ORGANIZATIONAL BEHAVIOR IN HEALTH INSTITUTIONS CONFERENCE


Organizational Behavior in Health Institutions Conference is one of the leading research topics in the international research conference domain. Organizational Behavior in Health Institutions is a conference track under the Healthcare Conference which aims to bring together leading academic scientists, researchers and research scholars to exchange and share their experiences and research results on all aspects of Healthcare.

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Organizational Behavior in Health Institutions is also a leading research topic on Google Scholar, Semantic Scholar, Zenedo, OpenAIRE, BASE, WorldCAT, Sherpa/RoMEO, Elsevier, Scopus, Web of Science.

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I. INTERNATIONAL HEALTHCARE CONFERENCE

MARCH 19 - 20, 2019
ISTANBUL, TURKEY

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II. INTERNATIONAL HEALTHCARE CONFERENCE

JUNE 26 - 27, 2019
PARIS, FRANCE

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III. INTERNATIONAL HEALTHCARE CONFERENCE

AUGUST 21 - 22, 2019
LONDON, UNITED KINGDOM

FINISHED

IV. INTERNATIONAL HEALTHCARE CONFERENCE

OCTOBER 08 - 09, 2019
NEW YORK, UNITED STATES

FINISHED

V. INTERNATIONAL HEALTHCARE CONFERENCE

DECEMBER 12 - 13, 2019
ROME, ITALY

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VI. INTERNATIONAL HEALTHCARE CONFERENCE

