Search results for: medi-cal data

Authors: Hana Rabbouch

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In recent years, there has been considerable growth of denoising techniques mainly devoted to medical imaging. This important evolution is not only due to the progress of computing techniques, but also to the emergence of multi-resolution analysis (MRA) on both mathematical and algorithmic bases. In this paper, a comparative study is conducted between the two best-known MRA-based decomposition techniques: the Empirical Mode Decomposition (EMD) and the Discrete Wavelet Transform (DWT). The comparison is carried out in a framework of multi-scale denoising, where a Non-Local Means (NLM) filter is performed scale-by-scale to a sample of benchmark medical images. The results prove the effectiveness of the multiscaled denoising, especially when the NLM filtering is coupled with the EMD.

Keywords: medical imaging, non local means, denoising, multiscaled analysis, empirical mode decomposition, wavelets

Procedia PDF Downloads 142

Authors: Ibtihal D. Mustafa, Mawia A. Hassan

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Tumor segmentation from MRI image is important part of medical images experts. This is particularly a challenging task because of the high assorting appearance of tumor tissue among different patients. MRI images are advance of medical imaging because it is give richer information about human soft tissue. There are different segmentation techniques to detect MRI brain tumor. In this paper, different procedure segmentation methods are used to segment brain tumors and compare the result of segmentations by using correlation and structural similarity index (SSIM) to analysis and see the best technique that could be applied to MRI image.

Keywords: MRI, segmentation, correlation, structural similarity

Procedia PDF Downloads 410

Authors: Nassim Salmi

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Postoperative mobilization is an important part of fundamental care. Increased mobilization has a positive effect on recovery, but immobilization is still a challenge in postoperative care. Aims: To report how the establishment of a national nursing database was used to measure postoperative mobilization in patients undergoing surgery for ovarian cancer. Mobilization was defined as at least 3 hours out of bed on postoperative day 1, with the goal set at achieving this in 60% of patients. Clinical nurses on 4400 patients with ovarian cancer performed data entry. Findings: 46.7% of patients met the goal for mobilization on the first postoperative day, but variations in duration and type of mobilization were observed. Of those mobilized, 51.8% had been walking in the hallway. A national nursing database creates opportunities to optimize fundamental care. By comparing nursing data with oncological, surgical, and pathology data, it became possible to study mobilization in relation to cancer stage, comorbidity, treatment, and extent of surgery.

Keywords: postoperative care, gynecology, nursing documentation, database

Procedia PDF Downloads 117

Authors: Farida Habib, Haya Alfozan, Eman Miligi, Najla Alotaibi

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Background: Women’s satisfaction with maternity services, especially care during labor and birth, has become highly significant to healthcare providers, administrators, and policymakers. Purpose: The aims of this study were to assess maternal satisfaction regarding the quality of care during labor and to compare the level of maternal satisfaction between women who delivered by physicians and those delivered by midwives. Methodology: A descriptive, cross-sectional, correlational design was used. A convenient sample of 180 low-risk cases of immediate postpartum women who delivered at King Abdul-Aziz medical city was recruited. Women whose babies were diagnosed with serious health problems were excluded from the study. Data were collected using a self-administered questionnaire. The validity and reliability of the questionnaire were ensured. The questionnaire included three parts, namely: demographics data, medical history, and obstetrical history, and the last part is the satisfaction assessment tool. Ethical confederations were ensured. Maternal satisfaction during labor was classified in terms of health care, health workers' communication, and the environment. Results: Regarding health care, women were highly satisfied with care received from nurse (M = 4.21 + 0.88), medical care received (M = 4.17 + 0.79), and comfort techniques (M = 4.04 + 0.91). Regarding health workers' communication, women were highly satisfied with the provider to treat with dignity and respect (M = 4.03 + 0.91) and orientation to the toilet, bathroom, washing area (M = 4.00 + 0.93). Regarding the environment, women were highly satisfied with the experience of their baby's birth (M = 4.18 + 0.98) and supplies with drugs and supplies (M = 4.09 + 0.97). There was no statistically significant difference in maternal satisfaction between women who delivered by physicians and those delivered by midwives. Conclusion: Women were generally satisfied with their labor and delivery experience. There was no difference in maternal satisfaction on the labor process between women who delivered by physicians and those delivered by midwives.

