e-Health and Co-production: Critical Drivers for Chronic Diseases Management

Palozzi, Gabriele; Binci, Daniele; Appolloni, Andrea

doi:10.1007/978-3-319-46412-1_15

Cited by 10 publications

(6 citation statements)

References 34 publications

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“…Although, reflecting in long-term, we can also conclude that our current situation is a call for the governance to redesign the worldwide health systems and the way healthcare management is developed and implemented. New healthcare business models should be studied, aiming to certify the world economy, sustainability, and the quality life for the patients [33].…”

Section: Discussionmentioning

confidence: 99%

“…This experience should be seen as a lesson, or even a case study to examine carefully. The majority of patients are already in their houses, which plays a pro-active part in its own treatment, showing that coproduction in the health field is possible and already used with other illnesses such as heart failure [33]. Practices of coproduction suggest a safer connection these days, and it is also economic for the health systems by improving the organization management and facilitating the workflow.…”

Section: Discussionmentioning

confidence: 99%

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The Combat against COVID-19 in Portugal: How State Measures and Data Availability Reinforce Some Organizational Values and Contribute to the Sustainability of the National Health System

et al. 2020

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Countries are facing a pandemic crisis in the context of a new disease from the coronavirus family, referred to as COVID-19. This article aims to present the main facts related to the fight against the pandemic from the perspective of the Portuguese governance, aiming to contribute to the knowledge of crisis management by political leaders as well as the performance of public entities. The present research was conducted through a quantitative approach, using data publicly provided by the Portuguese Directorate General of Health. An explanatory and descriptive study is presented about the current panorama, and yet to be shared good practices of crisis management and the relevance of organizational values in crisis management and crisis coordination are also discussed. Based on the lessons from Portugal, the authors suggest the relevance of organizational values and stakeholders’ coordination as key factors in crisis situations, such as the current one.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

The Combat against COVID-19 in Portugal: How State Measures and Data Availability Reinforce Some Organizational Values and Contribute to the Sustainability of the National Health System

et al. 2020

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“…By 2030, 13% of the world population will fall in the aging category and the burden on the health care sector will be enormous [62]. Serious diseases that include brain tumors, chest cancer, lung cancer, diabetes, hypertension, and heart failure, directly affect medical health care expenses all over the world [63][64][65]. The manual treatment of serious disease is a challenging task for the global health care systems in terms of quality of care delivery [65,66].…”

Section: Healthcare Scalability Importance and Challengesmentioning

confidence: 99%

Brain Tumor Analysis Empowered with Deep Learning: A Review, Taxonomy, and Future Challenges

et al. 2020

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Deep Learning (DL) algorithms enabled computational models consist of multiple processing layers that represent data with multiple levels of abstraction. In recent years, usage of deep learning is rapidly proliferating in almost every domain, especially in medical image processing, medical image analysis, and bioinformatics. Consequently, deep learning has dramatically changed and improved the means of recognition, prediction, and diagnosis effectively in numerous areas of healthcare such as pathology, brain tumor, lung cancer, abdomen, cardiac, and retina. Considering the wide range of applications of deep learning, the objective of this article is to review major deep learning concepts pertinent to brain tumor analysis (e.g., segmentation, classification, prediction, evaluation.). A review conducted by summarizing a large number of scientific contributions to the field (i.e., deep learning in brain tumor analysis) is presented in this study. A coherent taxonomy of research landscape from the literature has also been mapped, and the major aspects of this emerging field have been discussed and analyzed. A critical discussion section to show the limitations of deep learning techniques has been included at the end to elaborate open research challenges and directions for future work in this emergent area.

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“…By 2030, 13% of the world total population is expected to be assigned to around one billion people aged 65 years or older [181]. Numerous problems in chronic diseases are related to the momentary rise in ageing population and directly influence medical healthcare expenses [182][183][184]. The increase of chronic disease cases along with the increase of ageing population (e.g., heart failure, hypertension and diabetes) makes the healthcare management a serious issue for health systems worldwide [182].…”

Section: Patient Prioritisationmentioning

confidence: 99%

“…Numerous problems in chronic diseases are related to the momentary rise in ageing population and directly influence medical healthcare expenses [182][183][184]. The increase of chronic disease cases along with the increase of ageing population (e.g., heart failure, hypertension and diabetes) makes the healthcare management a serious issue for health systems worldwide [182]. According to the Medicare and Medicaid Services Centre [180], healthcare expenditure in the USA in 1970 was around $75 billion, and it increased more to than $4.3 trillion in 2018, as shown in Fig.…”

Section: Patient Prioritisationmentioning

confidence: 99%

Real-Time Remote-Health Monitoring Systems: a Review on Patients Prioritisation for Multiple-Chronic Diseases, Taxonomy Analysis, Concerns and Solution Procedure

et al. 2019

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Remotely monitoring a patient's condition is a serious issue and must be addressed. Remote health monitoring systems (RHMS) in telemedicine refers to resources, strategies, methods and installations that enable doctors or other medical professionals to work remotely to consult, diagnose and treat patients. The goal of RHMS is to provide timely medical services at remote areas through telecommunication technologies. Through major advancements in technology, particularly in wireless networking, cloud computing and data storage, RHMS is becoming a feasible aspect of modern medicine. RHMS for the prioritisation of patients with multiple chronic diseases (MCDs) plays an important role in sustainably providing high-quality healthcare services. