scholarly journals Embedding persuasive design for self-health management systems in Dutch healthcare informatics education: Application of a theory-based method

2018 ◽  
Vol 25 (4) ◽  
pp. 1631-1646 ◽  
Author(s):  
Laurence Alpay ◽  
Rob Doms ◽  
Harmen Bijwaard
Keyword(s):  
Health Informatics ◽  
Healthcare Professionals ◽  
Health Management ◽  
Methodological Approach ◽  
Health Information Systems ◽  
Health Condition ◽  
Management Systems ◽  
Pilot Phase ◽  
Healthcare Organizations ◽  
Know How

The development of eHealth is dramatically changing the way healthcare is provided and organized. eHealth applications are used not only by healthcare professionals but also by patients specifically to self-manage their health condition. The development of eHealth applications requires a new methodological approach, departing from the more conventional methods dedicated to designing health information systems. There is a gap between theories to design persuasive eHealth applications and practices. In the Netherlands, eHealth innovation emerges from three areas. In research, the development of eHealth application often remains in a pilot phase. Healthcare organizations are also keen to innovate but do not always have the know-how. We further witness technology push from business and industry, undermining the co-creation process of the innovation. We consequently advocate an integrated, systematic and practical but scientifically based methodology to design effective persuasive eHealth applications. This approach is being successfully embedded in our educational health informatics program.

scholarly journals Consumer Health Informatics: The Application Of ICT In Improving Patient-Provider Partnership For A Better Health Care

2014 ◽  
Vol 6 (2) ◽  
Author(s):  
Benjamin Abaidoo ◽  
Benjamin Teye Larweh
Keyword(s):  
Health Informatics ◽  
Health Condition ◽  
Consumer Health Informatics ◽  
Consumer Health ◽  
Time Data ◽  
Healthcare Organizations ◽  
The Public ◽  
Manual Search ◽  
Ict Industry ◽  
New Research

Background: There is a growing interest concerning the potential of ICT solutions that are customized to consumers. This emerging discipline referred to as consumer health informatics (CHI) plays a major role in providing information to patients and the public, and facilitates the promotion of self-management.The concept of CHI has emerged out of the desire of most patients to shoulder responsibilities regarding their health and a growing desire of health practitioners to fully appreciate the potential of the patient.Aim: To describe the role of ICT in improving the patient-provider partnership in consumer health informatics.Methods: Systematic reviewing of literature, identification of reference sources and formulation of search strategies and manual search regarding the significance of developed CHI applications in healthcare delivery.Results: New consumer health IT applications have been developed to be used on a variety of different platforms, including the Web, messaging systems, PDAs, and cell phones. These applications assists patients with self-management through reminders and prompts, delivery of real-time data on a patient’s health condition to patients and providers, web-based communication and personal electronic health information.Conclusion: New tools are being developed for the purposes of providing information to patients and the public which has enhanced decision making in health matters and an avenue for clinicians and consumers to exchange health information for personal and public use. This calls for corroboration among healthcare organizations, governments and the ICT industry to develop new research and IT innovations which are tailored to the health needs of the consumer.

scholarly journals Framework to Interpret Deep Learning-Based Health Management System with Human Interactions

2019 ◽  
Vol 11 (1) ◽  
Author(s):  
Michael H. Azarian ◽  
Namkyoung Lee ◽  
Michael G. Pecht
Keyword(s):  
Deep Learning ◽  
Management System ◽  
Health Management ◽  
System Development ◽  
Black Box ◽  
Remaining Useful Life ◽  
Management Systems ◽  
Know How ◽  
Human Interactions ◽  
Useful Life

Deep learning has shown good performance in detecting a product’s faults and estimating the remaining useful life of a product. However, it is hard to interpret deep learning-based health management systems because deep learning is often regarded as a black box. In order to make a maintenance decision based on the result of the management system, humans need to know how it gave the outcome. This study aims to develop a framework that utilizes human interactions during system development to understand the internal process of deep learning. The study will demonstrate the framework on bearing datasets.

