Nigerian zonal stores straight to healthcare facilities. Helped healthcare workers spend less time managing supplies and more time delivering care, and will be rolled out nationally across Nigeria.

Keywords: direct delivery information system, health delivery system, GIS mapping, Northern Nigeria, vaccines

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Authors: Arezoo Fallahi‎

Abstract:

Background: Exercise behavior (EB) has a significant impact on infertility, but the magnitude of the effect is not easily determined. The aim of the present study was to assess the effect of social support and self-regulation, as external and internal factors, on changes in exercise behavior among infertile women. Methods: For a cross-sectional study conducted in Sanandaj (Iran) in 2020, we recruited infertile women (n=483) from 35 comprehensive healthcare centers by means of convenience sampling. Standardized face-to-face interviews were conducted using established and reliable instruments for the assessment of EB, social support, and self-regulation. Logistic regression models were applied to assess the association between EB, social support and self-regulation. Results: The majority of the participants (56.7%) had secondary infertility, while 70.8% of them did not perform any exercise. Self-regulation and social support were significantly higher in women with secondary infertility than in those with primary infertility (p < 0.01). Self-regulation was significantly lower in women whose height was below 160 centimeters (cm) (p<0.05). Social support was significantly higher among participants aged ≥ 35 years and weighing ≥ 60 kilograms (kg) (p < 0.01). The odds of EB adoption increased with self-regulation and social support (OR=1.05, 95% CI=1.02-1.09, p <0.01), (OR=1.06, 95% CI=1.02-1.11, p <0.01). Conclusion: Social support and self-regulation almost equally influenced EB in infertile women. Designing support and consultation programs can be considered in encouraging infertile women to do exercise in future research.

Keywords: social support, regulation, infertility, women, exercise

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Authors: Abdullah Tahir

Abstract:

The omission of regular medications in surgical patients poses a significant challenge in healthcare settings and is associated with increased morbidity during hospital stays. Human factors such as high workload, poor communication, and emotional stress are known to contribute to these omissions, particularly evident in the surgical assessment unit (SAU) due to its high patient burden and long wait times. This study aimed to quantify and address the issue by implementing targeted interventions to enhance compliance in prescribing regular medications for surgical patients at Stoke Mandeville Hospital, United Kingdom. Data were collected on 14 spontaneous days between April and May 2023, and the frequency of prescription omissions was recorded using a tally chart. Subsequently, informative posters were introduced in the SAU, and presentations were given to the surgical team to emphasize the importance of compliance in this area. The interventions were assessed using a second data collection cycle, again over 14 spontaneous days in May 2023. Results demonstrated an improvement from 40% (60 out of 150) to 74% (93 out of 126) of patients having regular medications prescribed at the point of clerking. These findings highlight the efficacy of frequent prompts and awareness-raising interventions in increasing workforce compliance and addressing the issue of prescription omissions in the SAU.

Keywords: prescription omissions, quality improvement, regular medication, surgical assessment unit

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Authors: Fatemeh Noughani, Seyd Mehdi Sadat

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Medical tourism or travel therapy is travelling from one country to another to be under medical treatment, utilizing the health factors of natural sector like mineral water springs and so on. From 1990s medical tourism around the world developed and grew because of different factors like globalization and free trade in the fields of health services, changes in exchange rates in the world economy (which caused the desirability of Asian countries as a medical tourist attraction) in a way that currently there is a close competition in this field among famous countries in medical services to make them find a desirable place in medical tourism market of the world as a complicated and growing industry in a short time. Perhaps tourism is an attractive industry and a good support for the economy of Iran, if we try to merge oil earnings and tourism industry it would be better and more constructive than putting them in front of each other. Moving from oil toward tourism economy especially medical tourism, must be one of the prospects of Iran's government for the oil industry to provide a few percent of the yearly earnings of the country. Among the achievements in medical tourism we can name the prevention of brain drain to other countries and an increase in employment rate for healthcare staff, increase in foreign exchange earnings of the country because of the tourists' staying and followed by increasing the quality of life and cultural transmission as well as empowering the medical human resources.