Keywords: maternity, satisfaction, labor, delivery

Procedia PDF Downloads 193

Authors: Jang-hyun Oh, Kyoung-ho Choi, Jea-sun Lee

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The outbreak of the COVID-19 pandemic brought reconsiderations and doubts about urban density as compact cities became epidemic hot spots. Density, though, provides an upside in that medical services required to protect citizens against the spread of disease are concentrated within compact cities, which helps reduce the mortality rate. Sociodemographic characteristics are also a crucial factor in determining the vulnerability of the population, and the purpose of this study is to empirically discover how these three urban factors affect the severity of the epidemic impacts. The study aimed to investigate the influential relationships between urban factors and epidemic impacts and provide answers to whether superb medical service in compact cities can scale down the impacts of COVID-19. SEM (Structural Equation Modeling) was applied as a suitable research method for verifying interrelationships between factors based on theoretical grounds. The study accounted for 144 municipalities in South Korea during periods from the first emergence of COVID-19 to December 31st, 2022. The study collected data related to infection and mortality cases from each municipality, and it holds significance as primary research that enlightens the aspects of epidemic impact concerning urban settings and investigates for the first time the mediated effects of medical service. The result of the evaluation shows that compact cities are most likely to have lower sociodemographic vulnerability and better quality of medical service, while cities with low density contain a higher portion of vulnerable populations and poorer medical services. However, the quality of medical service had no significant influence in reducing neither the infection rate nor the mortality rate. Instead, density acted as the major influencing factor in the infection rate, while sociodemographic vulnerability was the major determinant of the mortality rate. Thus, the findings strongly paraphrase that compact cities, although with high infection rates, tend to have lower mortality rates due to less vulnerability in sociodemographics, Whereas death was more frequent in less dense cities due to higher portions of vulnerable populations such as the elderly and low-income classes. Findings suggest an important lesson for post-pandemic urban planning-intrinsic characteristics of urban settings, such as density and population, must be taken into account to effectively counteract future epidemics and minimize the severity of their impacts. Moreover, the study is expected to contribute as a primary reference material for follow-up studies that further investigate related subjects, including urban medical services during the pandemic.

Keywords: urban planning, sociodemographic vulnerability, medical service, COVID-19, pandemic

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Authors: Shizra Waris, Saleem Akhtar

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Big data is a research area receiving attention from academia and IT communities. In the digital world, the amounts of data produced and stored have within a short period of time. Consequently this fast increasing rate of data has created many challenges. In this paper, we use functionalism and structuralism paradigms to analyze the genesis of big data applications and its current trends. This paper presents a complete discussion on state-of-the-art big data technologies based on group and stream data processing. Moreover, strengths and weaknesses of these technologies are analyzed. This study also covers big data analytics techniques, processing methods, some reported case studies from different vendor, several open research challenges and the chances brought about by big data. The similarities and differences of these techniques and technologies based on important limitations are also investigated. Emerging technologies are suggested as a solution for big data problems.

Keywords: computer, it community, industry, big data

Procedia PDF Downloads 194

Authors: R. J. Kuo, W. C. Cheng, W. C. Lien, T. J. Yang

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Taiwan is a hyper endemic area for the Hepatitis B virus (HBV). The estimated total number of HBsAg carriers in the general population who are more than 20 years old is more than 3 million. Therefore, a case record review is conducted from January 2003 to June 2007 for all patients with a diagnosis of acute hepatitis who were admitted to the Emergency Department (ED) of a well-known teaching hospital. The cost for the use of medical resources is defined as the total medical fee. In this study, principal component analysis (PCA) is firstly employed to reduce the number of dimensions. Support vector regression (SVR) and artificial neural network (ANN) are then used to develop the forecasting model. A total of 117 patients meet the inclusion criteria. 61% patients involved in this study are hepatitis B related. The computational result shows that the proposed PCA-SVR model has superior performance than other compared algorithms. In conclusion, the Child-Pugh score and echogram can both be used to predict the cost of medical resources for patients with acute hepatitis in the ED.

Keywords: acute hepatitis, medical resource cost, artificial neural network, support vector regression

Procedia PDF Downloads 423

Authors: V. Durmus, M. Uydaci

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In order to prevent overburdened courts, rising costs of litigation, and lengthy trial resolutions, the Law on Mediation for Civil Disputes was enacted, which was aimed at defining the procedure and guiding principles for dispute resolutions under Civil Law, in 2012. This “Mediation Code” also applies for civil healthcare disputes in Turkey. Aside from mediation, reconciliation, governed by Articles 253-255 of Criminal Procedure Law, has emerged as an alternative way to resolve criminal medical disputes, but the difference between mediation and conciliation is mostly procedural. This article deals with mediation in Turkish health law and aspect of medical malpractice mediation in Turkey. In addition, this study examines the issue of mediation in health law from both a legal and normative point of view, including codes of mediation which regulate both the structural and professional practice of mediation providers. As a result, although there is not official record about success rate of medical malpractice litigations and malpractice mediation in Turkey, it is widely accepted that the success rate for medical malpractice cases is relatively low compared to other personal injury cases even if it is generally considered that medical malpractice case filings have gradually increased recently. According to the Justice Ministry’s Department of Mediation in Turkey, 719 civil disputes have referred to mediators since 2013 (when the first mediation law came into force) with a 98% success rate.