FEBRUARY 13 - 14, 2020
LONDON, UNITED KINGDOM

FINISHED

VII. INTERNATIONAL HEALTHCARE CONFERENCE

APRIL 15 - 16, 2020
BARCELONA, SPAIN

FINISHED

VIII. INTERNATIONAL HEALTHCARE CONFERENCE

MAY 11 - 12, 2020
ISTANBUL, TURKEY

FINISHED

IX. INTERNATIONAL HEALTHCARE CONFERENCE

JUNE 05 - 06, 2020
SAN FRANCISCO, UNITED STATES

FINISHED

X. INTERNATIONAL HEALTHCARE CONFERENCE

JULY 20 - 21, 2020
PARIS, FRANCE

FINISHED

XI. INTERNATIONAL HEALTHCARE CONFERENCE

AUGUST 10 - 11, 2020
NEW YORK, UNITED STATES

FINISHED

XII. INTERNATIONAL HEALTHCARE CONFERENCE

SEPTEMBER 10 - 11, 2020
TOKYO, JAPAN

FINISHED

XIII. INTERNATIONAL HEALTHCARE CONFERENCE

SEPTEMBER 16 - 17, 2020
ZÜRICH, SWITZERLAND

FINISHED

XIV. INTERNATIONAL HEALTHCARE CONFERENCE

OCTOBER 21 - 22, 2020
BARCELONA, SPAIN

FINISHED

XV. INTERNATIONAL HEALTHCARE CONFERENCE

NOVEMBER 02 - 03, 2020
SAN FRANCISCO, UNITED STATES

FINISHED

XVI. INTERNATIONAL HEALTHCARE CONFERENCE

NOVEMBER 12 - 13, 2020
ISTANBUL, TURKEY

FINISHED

XVII. INTERNATIONAL HEALTHCARE CONFERENCE

NOVEMBER 19 - 20, 2020
SINGAPORE, SINGAPORE

FINISHED

XVIII. INTERNATIONAL HEALTHCARE CONFERENCE

DECEMBER 15 - 16, 2020
BANGKOK, THAILAND

FINISHED

XIX. INTERNATIONAL HEALTHCARE CONFERENCE

DECEMBER 28 - 29, 2020
PARIS, FRANCE

FINISHED

XX. INTERNATIONAL HEALTHCARE CONFERENCE

FEBRUARY 13 - 14, 2021
LONDON, UNITED KINGDOM

FINISHED

XXI. INTERNATIONAL HEALTHCARE CONFERENCE

APRIL 15 - 16, 2021
BARCELONA, SPAIN

FINISHED

XXII. INTERNATIONAL HEALTHCARE CONFERENCE

MAY 11 - 12, 2021
ISTANBUL, TURKEY

FINISHED

XXIII. INTERNATIONAL HEALTHCARE CONFERENCE

JUNE 05 - 06, 2021
SAN FRANCISCO, UNITED STATES

FINISHED

XXIV. INTERNATIONAL HEALTHCARE CONFERENCE

JULY 20 - 21, 2021
PARIS, FRANCE

FINISHED

XXV. INTERNATIONAL HEALTHCARE CONFERENCE

AUGUST 10 - 11, 2021
NEW YORK, UNITED STATES

FINISHED

XXVI. INTERNATIONAL HEALTHCARE CONFERENCE

SEPTEMBER 10 - 11, 2021
TOKYO, JAPAN

FINISHED

XXVII. INTERNATIONAL HEALTHCARE CONFERENCE

SEPTEMBER 16 - 17, 2021
ZÜRICH, SWITZERLAND

FINISHED

XXVIII. INTERNATIONAL HEALTHCARE CONFERENCE

OCTOBER 21 - 22, 2021
BARCELONA, SPAIN

FINISHED

XXIX. INTERNATIONAL HEALTHCARE CONFERENCE

NOVEMBER 02 - 03, 2021
SAN FRANCISCO, UNITED STATES

FINISHED

XXX. INTERNATIONAL HEALTHCARE CONFERENCE

NOVEMBER 12 - 13, 2021
ISTANBUL, TURKEY

FINISHED

XXXI. INTERNATIONAL HEALTHCARE CONFERENCE

NOVEMBER 19 - 20, 2021
SINGAPORE, SINGAPORE

FINISHED

XXXII. INTERNATIONAL HEALTHCARE CONFERENCE

DECEMBER 15 - 16, 2021
BANGKOK, THAILAND

FINISHED

XXXIII. INTERNATIONAL HEALTHCARE CONFERENCE

DECEMBER 28 - 29, 2021
PARIS, FRANCE

Healthcare Conference Call For Papers are listed below:

Previously Published Papers on "Organizational Behavior in Health Institutions Conference"