Keywords: developing countries, health tourism, quality of life, cultural transmission

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Authors: Mohamed Elshal, Hazim El-Mounayri, Omar El-Mounayri

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Emergency department (ED) is considered as a complex system of interacting entities: patients, human resources, software and hardware systems, interfaces, and other systems. This paper represents a research for implementing a detailed Systems Engineering (SE) approach in a mid-size hospital in central Indiana. This methodology will be applied by “The Initiative for Product Lifecycle Innovation (IPLI)” institution at Indiana University to study and solve the crowding problem with the aim of increasing throughput of patients and enhance their treatment experience; therefore, the nature of crowding problem needs to be investigated with all other problems that leads to it. The presented SE methods are workflow analysis and systems modeling where SE tools such as Microsoft Visio are used to construct a group of system-level diagrams that demonstrate: patient’s workflow, documentation and communication flow, data systems, human resources workflow and requirements, leadership involved, and integration between ER different systems. Finally, the ultimate goal will be managing the process through implementation of an executable model using commercialized software tools, which will identify bottlenecks, improve documentation flow, and help make the process faster.

Keywords: systems modeling, ED operation, workflow modeling, systems analysis

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Authors: Mohammed Qutishat, Loai Abu Sharour, Kholoud Al-Damery, Ibtisam Al Harthy, Sulaiman Al-Sabei

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Background: The 2019 coronavirus outbreak (COVID-19) has been declared a pandemic and has greatly affected both patients and healthcare workers. This study was conducted to explore the extent of posttraumatic stress disorder (PTSD) experiences among nurses as a result of the COVID-19 pandemic in Jordan. Method: This study used a cross-sectional study design with a convenience sampling approach. A sample of 259 participants completed the study questionnaires, including a sociodemographic questionnaire and the posttraumatic stress disorder checklist for DSM‐5, between May and July 2020. Result: The prevalence of PTSD among the study participants was 37.1%. The majority of study participants who exhibited PTSD symptoms presented the lowest level of PTSD (17%). The results indicated significant differences in overall COVID-19-related PTSD according to the participant’s age (F = 14.750, P = .000), gender (F = 30.340, P = .000), level of education (F = 51.983, P =.000), years of experience (F = 52.33, P = .000), place of work (F = 19.593, P = .000), and working position (F = 11.597, P = .000), as determined by one-way ANOVA. Conclusion: Nurses must be qualified and accredited to cope with reported PTSD cases and their consequences in relation to COVID-19 outbreaks. Close collaboration with a multidisciplinary team is required to recognise, manage, and encourage safety literacy among health care professionals and individuals diagnosed with or suspected of PTSD due to COVID-19 outbreaks or any other viral outbreaks.

Keywords: PTSD, nursing, coronavirus, pandemic, infectious disease

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Authors: Lichung Jen, Yi Chun Liu, Kuan-Wei Lee

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Fruitful data has been accumulated in database nowadays and is commonly used as support for decision-making. In the healthcare industry, hospital, for instance, ordering pharmacy inventory is one of the key decision. With large drug inventory, the current cost increases and its expiration dates might lead to future issue, such as drug disposal and recycle. In contrast, underestimating demand of the pharmacy inventory, particularly standing drugs, affects the medical treatment and possibly hospital reputation. Prescription behaviour of hospital physicians is one of the critical factor influencing this decision, particularly irregular prescription behaviour. If a drug’s usage amount in the month is irregular and less than the regular usage, it may cause the trend of subsequent stockpiling. On the contrary, if a drug has been prescribed often than expected, it may result in insufficient inventory. We proposed a hierarchical Bayesian mixture model with two components to identify physicians’ regular/irregular prescription patterns with probabilities. Heterogeneity of hospital is considered in our proposed hierarchical Bayes model. The result suggested that modeling the prescription patterns of physician is beneficial for estimating the order quantity of medication and pharmacy inventory management of the hospital. Managerial implication and future research are discussed.