Keywords: malpractice mediation, medical disputes, reconciliation, health litigation, Turkish health law

Procedia PDF Downloads 312

Authors: Yan-Lin Liu, Cheng-Ting Shih, Jay Wu

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Tablet devices have been introduced into the medical environment in recent years. The performance of display can be varied based on the use of different hardware specifications and types of display technologies. Therefore, the differences between tablet devices and medical diagnostic LCDs have to be verified to ensure that image quality is not jeopardized for clinical diagnosis in a picture archiving and communication system (PACS). In this study, a set of randomized object test patterns (ROTPs) were developed, which included randomly located spheres in abdominal CT images. Five radiologists were asked to independently review the CT images on different generations of iPads and a diagnostic monochrome medical LCD monitor. Receiver operating characteristic (ROC) analysis was performed by using a five-point rating scale, and the average area under curve (AUC) and average reading time (ART) were calculated. The AUC values for the second generation iPad, iPad mini, iPad Air, and monochrome medical monitor were 0.712, 0.717, 0.725, and 0.740, respectively. The differences between iPads were not significant. The ARTs were 177 min and 127 min for iPad mini and medical LCD monitor, respectively. A significant difference appeared (p = 0.04). The results show that the iPads were slightly inferior to the monochrome medical LCD monitor. However, tablet devices possess advantages in portability and versatility, which can improve the convenience of rapid diagnosis and teleradiology. With advances in display technology, the applicability of tablet devices and mobile devices may be more diversified in PACS.

Keywords: tablet devices, PACS, receiver operating characteristic, LCD monitor

Procedia PDF Downloads 481

Authors: Branci Sarra, Branci Saadia

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Because of the multiplied data growth, many computer science tools have been developed to process and analyze these Big Data. High-performance computing architectures have been designed to meet the treatment needs of Big Data (view transaction processing standpoint, strategic, and tactical analytics). The purpose of this article is to provide a historical and global perspective on the recent trend of high-performance computing architectures especially what has a relation with Analytics and Data Mining.

Keywords: high performance computing, HPC, big data, data analysis

Procedia PDF Downloads 520

Authors: Nihar Bheda

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Protecting digital assets such as networks, systems, and data from advanced cyber threats is the aim of Digital Immunity Systems (DIS), which are a subset of cybersecurity. With features like continuous monitoring, coordinated reactions, and long-term adaptation, DIS seeks to mimic biological immunity. This minimizes downtime by automatically identifying and eliminating threats. Traditional security measures, such as firewalls and antivirus software, are insufficient for enterprises, such as healthcare providers, given the rapid evolution of cyber threats. The number of medical record breaches that have occurred in recent years is proof that attackers are finding healthcare data to be an increasingly valuable target. However, obstacles to enhancing security include outdated systems, financial limitations, and a lack of knowledge. DIS is an advancement in cyber defenses designed specifically for healthcare settings. Protection akin to an "immune system" is produced by core capabilities such as anomaly detection, access controls, and policy enforcement. Coordination of responses across IT infrastructure to contain attacks is made possible by automation and orchestration. Massive amounts of data are analyzed by AI and machine learning to find new threats. After an incident, self-healing enables services to resume quickly. The implementation of DIS is consistent with the healthcare industry's urgent requirement for resilient data security in light of evolving risks and strict guidelines. With resilient systems, it can help organizations lower business risk, minimize the effects of breaches, and preserve patient care continuity. DIS will be essential for protecting a variety of environments, including cloud computing and the Internet of medical devices, as healthcare providers quickly adopt new technologies. DIS lowers traditional security overhead for IT departments and offers automated protection, even though it requires an initial investment. In the near future, DIS may prove to be essential for small clinics, blood banks, imaging centers, large hospitals, and other healthcare organizations. Cyber resilience can become attainable for the whole healthcare ecosystem with customized DIS implementations.

Keywords: digital immunity system, cybersecurity, healthcare data, emerging technology

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Authors: Prashant Shrivastava

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The purpose of this study is to explore re3dat.org registry to identify research data repositories registration workflow process. Further objective is to depict a graph for present development of research data repositories in India. Preliminarily with an approach to understand re3data.org registry framework and schema design then further proceed to explore the status of research data repositories of India in re3data.org registry. Research data repositories are getting wider relevance due to e-research concepts. Now available registry re3data.org is a good tool for users and researchers to identify appropriate research data repositories as per their research requirements. In Indian environment, a compatible National Research Data Policy is the need of the time to boost the management of research data. Registry for Research Data Repositories is a crucial tool to discover specific information in specific domain. Also, Research Data Repositories in India have not been studied. Re3data.org registry and status of Indian research data repositories both discussed in this study.