  • Patient Perspectives on Telehealth during the Pandemic in the United States
    Authors: Manal Sultan Alhussein, Xiang Michelle Liu, Keywords: Telehealth, patient satisfaction, pandemic, healthcare, remote patient monitor. DOI:10.5281/zenodo. Abstract: Telehealth is an advanced technology using digital information and telecommunication facilities that provide access to health services from a distance. It slows the transmission factor of COVID-19, especially for elderly patients and patients with chronic diseases during the pandemic. Therefore, understanding patient perspectives on telehealth services and the factors impacting their option of telehealth service will shed light on the measures that healthcare providers can take to improve the quality of telehealth services. This study aimed to evaluate perceptions of telehealth services among different patient groups and explore various aspects of telehealth utilization in the United States during the COVID-19 pandemic. An online survey distributed via social media platforms was used to collect research data. In addition to the descriptive statistics, both correlation and regression analyses were conducted to test research hypotheses. The empirical results highlighted that the factors such as accessibility to telehealth services and the type of specialty clinics that the patients required play important roles in the effectiveness of telehealth services they received. However, the results found that patients’ waiting time to receive telehealth services and their annual income did not significantly influence their desire to select receiving healthcare services via telehealth. The limitations of the study and future research directions are discussed.
  • Telehealth Ecosystem: Challenge and Opportunity
    Authors: R. Poonsuph, Keywords: telehealth, Internet hospital, HealthTech, InsurTech DOI:10.5281/zenodo. Abstract: Technological innovation plays a crucial role in virtual healthcare services. A growing number of telehealth platforms are concentrating on using digital tools to improve the quality and availability of care. As a result, telehealth represents an opportunity to redesign the way health services are delivered. The research objective is to discover a new business model for digital health services and related industries to participate with telehealth solutions. The business opportunity is valuable for healthcare investors as a startup company to further investigations or implement the telehealth platform. The paper presents a digital healthcare business model and business opportunities to related industries. These include digital healthcare services extending from a traditional business model and use cases of business opportunities to related industries. Although there are enormous business opportunities, telehealth is still challenging due to the patient adaption and digital transformation process within a healthcare organization.
  • An Overview of Technology Availability to Support Remote Decentralized Clinical Trials
    Authors: S. Huber, B. Schnalzer, B. Alcalde, S. Hanke, L. Mpaltadoros, T. G. Stavropoulos, S. Nikolopoulos, I. Kompatsiaris, L. Pérez-Breva, V. Rodrigo-Casares, J. Fons-Martínez, J. de Bruin, Keywords: architectures and frameworks for health informatics systems, clinical trials, information and communications technology, remote decentralized clinical trials, technology availability DOI:10.5281/zenodo. Abstract: Developing new medicine and health solutions and improving patient health currently rely on the successful execution of clinical trials, which generate relevant safety and efficacy data. For their success, recruitment and retention of participants are some of the most challenging aspects of protocol adherence. Main barriers include: i) lack of awareness of clinical trials; ii) long distance from the clinical site; iii) the burden on participants, including the duration and number of clinical visits, and iv) high dropout rate. Most of these aspects could be addressed with a new paradigm, namely the Remote Decentralized Clinical Trials (RDCTs). Furthermore, the COVID-19 pandemic has highlighted additional advantages and challenges for RDCTs in practice, allowing participants to join trials from home and not depending on site visits, etc. Nevertheless, RDCTs should follow the process and the quality assurance of conventional clinical trials, which involve several processes. For each part of the trial, the Building Blocks, existing software and technologies were assessed through a systematic search. The technology needed to perform RDCTs is widely available and validated but is yet segmented and developed in silos, as different software solutions address different parts of the trial and at various levels. The current paper is analyzing the availability of technology to perform RDCTs, identifying gaps and providing an overview of Basic Building Blocks and functionalities that need to be covered to support the described processes.
  • Manual Pit Emptiers and Their Heath: Profiles, Determinants and Interventions
