Simulation of eHealth Scenarios with Role-play Supported by an Interactive Smartphone Application

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Using Mobile Devices as a Supportive Tool to Engage and Interest Young Students in e-Health

Master's thesis Multimedia and Educational Technology MM500 - University of Agder 2019This thesis explores if mobile devices could be used as a supportive elementto engage and interest young students in e-health by developing a prototypeto handle simulations of e-health scenarios in a serious game setting. Theprototype was to be used as a supportive tool for the research projectHighSchool Students as Co-researchers in eHealth. An iterative design processwas deployed to develop the prototype, going through multiple steps periteration, focusing on design and development, testing, and evaluation. Theresults from all of the testing were examined, and compared with the researchquestions regarding whether or not mobile devices are useful as supportivetools to engage and interest students. It is hoped that the study encouragesfuture use of mobile devices in education and learning

Innovative Continuing Education for Maternal and Newborn Health Workers in Low-and Middle-Income Countries: A Feasibility Study

Purpose: The purpose of this dissertation is to explore strategies to improve maternal and newborn health workers’ clinical competence and performance, particularly among nurses and midwives, in low-and middle-income countries (LMICs), through innovative continuing educational approaches using priority evidence-based content. A feasibility trial with one such learning approach was implemented with maternal and newborn health providers in a hard-to-reach setting of the Democratic Republic of the Congo (DRC) in order to test one possible response to the continued high maternal and neonatal mortality in that country. The study contributes to the knowledge base on provision of critical continuing education to maternal and newborn health workers in hard-to-reach settings and to the global effort underway to address excess maternal and neonatal mortality in LMICs. Problems/Aims: Health worker clinical performance is often inadequate in developing countries. Substandard delivery and emergency obstetric care (EmOC) in health facilities has been widely documented as a major cause of maternal mortality in health facilities globally. Similarly, studies show that quality gaps are leading to higher rates of neonatal mortality in facility births. A basic strategy for improving health worker practice and strengthening clinical performance is through the promotion of continuing education (CE). However, there are many challenges to organizing CE opportunities for healthcare workers in hard-to-reach LMIC settings. The aims of this research were 1) to explore potential approaches to continuing education for maternal and newborn health workers in LMICs by examining the approaches that are currently available worldwide and 2) evaluating one concrete approach using a mobile phone mLearning app. We examined the feasibility and acceptability of the use of mLearning with facility-based maternal and neonatal health workers in one hard-to-reach setting of the DRC. We also evaluated the use of mLearning for a preliminary impact on facility-based health worker Basic Emergency Obstetric & Neonatal Care (BEmONC) self-confidence and clinical knowledge, and on select maternal and newborn outcome trends (as a proxy for evaluating improved health worker clinical behavior/performance). We also sought to refine intervention delivery in the DRC and strengthen study procedures required to conduct a robust future largescale trial. Design including theoretical basis: This study design is comprised of two literature reviews on the topic and a feasibility study using a convergent parallel mixed methods and community-engaged pilot cluster-randomized trial design. Our theoretical basis is comprised of complementary theoretical approaches: (1) Benjamin Bloom’s Theory of Mastery-Learning and Taxonomy of Educational Objectives; (2) Kirkpatrick’s Model of training evaluation; and (3) The Theoretical Domains Framework (TDF). Findings: Our literature reviews on CE approaches for facility-based maternal and newborn health workers in low-income countries revealed that conventional and simulation training using varied teaching methodologies can improve provider knowledge, skills, clinical practice, and patient outcomes. However, results are variable and there is limited evidence overall, with minimal use of robust study designs and validated measurement instruments, that document the association between CE and long-term effectiveness of the interventions with improved patient outcomes. Other creative interventions are being piloted in eHealth / eLearning including mobile phone learning applications (mLearning) and these have shown encouraging results in overcoming some key challenges in providing health workers with evidence-based learning in more remote settings. mLearning was found to be feasible and acceptable to health workers and key stakeholders in the DRC. A trial of one recent mLearning evidence-based app, the Safe Delivery App, increased health worker knowledge and self-confidence on the management of obstetric and newborn emergencies 3 months after introduction and indicated preliminary encouraging impacts on health workers’ practices in BEmONC. Conclusion: eLearning and mLearning show promise for improving maternal and newborn health worker practice and reducing mortality in low-and middle-income countries, particularly for health workers in more remote settings, where the challenge of maternal and neonatal mortality and quality assurance of emergency obstetric and neonatal care is greatest. Factors such as health worker motivation and self-efficacy, as well as the physical and policy environment, emphasized by Bloom and the TDF, are essential in improving practice and should be considered, along with cost, in designing scalable and comprehensive maternal and neonatal mortality programs for improved outcomes