Keywords: research data, research data repositories, research data registry, re3data.org

Procedia PDF Downloads 326

Authors: Ghadeer Mohammad Said El-Sheikh, Samer Mohamad Shalhoob

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Medical equipment operation state is a valid reflection of health care organizations' performance, where such equipment highly contributes to the quality of healthcare services on several levels in which quality improvement has become an intrinsic part of the discourse and activities of health care services. In healthcare organizations, clinical and biomedical engineering departments play an essential role in maintaining the safety and efficiency of such equipment. One of the most challenging topics when it comes to such sophisticated equipment is the lifespan of medical equipment, where many factors will impact such characteristics of medical equipment through its life cycle. So far, many attempts have been made in order to address this issue where most of the approaches are kind of arbitrary approaches and one of the criticisms of existing approaches trying to estimate and understand the lifetime of a medical equipment lies under the inquiry of what are the environmental factors that can play into such a critical characteristic of a medical equipment. In an attempt to address this shortcoming, the purpose of our study rises where in addition to the standard technical factors taken into consideration through the decision-making process by a clinical engineer in case of medical equipment failure, the dimension of environmental factors shall be added. The investigations, researches and studies applied for the purpose of supporting the decision making process by a clinical engineers and assessing the lifespan of healthcare equipment’s in the Lebanese society was highly dependent on the identification of technical criteria’s that impacts the lifespan of a medical equipment where the affecting environmental factors didn’t receive the proper attention. The objective of our study is based on the need for introducing a new well-designed plan for evaluating medical equipment depending on two dimensions. According to this approach, the equipment that should be replaced or repaired will be classified based on a systematic method taking into account two essential criteria; the standard identified technical criteria and the added environmental criteria.

Keywords: technical, environmental, healthcare, characteristic of medical equipment

Procedia PDF Downloads 156

Authors: Siddhant Yadav, Ann Vincent, Sanjeev Nanda, Karen M. Fischer, Jessica A. Wright

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Statement of the Problem: Despite the growing popularity of cannabis in the general population, there are several unknowns regarding its use, specific reasons for use, patient’s choice of products, health benefits, and adverse effects. The aim of our study was to evaluate patient-reported information related to cannabis use that was recorded in the electronic medical records. Methodology & Theoretical Orientation: We manually reviewed the electronic medical records of cannabis users who were part of a large pharmacogenomic study. Data abstracted included demographics, level of education, concurrent alcohol and tobacco use, type of cannabis utilized, formulation, indication, symptomatic improvement, or adverse effects reported. Following this, we did a descriptive statistical analysis. Findings: Our sample of 164 cannabis users were predominantly female (73.2%); 66% of users reported using cannabis for medical indications. Of the 109 patients who recorded information pertaining to alcohol/tobacco use, two-thirds of cannabis users reported concurrent use of alcohol, and about half of them were former or current tobacco users. The mean age of cannabis use was 66 years. Regarding the type of cannabis, 34.1% reported using marijuana, 32.3% reported CBD use, 1.8% reported using THC, and 1.2% reported using Marinol. Oral formulations (capsules, oils, suspensions, brownies, cakes, and tea) were the most common route (44 %). Indications for use included chronic pain (n=76), anxiety (n=9), counteracting side effects of chemotherapy (n=4), and palliative reasons (n=2). Fifty-eight of the 76 users endorsed improvement in chronic pain (80%), 5 users reported improvement in anxiety, and 2 reported improvement in side effects of chemotherapy. Conclusion & Significance: The majority of our cannabis users were Caucasian females, and there was a high likelihood of coinciding use of alcohol/tobacco in patients using cannabis. Most of our patients used the oral formulation for chronic pain. Importantly, a considerable number of patients reported improvements in chronic pain, anxiety, and side effects of chemotherapy.

Keywords: cannabis use, adverse effects, medical practice, indications

Procedia PDF Downloads 93

Authors: Ilgin Gökaşar, Saman Ghaffarian

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The need for fast processed big data of transportation ridership (eg., smartcard data) and traffic operation (e.g., traffic detectors data) which requires a lot of computational power is incontrovertible in Intelligent Transportation Systems. Nowadays cloud computing is one of the important subjects and popular information technology solution for data processing. It enables users to process enormous measure of data without having their own particular computing power. Thus, it can also be a good selection for transportation big data processing as well. This paper intends to examine how the cloud computing can enhance transportation big data process with contrasting its advantages and disadvantages, and discussing cloud computing features.

Keywords: big data, cloud computing, Intelligent Transportation Systems, ITS, traffic data processing

Procedia PDF Downloads 470

Authors: Ali Asheibi

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The rapid increase in the size of databases required to store power quality monitoring data has demanded new techniques for analysing and understanding the data. One suggested technique to assist in analysis is data mining. Preparing raw data to be ready for data mining exploration take up most of the effort and time spent in the whole data mining process. Clustering is an important technique in data mining and machine learning in which underlying and meaningful groups of data are discovered. Large amounts of harmonic data have been collected from an actual harmonic monitoring system in a distribution system in Australia for three years. This amount of acquired data makes it difficult to identify operational events that significantly impact the harmonics generated on the system. In this paper, harmonic data preparation processes to better understanding of the data have been presented. Underlying classes in this data has then been identified using clustering technique based on the Minimum Message Length (MML) method. The underlying operational information contained within the clusters can be rapidly visualised by the engineers. The C5.0 algorithm was used for classification and interpretation of the generated clusters.