    Authors: Ivy Chumo, Sheillah Simiyu, Hellen Gitau, Isaac Kisiangani, Caroline Kabaria Kanyiva Muindi, Blessing Mberu, Keywords: Sanitation, occupational health, manual emptiers, informal settlements. DOI:10.5281/zenodo. Abstract: The global sanitation workforce bridges the gap between sanitation infrastructure and the provision of sanitation services through essential public service work. Manual pit emptiers often perform the work at the cost of their dignity, safety, and health as their work requires repeated heavy physical activities such as lifting, carrying, pulling, and pushing. This exposes them to occupational and environmental health hazards and risking illness, injury, and death. The study will extend the studies by presenting occupational health risks and suggestions for improvement in informal settlements of Nairobi, Kenya. This is a qualitative study conducted among sanitation stakeholders in Korogocho, Mukuru and Kibera informal settlements in Nairobi. Data were captured using digital voice recorders, transcribed and thematically analysed. The discussion notes were further supported by observational notes made during the interviews. These formed the basis for a robust picture of occupational health of manual pit emptiers; a lack or inappropriate use of protective clothing, and prolonged duration of working hours were described to contribute to the occupational health hazard. To continue working, manual pit emptiers had devised coping strategies which include working in groups, improvised protective clothing, sharing the available protective clothing, working at night and consuming alcohol drinks while at work. Many of these strategies are detrimental to their health. Occupational health hazards among pit emptiers are key for effective working and is as a result of a lack of collaboration amongst stakeholders linked to health, safety and lack of PPE of pit emptiers. Collaborations amongst sanitation stakeholders is paramount for health, safety, and in ensuring the provision and use of personal protective devices.
  • Building an Integrated Relational Database from Swiss Nutrition National Survey and Swiss Health Datasets for Data Mining Purposes
    Authors: Ilona Mewes, Helena Jenzer, Farshideh Einsele, Keywords: Health informatics, data mining, nutritional and health databases, nutritional and chronical databases. DOI:10.5281/zenodo. Abstract: Objective: The objective of the study was to integrate two big databases from Swiss nutrition national survey (menuCH) and Swiss health national survey 2012 for data mining purposes. Each database has a demographic base data. An integrated Swiss database is built to later discover critical food consumption patterns linked with lifestyle diseases known to be strongly tied with food consumption. Design: Swiss nutrition national survey (menuCH) with approx. 2000 respondents from two different surveys, one by Phone and the other by questionnaire along with Swiss health national survey 2012 with 21500 respondents were pre-processed, cleaned and finally integrated to a unique relational database. Results: The result of this study is an integrated relational database from the Swiss nutritional and health databases.
  • A Deep-Learning Based Prediction of Pancreatic Adenocarcinoma with Electronic Health Records from the State of Maine
    Authors: Xiaodong Li, Peng Gao, Chao-Jung Huang, Shiying Hao, Xuefeng B. Ling, Yongxia Han, Yaqi Zhang, Le Zheng, Chengyin Ye, Modi Liu, Minjie Xia, Changlin Fu, Bo Jin, Karl G. Sylvester, Eric Widen, Keywords: Cancer prediction, deep learning, electronic health records, pancreatic adenocarcinoma. DOI:10.5281/zenodo. Abstract: Predicting the risk of Pancreatic Adenocarcinoma (PA) in advance can benefit the quality of care and potentially reduce population mortality and morbidity. The aim of this study was to develop and prospectively validate a risk prediction model to identify patients at risk of new incident PA as early as 3 months before the onset of PA in a statewide, general population in Maine. The PA prediction model was developed using Deep Neural Networks, a deep learning algorithm, with a 2-year electronic-health-record (EHR) cohort. Prospective results showed that our model identified 54.35% of all inpatient episodes of PA, and 91.20% of all PA that required subsequent chemoradiotherapy, with a lead-time of up to 3 months and a true alert of 67.62%. The risk assessment tool has attained an improved discriminative ability. It can be immediately deployed to the health system to provide automatic early warnings to adults at risk of PA. It has potential to identify personalized risk factors to facilitate customized PA interventions.
  • Prevalence, Associated Factors, and Help-Seeking Behavior of Psychological Distress among International Students at the National University of Malaysia
    Authors: Khadiga Kahwa, Aniza Ismail, Keywords: Anxiety, depression, stress, help-seeking behavior, students. DOI:10.5281/zenodo. Abstract: Depression, anxiety, and stress are associated with decreased role functioning, productivity, and quality of life. International students are more prone to psychological distress as they face many stressors while studying abroad. The objectives of the study were to determine the prevalence and associated factors of depression, anxiety, and stress among international students, their help-seeking behavior, and their awareness of the available on-campus mental support services. A cross-sectional study with a purposive sampling method was performed on 280 international students at Universiti Kebangsaan Malaysia (UKM) between the age of 18 and 35 years. The Depression Anxiety Stress Scale-21 (DASS-21) questionnaire was used anonymously to assess the mental health of students. Socio-demographic, help-seeking behavior, and awareness