Telehealth System for Effective Treatment in COVID-19 Pandemics

2022 ◽  
pp. 328-339
Author(s):  
Vijay M. Mane ◽  
Sanjiv Patki ◽  
Anil Vishwanathrao Dhumma ◽  
Ketan J. Apte
Keyword(s):  
Effective Treatment ◽  
Healthcare System ◽  
Medical Staff ◽  
Healthcare Systems ◽  
Medical Facilities

The current coronavirus disease 2019 (COVID-19) pandemic has placed tremendous pressure on the worldwide healthcare systems. The hospitals are instructing patients to quarantine and providing medical facilities to COVID-19 patients at their homes. The feedback and proper monitoring of the quarantined patients is very important for the healthcare system. This situation has forced the use of telehealth systems to offer the delivery of medical facilities over a distance. This chapter presents a wireless telehealth system to monitor the home quarantined COVID-19 patients effectively. When an abnormality is detected then an alert is sent to the concerned hospital or doctor. The presented system allows setting the thresholds and providing alerts, reminders, and notifications to the doctors. The prototype of the presented system has been successfully developed, implemented, and tested, which helps the medical staff to monitor and treat the patients remotely, especially the coronavirus patients who are home quarantined.

Incorporating Human Factors Into a Healthcare System’s COVID-19 Communication Strategy

2021 ◽  
Vol 10 (1) ◽  
pp. 175-179
Author(s):  
Rebecca L. Butler ◽  
Ann Katherine Hoobler ◽  
Lucy C. Stein ◽  
Erica S. Hoenig ◽  
Laura M. Lee ◽  
...  
Keyword(s):  
Human Factors ◽  
Healthcare System ◽  
Communication Strategies ◽  
Clinical Information ◽  
Effective Communication ◽  
Healthcare Systems ◽  
User Feedback ◽  
Communication Strategy ◽  
Successful Communication

The COVID-19 era has been an age of change for healthcare systems worldwide. At the beginning of the pandemic in particular, there was a huge need to rapidly communicate new and constantly changing information with critical safety implications. Previously successful communication strategies were not adequate for this unprecedented challenge. At MedStar Health, the Quality & Safety team led a unique partnership between human factors experts, clinical teams, and the communications department to develop a three-pronged strategy for effective communication during the pandemic. This strategy incorporated the following components: 1) Using human factors and usability concepts to distill complex clinical information into easy-to-understand infographics for frontline associates; 2) Creating regular, succinct messaging to distribute the information and provide frequent updates throughout the healthcare system; and 3) Designing and maintaining a usable webpage where associates could access up-to-date information relevant to their specialty at any time, on or off the hospital network. This strategy, which was dynamic and adapted to user feedback, was supported by associates as a streamlined method for communicating important information throughout the pandemic.

scholarly journals Implementation of Fog computing in IoT-based healthcare system

2018 ◽  
Vol 14 (2) ◽  
Author(s):  
Mirjana Maksimović
Keyword(s):  
Healthcare System ◽  
Low Cost ◽  
Fog Computing ◽  
Healthcare Systems ◽  
Healthcare Sector ◽  
Smart Devices ◽  
New Paradigm ◽  
Healthcare Applications ◽  
Privacy And Security ◽  
Main Challenge

Nowhere do the technology advancements bring improvements than in the healthcare sector, constantly creating new healthcare applications and systems which completely revolutionize the healthcare domain. The appearance of Internet of Things (IoT) based healthcare systems has immensely improved quality and delivery of care, and significantly reduced the costs. At the same time, these systems generate the enormous amount of health-associated data which has to be properly gathered, analyzed and shared. The smart devices, as the components of IoT-driven healthcare systems, are not able to deal with IoT-produced data, neither data posting to the Cloud is the appropriate solution. To overcome smart devices’ and Cloud’s limitations the new paradigm, known as Fog computing, has appeared, where an additional layer processes the data and sends the results to the Cloud. Despite numerous benefits Fog computing brings into IoT-based environments, the privacy and security issues remain the main challenge for its implementation. The reasons for integrating the IoT-based healthcare system and Fog computing, benefits and challenges, as well as the proposition of simple low-cost system are presented in this paper.

scholarly journals OPTIMIZING TELEMEDICINE FRAMEWORK USING FOG COMPUTING FOR SMART HEALTHCARE SYSTEMS

2021 ◽  
Author(s):  
Michael Enbibel
Keyword(s):  
Data Management ◽  
Healthcare System ◽  
Data Flow ◽  
System Organization ◽  
Fog Computing ◽  
Healthcare Systems ◽  
Distributed Data ◽  
Smart Healthcare ◽  
Network Latency

This research is done for optimizing telemedicine framework by using fogging or fog computing for smart healthcare systems. Fog computing is used to solve the issues that arise on telemedicine framework of smart healthcare system like Infrastructural, Implementation, Acceptance, Data Management, Security, Bottleneck system organization, and Network latency Issues. we mainly used Distributed Data Flow (DDF) method using fog computing in order to fully solve the listed issues.