Keywords: data mining, harmonic data, clustering, classification

Procedia PDF Downloads 250

Authors: E. Y. Igde, S. Aydogan, F. E. Boran, D. Akay

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Patent data have an increasingly important role in economic growth, innovation, technical advantages and business strategies and even in countries competitions. Analyzing of patent data is crucial since patents cover large part of all technological information of the world. In this paper, we have used the linguistic summarization technique to prove the validity of the hypotheses related to patent data stated in the literature.

Keywords: data mining, fuzzy sets, linguistic summarization, patent data

Procedia PDF Downloads 272

Authors: Y. Atilgan Şengül

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Health information technologies promise higher quality, safer care and much more for both patients and professionals. Despite their promise, they are costly to develop and difficult to implement. On the other hand, user acceptance and usage determine the success of implemented information technology in healthcare. This study provides a model to understand health professionals’ perception and expectation of health information technology. Extensive literature review has been conducted to determine the main factors to be measured. A questionnaire has been designed as a measurement model and submitted to the personnel of an in vitro fertilization clinic. The respondents’ degree of agreement according to five-point Likert scale was 72% for convenient access to data and 69.4% for the importance of data security. There was a significant difference in acceptance of electronic data storage for female respondents. Also, other significant differences between professions were obtained.

Keywords: healthcare, health informatics, medical record system, questionnaire

Procedia PDF Downloads 174

Authors: M. Kebisek, L. Spendla, M. Kopcek, T. Skulavik

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In our paper we describe the security capabilities of data collection. Data are collected with probes located in the near and distant surroundings of the company. Considering the numerous obstacles e.g. forests, hills, urban areas, the data collection is realized in several ways. The collection of data uses connection via wireless communication, LAN network, GSM network and in certain areas data are collected by using vehicles. In order to ensure the connection to the server most of the probes have ability to communicate in several ways. Collected data are archived and subsequently used in supervisory applications. To ensure the collection of the required data, it is necessary to propose algorithms that will allow the probes to select suitable communication channel.

Keywords: communication, computer network, data collection, probe

Procedia PDF Downloads 362

Authors: Angely Sim Jia Wun, Sasa Arsovski

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Numerous studies have been conducted on the segmentation of medical images. Segmenting the lungs is one of the common research topics in those studies. Our research stemmed from the lack of solutions for automatic bone, airway, and vessel segmentation, despite the existence of multiple lung segmentation techniques. Consequently, currently, available software tools used for medical image segmentation do not provide automatic lung, bone, airway, and vessel segmentation. This paper presents segmentation techniques along with an interactive software tool architecture for segmenting bone, lung, airway, and vessel tissues. Additionally, we propose a method for creating binary masks from automatically generated segments. The key contribution of our approach is the technique for automatic image thresholding using adjustable Hounsfield values and binary mask extraction. Generated binary masks can be successfully used as a training dataset for deep-learning solutions in medical image segmentation. In this paper, we also examine the current software tools used for medical image segmentation, discuss our approach, and identify its advantages.

Keywords: lung segmentation, binary masks, U-Net, medical software tools

Procedia PDF Downloads 98

Authors: Szymon Szemik, Małgorzata Kowalska

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Objective: Medical students experience numerous demands during the education process, determining their quality of life (QoL) and health status. POLLEK (POLski LEKarz, eng. Polish Physician) study aims to identify and evaluate the quality of life, mental health status, and ever-recognized chronic diseases by simultaneously assessing their determinants in Polish medical students during long-term observation. Material and Methods: The POLLEK is the follow-up cohort study conducted among medical students at the Medical University of Silesia in Katowice. Students were followed during two observation periods: in their first year of studies, the academic year 2021/2022 (T1), and in their second year, the academic year 2022/2023 (T2). Results: The total number of participants in the first year of observation (T1) was 427 while in the second year (T2) was 335. Obtained results confirmed that the QoL score significantly decreased in their second year of studies mainly in the somatic and psychological domains. Moreover, we observed a significant increase in self-declared scoring of somatic symptoms year by year (from M=4.75 at T1 to M=8.06 at T2, p<0.001) in the GHQ-28 questionnaire survey. The determinants of QoL domains common to T1 and T2 remained self-declared health status, frequency of physical activity, and current financial situation. In the first year of evaluation, 56 students (13.10%) were overweight or obese, and 52 (15.8%) in the second. Regardless of the academic year, the increased risk of being overweight or obese was significantly associated with dissatisfaction with personal health, financial deficiencies, and a diet abundant in meat consumption. Conclusions: The QoL in medical students and selected determinants of their health status deteriorated during the observation period. Our findings suggest that medical schools should actively promote the activity needed to achieve a balance between schoolwork and the personal life of medical students from the beginning of university study.

Keywords: quality of life, mental health, medical students, follow-up study

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Authors: Isabell Koinig, Sandra Diehl

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In recent years, the health-care context has not been left unaffected by technological developments. In recent years, the Internet of Medical Things (IoMT)has not only led to a collaboration between disease management and advanced care coordination but also to more personalized health care and patient empowerment. With more than 40 % of all health technology being IoMT-related by 2020, questions regarding privacy become more prevalent, even more so during COVID-19when apps allowing for an intensive tracking of people’s whereabouts and their personal contacts cause privacy advocates to protest and revolt. There is a widespread tendency that even though users may express concerns and fears about their privacy, they behave in a manner that appears to contradict their statements by disclosing personal data. In literature, this phenomenon is discussed as a privacy paradox. While there are some studies investigating the privacy paradox in general, there is only scarce research related to the privacy paradox in the health sector and, to the authors’ knowledge, no empirical study investigating young people’s attitudes toward data security when using wearables and health apps. The empirical study presented in this paper tries to reduce this research gap by focusing on the area of digital and mobile health. It sets out to investigate the degree of importance individuals attribute to protecting their privacy and individual privacy protection strategies. Moreover, the question to which degree individuals between the ages of 20 and 30 years are willing to grant commercial parties access to their private data to use digital health services and apps are put to the test. To answer this research question, results from 6 focus groups with 40 participants will be presented. The focus was put on this age segment that has grown up in a digitally immersed environment. Moreover, it is particularly the young generation who is not only interested in health and fitness but also already uses health-supporting apps or gadgets. Approximately one-third of the study participants were students. Subjects were recruited in August and September 2019 by two trained researchers via email and were offered an incentive for their participation. Overall, results indicate that the young generation is well informed about the growing data collection and is quite critical of it; moreover, they possess knowledge of the potential side effects associated with this data collection. Most respondents indicated to cautiously handle their data and consider privacy as highly relevant, utilizing a number of protective strategies to ensure the confidentiality of their information. Their willingness to share information in exchange for services was only moderately pronounced, particularly in the health context, since health data was seen as valuable and sensitive. The majority of respondents indicated to rather miss out on using digital and mobile health offerings in order to maintain their privacy. While this behavior might be an unintended consequence, it is an important piece of information for app developers and medical providers, who have to find a way to find a user base for their products against the background of rising user privacy concerns.

Keywords: digital health, privacy, privacy paradox, IoMT

Procedia PDF Downloads 138

Authors: ShuYing Chung, Minchuan Huang, Iping Chen

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Taking the medical staff in an emergency ward of a medical center in Central Taiwan as the research object, the questionnaire data were collected by anonymous and voluntary reporting methods with structured questionnaire to explore the actual situation, willingness and attitude of organ donation. Only 80 valid questionnaires were collected. Among the 8 questions, the average correct rate was 5.9 + 1.2, and the correct rate was 73.13%. The willingness of organ donation that 7.5% of the people are not willing; 92.5% of the people are willing, of which 62.5% have considered but have not yet decided; 21.3% are willing but have not signed the consent of organ donation; They have signed the consent of organ donation 8.7%. The average total score (standard deviation) of attitude towards organ donation was 36.2. There is no significant difference between the demographic variables and the awareness and willingness of organ donation, but there is a significant correlation between the marital status and the attitude of organ donation.

Keywords: clinical psychology, organ donation, doctors affecting psychological disorders, commitment

Procedia PDF Downloads 139

Authors: Nay Myo Sandar

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With the growth of technologies and applications, a large amount of data has been producing at increasing rate from various resources such as social media networks, sensor devices, and other information serving devices. This large collection of massive, complex and exponential growth of dataset is called big data. The traditional database systems cannot store and process such data due to large and complexity. Consequently, cloud computing is a potential solution for data storage and processing since it can provide a pool of resources for servers and storage. However, moving large amount of data to and from is a challenging issue since it can encounter a high latency due to large data size. With respect to big data movement problem, this paper reviews the literature of previous works, discusses about research issues, finds out approaches for dealing with big data movement problem.

Keywords: Big Data, Cloud Computing, Big Data Movement, Network Techniques

Procedia PDF Downloads 88

Authors: Ahmed Mateen, Zhu Qingsheng, Ahmad Bilal

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In the current age of technology, information is the most precious asset of a company. Today, companies have a large amount of data. As the data become larger, access to data for some particular information is becoming slower day by day. Faster data processing to shape it in the form of information is the biggest issue. The major problems in distributed databases are the efficiency of data distribution and response time of data distribution. The security of data distribution is also a big issue. For these problems, we proposed a strategy that can maximize the efficiency of data distribution and also increase its response time. This technique gives better results for secure data distribution from multiple heterogeneous sources. The newly proposed technique facilitates the companies for secure data sharing efficiently and quickly.