A Priority-based Fair Queuing (PFQ) Model for Wireless Healthcare System

Healthcare is a very active research area, primarily due to the increase in the elderly population that leads to increasing number of emergency situations that require urgent actions. In recent years some of wireless networked medical devices were equipped with different sensors to measure and report on vital signs of patient remotely. The most important sensors are Heart Beat Rate (ECG), Pressure and Glucose sensors. However, the strict requirements and real-time nature of medical applications dictate the extreme importance and need for appropriate Quality of Service (QoS), fast and accurate delivery of a patient’s measurements in reliable e-Health ecosystem. As the elderly age and older adult population is increasing (65 years and above) due to the advancement in medicine and medical care in the last two decades; high QoS and reliable e-health ecosystem has become a major challenge in Healthcare especially for patients who require continuous monitoring and attention. Nevertheless, predictions have indicated that elderly population will be approximately 2 billion in developing countries by 2050 where availability of medical staff shall be unable to cope with this growth and emergency cases that need immediate intervention. On the other side, limitations in communication networks capacity, congestions and the humongous increase of devices, applications and IOT using the available communication networks add extra layer of challenges on E-health ecosystem such as time constraints, quality of measurements and signals reaching healthcare centres. Hence this research has tackled the delay and jitter parameters in E-health M2M wireless communication and succeeded in reducing them in comparison to current available models. The novelty of this research has succeeded in developing a new Priority Queuing model ‘’Priority Based-Fair Queuing’’ (PFQ) where a new priority level and concept of ‘’Patient’s Health Record’’ (PHR) has been developed and integrated with the Priority Parameters (PP) values of each sensor to add a second level of priority. The results and data analysis performed on the PFQ model under different scenarios simulating real M2M E-health environment have revealed that the PFQ has outperformed the results obtained from simulating the widely used current models such as First in First Out (FIFO) and Weight Fair Queuing (WFQ). PFQ model has improved transmission of ECG sensor data by decreasing delay and jitter in emergency cases by 83.32% and 75.88% respectively in comparison to FIFO and 46.65% and 60.13% with respect to WFQ model. Similarly, in pressure sensor the improvements were 82.41% and 71.5% and 68.43% and 73.36% in comparison to FIFO and WFQ respectively. Data transmission were also improved in the Glucose sensor by 80.85% and 64.7% and 92.1% and 83.17% in comparison to FIFO and WFQ respectively. However, non-emergency cases data transmission using PFQ model was negatively impacted and scored higher rates than FIFO and WFQ since PFQ tends to give higher priority to emergency cases. Thus, a derivative from the PFQ model has been developed to create a new version namely “Priority Based-Fair Queuing-Tolerated Delay” (PFQ-TD) to balance the data transmission between emergency and non-emergency cases where tolerated delay in emergency cases has been considered. PFQ-TD has succeeded in balancing fairly this issue and reducing the total average delay and jitter of emergency and non-emergency cases in all sensors and keep them within the acceptable allowable standards. PFQ-TD has improved the overall average delay and jitter in emergency and non-emergency cases among all sensors by 41% and 84% respectively in comparison to PFQ model

Usability analysis of contending electronic health record systems

In this paper, we report measured usability of two leading EHR systems during procurement. A total of 18 users participated in paired-usability testing of three scenarios: ordering and managing medications by an outpatient physician, medicine administration by an inpatient nurse and scheduling of appointments by nursing staff. Data for audio, screen capture, satisfaction rating, task success and errors made was collected during testing. We found a clear difference between the systems for percentage of successfully completed tasks, two different satisfaction measures and perceived learnability when looking at the results over all scenarios. We conclude that usability should be evaluated during procurement and the difference in usability between systems could be revealed even with fewer measures than were used in our study. © 2019 American Psychological Association Inc. All rights reserved.Peer reviewe