Keywords: hierarchical Bayesian model, poission mixture model, medicines prescription behavior, irregular behavior

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Authors: Rachel Karasenty Saltoun, Charlotte Roddick, Chelsea D. Christie, Frances Chen

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Moving has become an integral part of many people’s lives. This research explores whether relocating to a new city is associated with an increase in loneliness and cardiovascular disease risk and if this increased risk diminishes with continued residency. To test this, various psychosocial variables and three cardiovascular disease risk markers (C-reactive protein, albumin, blood pressure) were assessed on two groups of individuals: those who have moved to Vancouver, Canada in the previous 6 weeks (‘Movers’) and those who have lived in Vancouver for at least five years (‘Non-Movers’). It was hypothesized that individuals who had recently relocated would have heightened levels of loneliness, blood pressure (BP), albumin, and C-reactive protein (CRP) compared to those who had not recently relocated. Length of residency was hypothesized to moderate these effects, such that after a few months, loneliness levels and cardiovascular disease risk would decrease among those who had recently relocated. Correlational analysis indicated a trend between the change in CRP and albumin levels and loneliness overtime on an individual level. However, these results must be interpreted with caution due to the small sample size. As Vancouver’s immigration rates continue to grow, this study has important implications regarding the social support resources offered to new immigrants, as well as bringing awareness at the healthcare level of the potential increase in cardiovascular disease risk among those who have recently relocated.

Keywords: cardiovascular disease risk, loneliness, moving, residential mobility

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Authors: Roseline Oghogho Osaseri, Osaseri E. I.

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Lassa fever is an epidemic hemorrhagic fever caused by the Lassa virus, an extremely virulent arena virus. This highly fatal disorder kills 10% to 50% of its victims, but those who survive its early stages usually recover and acquire immunity to secondary attacks. One of the major challenges in giving proper treatment is lack of fast and accurate diagnosis of the disease due to multiplicity of symptoms associated with the disease which could be similar to other clinical conditions and makes it difficult to diagnose early. This paper proposed an Adaptive Neuro Fuzzy Inference System (ANFIS) for the prediction of Lass Fever. In the design of the diagnostic system, four main attributes were considered as the input parameters and one output parameter for the system. The input parameters are Temperature on admission (TA), White Blood Count (WBC), Proteinuria (P) and Abdominal Pain (AP). Sixty-one percent of the datasets were used in training the system while fifty-nine used in testing. Experimental results from this study gave a reliable and accurate prediction of Lassa fever when compared with clinically confirmed cases. In this study, we have proposed Lassa fever diagnostic system to aid surgeons and medical healthcare practictionals in health care facilities who do not have ready access to Polymerase Chain Reaction (PCR) diagnosis to predict possible Lassa fever infection.

Keywords: anfis, lassa fever, medical diagnosis, soft computing

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Authors: Jung Yoon Kim

Abstract:

Introduction: Wounds inevitably cause patients to experience discomfort, distress, and consequentially reduced quality of life due to entailed pain, maceration, and foul odor. The dressing has been a universal wound care method in which wounds are covered and protected, and an optimum environment for healing is provided. This study aimed to investigate Korean nurses’ level of awareness of pain and skin tearing in wound beds and/or peri-wound skin at dressing change. Methods: A descriptive study was performed. Convenience sampling was employed, and registered nurses were recruited from attendees of continuing education program. A total of 399 participants (RN) completed the questionnaire. Data were collected from September to November 2022. Results: Many of them perceived skin tearing and wound-related pain associated with dressing changes, but most of them did not assess and record pain and skin tearing at dressing change. More than half of the respondents reported that they did not provide nursing intervention to prevent pain and skin tearing. Many of them reported that a systematic educational program for preventing pain and skin tearing at dressing changes was needed. Discussion: Many of the respondents were aware of pain and skin tearing at dressing change but did not take any further necessary measures, including nursing intervention, for the most appropriate, systematic pain and skin tearing management. Therefore, this study suggested that a systematic and comprehensive educational program for Korean healthcare professionals needs to be developed and implemented in Korea’s hospital settings.