Can the health care system be effective? - The research results

2020 ◽  
Vol 3 (14) ◽  
pp. 01-06
Author(s):  
Joanna Jasińska
Keyword(s):  
Health Care ◽  
Personalized Medicine ◽  
Healthcare System ◽  
Health Systems ◽  
Basic Problem ◽  
Economic Value ◽  
Healthcare Systems ◽  
Scientific Databases ◽  
Concepts Of Health

The different definitions of efficiency (in their medical meanings) are presented as the result of meta-reviews found in scientific databases. Efficacy and efficiency are often mismatched with effectiveness in the research of healthcare systems in different countries. In addition to the classic Bismarck’s and Beveridge’s models the modern concepts of health systems include personalized medicine, recognition of health as economic value. However, the basic problem in the Polish healthcare system is the low quality of overly specific and often changed legislation.

User Behavioral Intention toward Using Mobile Healthcare System

2015 ◽  
pp. 128-143 ◽  
Author(s):  
Pantea Keikhosrokiani ◽  
Norlia Mustaffa ◽  
Nasriah Zakaria ◽  
Ahmad Suhaimi Baharudin
Keyword(s):  
Least Squares ◽  
Partial Least Squares ◽  
Healthcare System ◽  
Behavioral Intention ◽  
Measurement Model ◽  
Healthcare Systems ◽  
Intention To Use ◽  
Mobile Healthcare ◽  
Effort Expectancy ◽  
Behavioral Intention To Use

This chapter introduces Mobile Healthcare Systems (MHS) and employs some theories to explore the behavioral intention of Smartphone users in Penang, Malaysia to use MHS. A survey was conducted in the form of questionnaire to Smartphone users in Penang, Malaysia for the duration of three weeks starting in September 2013. A total number of 123 valid surveys out of 150 were returned, which is equivalent to a response rate of 82%. The authors use Partial Least Squares (PLS) for analyzing the proposed measurement model. The factors that are tested are self-efficacy, anxiety, effort expectancy, performance expectancy, attitude, and behavioral intention to use. The results indicate which factors have a significant effect on Smartphone users' behavioral intention and which factors are not significant. The results assist in assessing whether MHS is highly demanded by users or not, and will assist in development of the system in the future.

scholarly journals Has the Efficiency of China’s Healthcare System Improved after Healthcare Reform? A Network Data Envelopment Analysis and Tobit Regression Approach

2019 ◽  
Vol 16 (23) ◽  
pp. 4847 ◽  
Author(s):  
Guangwen Gong ◽  
Yingchun Chen ◽  
Hongxia Gao ◽  
Dai Su ◽  
Jingjing Chang
Keyword(s):  
Data Envelopment Analysis ◽  
Healthcare System ◽  
Health Expenditure ◽  
Healthcare Reform ◽  
Healthcare Systems ◽  
Network Data ◽  
Data Envelopment ◽  
Tobit Regression ◽  
Network Data Envelopment Analysis ◽  
Overall Efficiency

Background: A healthcare system refers to a typical network production system. Network data envelopment analysis (DEA) show an advantage than traditional DEA in measure the efficiency of healthcare systems. This paper utilized network data envelopment analysis to evaluate the overall and two substage efficiencies of China’s healthcare system in each of its province after the implementation of the healthcare reform. Tobit regression was performed to analyze the factors that affect the overall efficiency of healthcare systems in the provinces of China. Methods: Network DEA were obtained on MaxDEA 7.0 software, and the results of Tobit regression analysis were obtained on StataSE 15 software. The data for this study were acquired from the China health statistics yearbook (2009–2018) and official websites of databases of Chinese national bureau. Results: Tobit regression reveals that regions and government health expenditure effect the efficiency of the healthcare system in a positive way: the number of high education enrollment per 100,000 inhabitants, the number of public hospital, and social health expenditure effect the efficiency of healthcare system were negative. Conclusion: Some provincial overall efficiency has fluctuating increased, while other provincial has fluctuating decreased, and the average overall efficiency scores were fluctuations increase.