Keywords: ER-schema, electronic record, P2P framework, API, query formulation

Procedia PDF Downloads 333

Authors: Sneha Shankar, Orlando Buendia, Will Evans

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Alpha-1 antitrypsin deficiency (AATD) is a rare, genetic, and multisystemic condition. Underdiagnosis is common, leading to chronic pulmonary and hepatic complications, increased resource utilization, and additional costs to the healthcare system. Currently, there is limited evidence of the direct medical costs of AATD diagnosis in the UK. This study explores the economic impact of AATD patients during the 3 years before diagnosis and to identify the major cost drivers using primary and secondary care electronic health record (EHR) data. The 3 years before diagnosis time period was chosen based on the ability of our tool to identify patients earlier. The AATD algorithm was created using published disease criteria and applied to 148 known AATD patients’ EHR found in a primary care database of 936,148 patients (413,674 Biobank and 501,188 in a single primary care locality). Among 148 patients, 9 patients were flagged earlier by the tool and, on average, could save 3 (1-6) years per patient. We analysed 101 of the 148 AATD patients’ primary care journey and 20 patients’ Hospital Episode Statistics (HES) data, all of whom had at least 3 years of clinical history in their records before diagnosis. The codes related to laboratory tests, clinical visits, referrals, hospitalization days, day case, and inpatient admissions attributable to AATD were examined in this 3-year period before diagnosis. The average cost per patient was calculated, and the direct medical costs were modelled based on the mean prevalence of 100 AATD patients in a 500,000 population. A deterministic sensitivity analysis (DSA) of 20% was performed to determine the major cost drivers. Cost data was obtained from the NHS National tariff 2020/21, National Schedule of NHS Costs 2018/19, PSSRU 2018/19, and private care tariff. The total direct medical cost of one hundred AATD patients three years before diagnosis in primary and secondary care in the UK was £3,556,489, with an average direct cost per patient of £35,565. A vast majority of this total direct cost (95%) was associated with inpatient admissions (£3,378,229). The DSA determined that the costs associated with tier-2 laboratory tests and inpatient admissions were the greatest contributors to direct costs in primary and secondary care, respectively. This retrospective study shows the role of EHRs in calculating direct medical costs and the potential benefit of new technologies for the early identification of patients with AATD to reduce the economic burden in primary and secondary care in the UK.

Keywords: alpha-1 antitrypsin deficiency, costs, digital health, early diagnosis

Procedia PDF Downloads 168

Authors: E. Steen, B. Dewulf, N. Müller, C. Vandycke, Y. Vandekerckhove

Abstract:

Introduction: The care for a ST-elevation myocardial infarction (STEMI) patient is time-critical. Reperfusion therapy within 90 minutes of initial medical contact is mandatory in the improvement of the outcome. Primary percutaneous coronary intervention (PCI) without previous fibrinolytic treatment, is the preferred reperfusion strategy in patients with STEMI, provided it can be performed within guideline-mandated times. Aim of the study: During a one year period (January 2013 to December 2013) the files of all consecutive STEMI patients with urgent referral from non-PCI facilities for primary PCI were reviewed. Special attention was given to a subgroup of patients with prior out-of-hospital medical contact generated by the 112-system. In an effort to reduce out-of-hospital system delay to definitive care a change in pre-hospital 112 dispatch strategies is proposed for these time-critical patients. Actual time recordings were compared with travel time simulations for two suggested scenarios. A first scenario (SC1) involves the decision by the on scene ground EMS (GEMS) team to transport the out-of-hospital diagnosed STEMI patient straight forward to a PCI centre bypassing the nearest non-PCI hospital. Another strategy (SC2) explored the potential role of helicopter EMS (HEMS) where the on scene GEMS team requests a PCI-centre based HEMS team for immediate medical transfer to the PCI centre. Methods and Results: 49 (29,1% of all) STEMI patients were referred to our hospital for emergency PCI by a non-PCI facility. 1 file was excluded because of insufficient data collection. Within this analysed group of 48 secondary referrals 21 patients had an out-of-hospital medical contact generated by the 112-system. The other 27 patients presented at the referring emergency department without prior contact with the 112-system. The table below shows the actual time data from first medical contact to definitive care as well as the simulated possible gain of time for both suggested strategies. The PCI-team was always alarmed upon departure from the referring centre excluding further in-hospital delay. Time simulation tools were similar to those used by the 112-dispatch centre. Conclusion: Our data analysis confirms prolonged reperfusion times in case of secondary emergency referrals for STEMI patients even with the use of HEMS. In our setting there was no statistical difference in gain of time between the two suggested strategies, both reducing the secondary referral generated delay with about one hour and by this offering all patients PCI within the guidelines mandated time. However, immediate HEMS activation by the on scene ground EMS team for transport purposes is preferred. This ensures a faster availability of the local GEMS-team for its community. In case these options are not available and the guideline-mandated times for primary PCI are expected to be exceeded, primary fibrinolysis should be considered in a non-PCI centre.