Keywords: skin tearing, pain, dressing change, nurses

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Authors: Juan Pablo Hervas-Perez, Jesus Guodemar-Perez, Montserrat Ruiz-Lopez, Elena Sonsoles Rodriguez-Lopez, Noemi Mayoral-Gonzalo, Eduardo Cimadevilla Fernandez-Pola, Mario Caballero-Corella

Abstract:

Physiotherapy is a healthcare discipline that covers many fields of action within the recovery and prevention of health. Some are well known, but others, such as working with newborns and premature children are not so. Physical therapist functions are well defined, but the impression of the population is that there are other professionals who can develop them, and a large part are unknown. Objective: To evaluate the level of knowledge of the sample on the role of the physiotherapist in general, and more specifically in the neonatal intensive care (NICU) units, and estimate your level of notions on the development centered care (DCC). Method: A descriptive, transversal, observational and prospective study developed on a 125 participants' sample. Results: From the sample studied, 87.2% had already had contact with physiotherapy previously. An 80.9% believed that the physiotherapist intervention was decisive for the cure, and 84.0% would recommend physiotherapy treatment to others. Of the total surveyed, 98.0% felt that the physiotherapist is who should run the physiotherapeutic treatments, but shares with other professions 71.0% of votes. The field's best-known work is rehabilitation (94.0%); Neonatology is on the 4th place (66.0% of votes). Conclusions: Many areas of work of physical therapy are unknown to a big part of the population, including the own health workers. Less than half of the sample meets the DCC, and only 58% of the interviewed physiotherapists know them.

Keywords: functions of physiotherapist, neonatal intensive care, physiotherapy, prematurity

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Authors: Riyona Chetty, Raisuyah Bhagwan, Nalini Govender

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Background: During rehabilitation, the prosthetist establishes prosthetic and/or orthotic realistic goals and programmes as well as clinical outcome measures. They are well-positioned to improve the amputee’s physical and psychosocial well-being. Objective: This study aims to explore the ways in which the prosthetist may be able to improve the holistic well-being of the amputee. Methods: Data was collected using a focus group discussion with 16 prosthetists at a medical facility in KwaZulu-Natal, South Africa. Results: The findings indicate that amputees are encouraged to consider physical activities to improve their health. However, a major challenge experienced by the prosthetists was their lack of adequate psychosocial expertise, which affected their ability to offer emotional support. Additional factors such as language barriers, rotational systems, and unrealistic expectations further obstructed optimal service delivery. Conclusion: The prosthetists are adequately skilled in manufacturing the ideal prosthesis and encouraging physical exercise to promote the amputee’s physical health. However, their lack of psychosocial training limits them in providing emotional support during rehabilitation. It is recommended that prosthetists are provided with professional training to provide emotional support as part of holistic healthcare. Clinical relevance: The intention of this study was to provide pertinent recommendations for prosthetists, enabling them to provide holistic quality care to their patients.

Keywords: psychological, social, well-being, amputee, prosthetist

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Authors: Alexandria Carey, Angela Starkweather, Ann Horgas, Hwayoung Cho, Jason Beneciuk