Key Considerations for the Adoption and Implementation of Knowledge Management in Healthcare Operations

2010 ◽  
pp. 125-142 ◽  
Author(s):  
Nilmini Wickramasinghe ◽  
Elie Geisler
Keyword(s):  
Knowledge Management ◽  
Healthcare System ◽  
Healthcare Costs ◽  
Cost Effective ◽  
Healthcare Setting ◽  
Healthcare Systems ◽  
Healthcare Operations ◽  
Healthcare Settings ◽  
Adoption And Implementation ◽  
The U.S

The importance of knowledge management (KM) to organizations in today’s competitive environment is being recognized as paramount and significant. This is particularly evident for healthcare both globally and in the U.S. The U.S. healthcare system is facing numerous challenges in trying to deliver cost effective, high quality treatments and is turning to KM techniques and technologies for solutions in an attempt to achieve this goal. While the challenges facing the U.S. healthcare are not dissimilar to those facing healthcare systems in other nations, the U.S. healthcare system leads the field with healthcare costs more than 15% of GDP and rising exponentially. What is becoming of particular interest when trying to find a solution is the adoption and implementation of KM and associated KM technologies in the healthcare setting, an arena that has to date been notoriously slow to adopt technologies and new approaches for the practice management side of healthcare. We examine this issue by studying the barriers encountered in the adoption and implementation of specific KM technologies in healthcare settings. We then develop a model based on empirical data and using this model draw some conclusions and implications for orthopaedics.

scholarly journals Soft skills for esearch on gender and sexual minorities

2019 ◽  
Vol 29 (Supplement_4) ◽  
Author(s):  
A van der Star
Keyword(s):  
Healthcare System ◽  
Sexual Minorities ◽  
Healthcare Professionals ◽  
Soft Skills ◽  
Healthcare Systems

Abstract LGBTQI+ individuals and the healthcare system. Arjan will present a variety of issues that LGBTQI+ individuals may face when trying to access healthcare or during interactions with healthcare professionals. The group will discuss how and which soft skills would tie into these issues and will brainstorm about ideas for strategies tackling LGBTQI+ discrimination in healthcare systems across Europe. (20’)

scholarly journals Virtual volunteers: the importance of restructuring medical volunteering during the COVID-19 pandemic

2020 ◽  
Vol 46 (4) ◽  
pp. 537-540 ◽  
Author(s):  
Zachary Pickell ◽  
Kathleen Gu ◽  
Aaron M Williams
Keyword(s):  
Viral Infection ◽  
Patient Care ◽  
Healthcare System ◽  
Health Systems ◽  
Video Conferencing ◽  
Healthcare Systems ◽  
Patient Experiences ◽  
Online Video ◽  
Virtual Volunteering

Healthcare systems have postponed medical volunteering services in response to the COVID-19 pandemic. However, much of the aid provided by these volunteers is crucial to patient care and hospital functioning in the American healthcare system. The adoption of online video conferencing platforms in healthcare—telehealth—offers a novel solution for volunteering during this pandemic. Virtual volunteering can alleviate pressures on medical workers, enhance patient experiences, reduce the risk of viral infection and provide a sense of normalcy for patients and families. Although further study is required, this should be an avenue considered by health systems.

scholarly journals Modeling and simulation framework for value-based healthcare systems

SIMULATION ◽  
2018 ◽  
Vol 95 (6) ◽  
pp. 481-497 ◽  
Author(s):  
Mamadou Kaba Traoré ◽  
Gregory Zacharewicz ◽  
Raphaël Duboz ◽  
Bernard Zeigler
Keyword(s):  
Modeling And Simulation ◽  
Healthcare System ◽  
Healthcare Systems ◽  
Simulation Framework ◽  
Multiple Perspectives ◽  
Levels Of Abstraction ◽  
Holistic View ◽  
Complex Processes ◽  
Distributed Components ◽  
Parameter Values

Regardless of the coordination of its activities, a healthcare system is composed of a large number of distributed components that are interrelated by complex processes. Understanding the behavior of the overall system is becoming a major concern among healthcare managers and decision-makers. This paper presents a modeling and simulation framework to support a holistic analysis of healthcare systems through a stratification of the levels of abstraction into multiple perspectives and their integration in a common simulation framework. In each of the perspectives, models of different components of a healthcare system can be developed and coupled together. Concerns from other perspectives are abstracted as parameters, that is, we reflect the parameter values of other perspectives through explicit assumptions and simplifications in such models. Consequently, the resulting top model within each perspective can be coupled with its experimental frame to run simulations and derive results. Components of the various perspectives are integrated to provide a holistic view of the healthcare problem and system under study. The resulting global model can be coupled with a holistic experimental frame to derive results that cannot be accurately addressed in any of the perspectives taken alone. Furthermore, as we endeavored to allow perspective-specific experts to contribute to the modeling process, we took benefit of results originating from research efforts that Norbert Giambiasi initiated in the 2000s, which his PhD students further developed with their own PhD students.

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