Keywords: STEMI, system delay, HEMS, emergency medicine

Procedia PDF Downloads 319

Authors: Jonah Kenei, Elisha Opiyo

Abstract:

Electronic health records, as a repository of patient information, is nowadays the most commonly used technology to record, store and review patient clinical records and perform other clinical tasks. However, the accurate identification and retrieval of relevant information from clinical records is a difficult task due to the unstructured nature of clinical documents, characterized in particular by a lack of clear structure. Therefore, medical practice is facing a challenge thanks to the rapid growth of health information in electronic health records (EHRs), mostly in narrative text form. As a result, it's becoming important to effectively manage the growing amount of data for a single patient. As a result, there is currently a requirement to visualize electronic health records (EHRs) in a way that aids physicians in clinical tasks and medical decision-making. Leveraging text visualization techniques to unstructured clinical narrative texts is a new area of research that aims to provide better information extraction and retrieval to support clinical decision support in scenarios where data generated continues to grow. Clinical datasets in electronic health records (EHR) offer a lot of potential for training accurate statistical models to classify facets of information which can then be used to improve patient care and outcomes. However, in many clinical note datasets, the unstructured nature of clinical texts is a common problem. This paper examines the very issue of getting raw clinical texts and mapping them into meaningful structures that can support healthcare professionals utilizing narrative texts. Our work is the result of a collaborative design process that was aided by empirical data collected through formal usability testing.

Keywords: classification, electronic health records, narrative texts, visualization

Procedia PDF Downloads 118

Authors: Policarpio Jr. Joves

Abstract:

Physicians in most teaching hospitals are commonly promoted into managerial roles, yet their training is mostly in clinical and scientific skills but not in leadership competencies. When they shift into roles of physician leadership, the majority hold on to their primary identity of physicians. These conflicting roles affect their identity and eventually their work. The physician leaders also face additional challenges related to academics which include incorporation of new knowledge into the existing curriculum, use of technology in the delivery of teaching, the need to train medical students outside of hospital wards, etc. The study aims to explore how physician leaders in teaching hospitals of private medical schools enact their leadership roles and how they face the challenges as physician leaders. The study setting shall be teaching hospitals of three private medical schools situated in the National Capital Region, Philippines. A multiple case study design shall be adopted in this research. Physicians shall be eligible to participate in the study if they are practicing clinicians limited to the five major clinical specialty: Internal Medicine, Pediatrics, Family Medicine, Surgery, Obstetrics and Gynecology. They must be teaching in the College of Medicine prior to their appointments as physician leaders in both medical school and teaching hospital. Semi-structured face-to-face interviews shall be utilized as a means of data collection, with open-ended questions, enabling physician leaders to present narratives about their identity, role enactment, conflicts, reaction of colleagues, and the challenges encountered in their day-to-day work as physician leaders. Interviews shall be combined with observations and review of records to gain more insights into how the physician leaders are 'doing' management. Within-case analysis shall be done initially followed by a thematic analysis across the cases, referred to as cross–case analysis or cross-case synthesis.

Keywords: academic leaders, academic managers, physician leaders, physician managers

Procedia PDF Downloads 346

Authors: Jinyan Li, Simon Fong, Raymond Wong, Mohammed Sabah, Fiaidhi Jinan

Abstract:

Clinical data analysis and forecasting have make great contributions to disease control, prevention and detection. However, such data usually suffer from highly unbalanced samples in class distributions. In this paper, we target at the binary imbalanced dataset, where the positive samples take up only the minority. We investigate two different meta-heuristic algorithms, particle swarm optimization and bat-inspired algorithm, and combine both of them with the synthetic minority over-sampling technique (SMOTE) for processing the datasets. One approach is to process the full dataset as a whole. The other is to split up the dataset and adaptively process it one segment at a time. The experimental results reveal that while the performance improvements obtained by the former methods are not scalable to larger data scales, the later one, which we call Adaptive Swarm Balancing Algorithms, leads to significant efficiency and effectiveness improvements on large datasets. We also find it more consistent with the practice of the typical large imbalanced medical datasets. We further use the meta-heuristic algorithms to optimize two key parameters of SMOTE. Leading to more credible performances of the classifier, and shortening the running time compared with the brute-force method.

Keywords: Imbalanced dataset, meta-heuristic algorithm, SMOTE, big data

Procedia PDF Downloads 443