data were obtained. Independent sample t-test, one-way ANOVA test, and multiple linear regression were used to explore associated factors. The overall prevalence of depression, anxiety, and stress among international students were 58.9%, 71.8%, and 53.9%, respectively. Age was significantly associated with depression and anxiety. Ethnicity showed a significant association with depression and stress. No other factors were found to be significantly associated with psychological distress. Only 9.6% of the international students had sought help from on-campus mental support services. Students who were aware of the presence of such services were only 21.4% of the participants. In conclusion, this study addressed the gap in the literature on the mental health of international students and provided data that could be used in intervention programs to improve the mental health of the increasing number of international students in Malaysia.
  • Robotic Assistance in Nursing Care: Survey on Challenges and Scenarios
    Authors: Pascal Gliesche, Kathrin Seibert, Christian Kowalski, Dominik Domhoff, Max Pfingsthorn, Karin Wolf-Ostermann, Andreas Hein, Keywords: Robotics and automation, engineering management, engineering in medicine and biology, medical services, public healthcare. DOI:10.5281/zenodo. Abstract: Robotic assistance in nursing care is an increasingly important area of research and development. Facing a shortage of labor and an increasing number of people in need of care, the German Nursing Care Innovation Center (Pflegeinnovationszentrum, PIZ) aims to address these challenges from the side of technology. Little is known about nurses experiences with existing robotic assistance systems. Especially nurses perspectives on starting points for the development of robotic solutions, that target recurring burdensome tasks in everyday nursing care, are of interest. This paper presents findings focusing on robotics resulting from an explanatory mixed-methods study on nurses experiences with and their expectations for innovative technologies in nursing care in stationary and ambulant care facilities and hospitals in Germany. Based on the findings, eight scenarios for robotic assistance are identified based on the real needs of practitioners. An initial system addressing a single use-case is described to show perspectives for the use of robots in nursing care.
  • A Taxonomy of Behavior for a Medical Coordinator by Utlizing Leadership Styles
    Authors: Aryana Collins Jackson, Elisabetta Bevacqua, Pierre De Loor, Ronan Querrec, Keywords: Medical, leadership styles, taxonomy, human behavior. DOI:10.5281/zenodo.10.5281/zenodo.5913527 Abstract: This paper presents a taxonomy of non-technical skills, communicative intentions, and behavior for an individual acting as a medical coordinator. In medical emergency situations, a leader among the group is imperative to both patient health and team emotional and mental health. Situational Leadership is used to make clear and easy-to-follow guidelines for behavior depending on circumstantial factors. Low-level leadership behaviors belonging to two different styles, directive and supporting, are identified from literature and are included in the proposed taxonomy. The high-level information in the taxonomy consists of the necessary non-technical skills belonging to a medical coordinator: situation awareness, decision making, task management, and teamwork. Finally, communicative intentions, dimensions, and functions are included. Thus this work brings high-level and low-level information - medical non-technical skills, communication capabilities, and leadership behavior - into a single versatile taxonomy of behavior.
  • Vision-Based Daily Routine Recognition for Healthcare with Transfer Learning
    Authors: Bruce X. B. Yu, Yan Liu, Keith C. C. Chan, Keywords: Daily activity recognition, healthcare, IoT sensors, transfer learning. DOI:10.5281/zenodo. Abstract: We propose to record Activities of Daily Living (ADLs) of elderly people using a vision-based system so as to provide better assistive and personalization technologies. Current ADL-related research is based on data collected with help from non-elderly subjects in laboratory environments and the activities performed are predetermined for the sole purpose of data collection. To obtain more realistic datasets for the application, we recorded ADLs for the elderly with data collected from real-world environment involving real elderly subjects. Motivated by the need to collect data for more effective research related to elderly care, we chose to collect data in the room of an elderly person. Specifically, we installed Kinect, a vision-based sensor on the ceiling, to capture the activities that the elderly subject performs in the morning every day. Based on the data, we identified 12 morning activities that the elderly person performs daily. To recognize these activities, we created a HARELCARE framework to investigate into the effectiveness of existing Human Activity Recognition (HAR) algorithms and propose the use of a transfer learning algorithm for HAR. We compared the performance, in terms of accuracy, and training progress. Although the collected dataset is relatively small, the proposed algorithm has a good potential to be applied to all daily routine activities for healthcare purposes such as evidence-based diagnosis and treatment.

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