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Background/Significance: Over 3.4 million acute axial low back pain (aLBP) cases are treated annually in the United States (US) emergency departments (ED). ED patients with aLBP receive varying verbal and written discharge routine care (RC), leading to ineffective patient self-management. Ineffective self-management increase chronic low back pain (cLPB) transition risks, a chief cause of worldwide disability, with associated costs >$60 million annually. This research addresses this significant problem by evaluating an ED digital pain self-management intervention (EDPSI) focused on improving self-management through improved knowledge retainment, skills, and self-efficacy (confidence) (KSC) thus reducing aLBP to cLBP transition in ED patients discharged with aLBP. The research has significant potential to increase self-efficacy, one of the most potent mechanisms of behavior change and improve health outcomes. Focusing on accessibility and usability, the intervention may reduce discharge disparities in aLBP self-management, especially with low health literacy. Study Questions: This research will answer the following questions: 1) Will an EDPSI focused on improving KSC progress patient self-management behaviors and health status?; 2) Is the EDPSI sustainable to improve pain severity, interference, and pain recurrence?; 3) Will an EDPSI reduce aLBP to cLBP transition in patients discharged with aLBP? Aims: The pilot randomized-controlled trial (RCT) study’s objectives assess the effects of a 12-week digital self-management discharge tool in patients with aLBP. We aim to 1) Primarily assess the feasibility [recruitment, enrollment, and retention], and [intervention] acceptability, and sustainability of EDPSI on participant’s pain self-management; 2) Determine the effectiveness and sustainability of EDPSI on pain severity/interference among participants. 3) Explore patient preferences, health literacy, and changes among participants experiencing the transition to cLBP. We anticipate that EDPSI intervention will increase likelihood of achieving self-management milestones and significantly improve pain-related symptoms in aLBP. Methods: The study uses a two-group pilot RCT to enroll 30 individuals who have been seen in the ED with aLBP. Participants are randomized into RC (n=15) or RC + EDPSI (n=15) and receive follow-up surveys for 12-weeks post-intervention. EDPSI innovative content focuses on 1) highlighting discharge education; 2) provides self-management treatment options; 3) actor demonstration of ergonomics, range of motion movements, safety, and sleep; 4) complementary alternative medicine (CAM) options including acupuncture, yoga, and Pilates; 5) combination therapies including thermal application, spinal manipulation, and PT treatments. The intervention group receives Booster sessions via Zoom to assess and reinforce their knowledge retention of techniques and provide return demonstration reinforcing ergonomics, in weeks two and eight. Outcome Measures: All participants are followed for 12-weeks, assessing pain severity/ interference using the Brief Pain Inventory short-form (BPI-sf) survey, self-management (measuring KSC) using the short 13-item Patient Activation Measure (PAM), and self-efficacy using the Pain Self-Efficacy Questionnaire (PSEQ) weeks 1, 6, and 12. Feasibility is measured by recruitment, enrollment, and retention percentages. Acceptability and education satisfaction are measured using the Education-Preference and Satisfaction Questionnaire (EPSQ) post-intervention. Self-management sustainment is measured including PSEQ, PAM, and patient satisfaction and healthcare utilization (PSHU) requesting patient overall satisfaction, additional healthcare utilization, and pain management related to continued back pain or complications post-injury.

Keywords: digital, pain self-management, education, tool

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Authors: Gajendra Kumar Mourya, Dinesh Bhatia, Akash Handique, Sunita Warjri, Syed Achaab Amir

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Nowadays, Medical imaging has become an integral part of modern healthcare. Abdominal CT images are an invaluable mean for abdominal organ investigation and have been widely studied in the recent years. Diagnosis of liver pathologies is one of the major areas of current interests in the field of medical image processing and is still an open problem. To deeply study and diagnose the liver, segmentation of liver is done to identify which part of the liver is mostly affected. Manual segmentation of the liver in CT images is time-consuming and suffers from inter- and intra-observer differences. However, automatic or semi-automatic computer aided segmentation of the Liver is a challenging task due to inter-patient Liver shape and size variability. In this paper, we present a technique for automatic segmenting the liver from CT images using Random Forest Classifier. Random forests or random decision forests are an ensemble learning method for classification that operate by constructing a multitude of decision trees at training time and outputting the class that is the mode of the classes of the individual trees. After comparing with various other techniques, it was found that Random Forest Classifier provide a better segmentation results with respect to accuracy and speed. We have done the validation of our results using various techniques and it shows above 89% accuracy in all the cases.