INTEGRATED MEDICAL DATA MANAGEMENT SYSTEMS REVIEW

2019 ◽  
Author(s):  
Ihor Pysmennyi
Keyword(s):  
Health Informatics ◽  
Quality Care ◽  
Exchange Process ◽  
Knowledge Exchange ◽  
Clinical Information ◽  
Mobile Network ◽  
Developed Countries ◽  
Management Systems ◽  
Learning Techniques ◽  
Drastic Increase

In recent years we’ve seen breakthrough research success in medicine and computer science enabled by novel technology advancements, data analyses capabilities and learning techniques. Despite this, quality care doesn’t have full cove­ rage even in developed countries and access to care is recognised as one of the biggest challenges to the global healthcare system. Bound with population growth in remote areas in developing regions, which lack skilled professionals and medical resources, as well as aging in developed countries this caused a strong need for increasing healthcare effectiveness. Enabled by development of cloud technologies, quick expansion of mobile network coverage and internet access Clinical Information Management Systems integrated with decision support systems, Telemedicine (inclu­ ding distributed Virtual Healthcare Teams and medical imaging), Mobile Healthcare, medical Internet of Things (mIoT), Consumer Health Informatics with personal intelligent health assistants, Health Information Exchanges and deep learning techniques for diagnostics and knowledge extraction are among the state-of-the-art solutions which are more or less successfully used for coping with the problem mentioned above. This paper reviews current situation with implementing these novel informational systems, analyses their advantages, drawbacks, implementation impediments and outcome effectiveness suggesting platform for empowering their integration and maximizing output of each module. Such solution will have a synergy effect and result in a drastic increase of medical resource utilization effectiveness, service quality and providing bigger and fuller coverage with less spending at the same time empowering knowledge exchange process and laying foundation for future development and innovations in the whole healthcare domain.

scholarly journals Discharge Plan to Promote Patient Safety and Shared Decision Making by a Multidisciplinary Team of Healthcare Professionals in a Respiratory Unit

2021 ◽  
Vol 11 (3) ◽  
pp. 590-599
Author(s):  
Daniel A. Nnate ◽  
David Barber ◽  
Ukachukwu O. Abaraogu
Keyword(s):  
Healthcare Professionals ◽  
Health Condition ◽  
Social Needs ◽  
Chronic Obstructive ◽  
Best Interest ◽  
Obstructive Pulmonary Disease ◽  
Discharge Plan ◽  
Health And Social Care ◽  
Multidisciplinary Working ◽  
Prolonged Hospital

Patients with chronic obstructive pulmonary disease (COPD) often require frequent hospitalization due to worsening symptoms. Preventing prolonged hospital stays and readmission becomes a challenge for healthcare professionals treating patients with COPD. Although the integration of health and social care supports greater collaboration and enhanced patient care, organizational structure and poor leadership may hinder the implementation of patient-oriented goals. This paper presents a case of a 64-year-old chronic smoker with severe COPD who was to be discharged on long-term oxygen therapy (LTOT). It also highlights the healthcare decisions made to ensure the patient’s safety at home and further provides a long-lasting solution to the existing medical and social needs. The goal was accomplished through a discharge plan that reflects multidisciplinary working, efficient leadership, and change management using Havelock’s theory. While COPD is characterized by frequent exacerbation and hospital readmission, it was emphasized that most failed discharges could be attributed to bureaucratic organizational workflow which might not be in the patient’s best interest. It was further demonstrated that healthcare professionals are likely to miss the window of opportunity to apply innovative and long-lasting solutions to the patient’s health condition in an attempt to remedy the immediate symptoms of COPD.

scholarly journals Methods for conducting international Delphi surveys to optimise global participation in core outcome set development: a case study in gastric cancer informed by a comprehensive literature review