Keywords: CT images, image validation, random forest, segmentation

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Authors: Malik Takreem Ahmad, Pablo Lamata, Rasi Mizori

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Background: In recent years, mobile health apps have grown in popularity as a means for people to track and manage their health. While there is increasing worry that these applications may potentially contribute to the emergence of health anxiety, they can also help to encourage healthy behaviours and provide access to health information. Objective: The objective of this literature review is to look at available mhealth apps and critically evaluate the compromise between reassurance and anxiety. Methodology: A literature review was carried out to analyse the effects of mhealth apps on the creation of health anxiety within the general population. PubMed and SCOPUS were used to search for relevant articles, and abstracts were screened using inclusion criteria of the terms: mhealth apps; e-Health; healthcare apps; cyberchondria; Health anxiety; illness anxiety disorder. A total of 27 studies were included in the review. Results and discussion: The findings suggest a direct relationship between mobile health app use and health anxiety. The impact of mobile health apps on health anxiety may depend on how they are used - individuals receiving a constant stream of health-related information may trigger unnecessary concern about one's health. The need for more regulation and oversight is identified, which can lead to app quality and safety consistency. There are also concerns about data security and privacy and the resulting "digital gap" for individuals without mobiles or internet access. Conclusion: While health apps can be valuable tools for managing and tracking health, individuals need to use them in a balanced and informed way to avoid increased anxiety.

Keywords: mobile health, mhealth apps, cyberchondria, health anxiety

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Authors: M. D. Antoine

Abstract:

When a child is diagnosed with an illness, condition, or developmental disorder, the process involved in understanding and accepting this diagnosis can be a very stressful and isolating experience for parents and families. The healthcare providers’ ability to effectively communicate in such situations represents a vital lifeline for parents. In this context, communication becomes a crucial element not only for getting through the period of grief but also for the future. We mobilized the five stages of grief model to summarize existing literature regarding the ways in which the experience ofan autism spectrum disorder diagnosis disclosurealigns with the experience of grief to explore how this can inform best practices for effective communication with parents through the diagnosis disclosure. Fifteen publications met inclusion criteria. Findings from the scoping review of empirical studies show that parents/families experience grief-like emotions during the diagnosis disclosure. However, grief is not an outcome of the encounter itself. In fact, the experience of the encounter can help mitigate the grief experience. The way parents/families receive and react to the ‘news’ depends on their preparedness, knowledge, and the support received through the experience. Individual communication skills, as well as policies and regulations, should be examined to alleviate adverse reactions in this context. These findings highlight the importance of further research into effective parent-provider communication strategies and their place in supporting quality autism care.

Keywords: autism spectrum disorder, autism spectrum disorder diagnosis, diagnosis disclosure, parent-provider communication, parental grief

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Authors: Karan Vishavjit, Aakash Lakra, Shafaq Khan

Abstract:

The COVID-19 pandemic has pushed healthcare professionals to use big data analytics as a vital tool for tracking and evaluating the effects of contagious viruses. To effectively analyze huge datasets, efficient NoSQL databases are needed. The analysis of post-COVID-19 health and well-being outcomes and the evaluation of the effectiveness of government efforts during the pandemic is made possible by this research’s integration of several datasets, which cuts down on query processing time and creates predictive visual artifacts. We recommend applying sharding and indexing technologies to improve query effectiveness and scalability as the dataset expands. Effective data retrieval and analysis are made possible by spreading the datasets into a sharded database and doing indexing on individual shards. Analysis of connections between governmental activities, poverty levels, and post-pandemic well being is the key goal. We want to evaluate the effectiveness of governmental initiatives to improve health and lower poverty levels. We will do this by utilising advanced data analysis and visualisations. The findings provide relevant data that supports the advancement of UN sustainable objectives, future pandemic preparation, and evidence-based decision-making. This study shows how Big Data and NoSQL databases may be used to address problems with global health.

Keywords: big data, COVID-19, health, indexing, NoSQL, sharding, scalability, well being

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