Trials ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Bilal Alkhaffaf ◽  
Jane M. Blazeby ◽  
Aleksandra Metryka ◽  
Anne-Marie Glenny ◽  
Ademola Adeyeye ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Literature Review ◽  
Healthcare Professionals ◽  
Vascular Malformations ◽  
Methodological Approach ◽  
Core Outcome Set ◽  
Core Outcome ◽  
Comprehensive Literature Review ◽  
International Participation

Abstract Background Core outcome sets (COS) should be relevant to key stakeholders and widely applicable and usable. Ideally, they are developed for international use to allow optimal data synthesis from trials. Electronic Delphi surveys are commonly used to facilitate global participation; however, this has limitations. It is common for these surveys to be conducted in a single language potentially excluding those not fluent in that tongue. The aim of this study is to summarise current approaches for optimising international participation in Delphi studies and make recommendations for future practice. Methods A comprehensive literature review of current approaches to translating Delphi surveys for COS development was undertaken. A standardised methodology adapted from international guidance derived from 12 major sets of translation guidelines in the field of outcome reporting was developed. As a case study, this was applied to a COS project for surgical trials in gastric cancer to translate a Delphi survey into 7 target languages from regions active in gastric cancer research. Results Three hundred thirty-two abstracts were screened and four studies addressing COS development in rheumatoid and osteoarthritis, vascular malformations and polypharmacy were eligible for inclusion. There was wide variation in methodological approaches to translation, including the number of forward translations, the inclusion of back translation, the employment of cognitive debriefing and how discrepancies and disagreements were handled. Important considerations were identified during the development of the gastric cancer survey including establishing translation groups, timelines, understanding financial implications, strategies to maximise recruitment and regulatory approvals. The methodological approach to translating the Delphi surveys was easily reproducible by local collaborators and resulted in an additional 637 participants to the 315 recruited to complete the source language survey. Ninety-nine per cent of patients and 97% of healthcare professionals from non-English-speaking regions used translated surveys. Conclusion Consideration of the issues described will improve planning by other COS developers and can be used to widen international participation from both patients and healthcare professionals.

Acoustic emission structural health management systems (AE-SHMS)

2000 ◽  
Author(s):  
Richard D. Finlayson ◽  
Mark A. Friesel ◽  
Mark F. Carlos ◽  
Ronnie K. Miller ◽  
Valery Godinez
Keyword(s):  
Acoustic Emission ◽  
Health Management ◽  
Management Systems ◽  
Structural Health ◽  
Structural Health Management

scholarly journals Health Condition Estimation of Bearings with Multiple Faults by a Composite Learning-Based Approach

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4424
Author(s):  
Udeme Inyang ◽  
Ivan Petrunin ◽  
Ian Jennions
Keyword(s):  
Fault Diagnosis ◽  
Health Management ◽  
Network Models ◽  
Health Condition ◽  
Limited Attention ◽  
Neural Network Models ◽  
Multiple Fault ◽  
Multiple Faults ◽  
Multiple Fault Diagnosis ◽  
Non Gaussian

Bearings are critical components found in most rotating machinery; their health condition is of immense importance to many industries. The varied conditions and environments in which bearings operate make them prone to single and multiple faults. Widespread interest in the improvements of single fault diagnosis meant limited attention was spent on multiple fault diagnosis. However, multiple fault diagnosis poses extra challenges due to the submergence of the weak fault by the strong fault, presence of non-Gaussian noise, coupling of the frequency components, etc. A number of existing convolutional neural network models operate on a distinct feature that is not enough to assure reliable results in the presence of these challenges. In this paper, extended feature sets in three homogenous deep learning models are used for multiple fault diagnosis. This ensures a measure of diversity is introduced to the health management dataset to obtain complementary solutions from the models. The outputs of the models are fused through blending ensemble learning. Experiments using vibration datasets based on bearing multiple faults show an accuracy of 98.54%, with an improvement of 2.74% in the overall effectiveness over the single models. Compared with other technologies, the results show that this approach provides an improved generalized diagnostic capability.

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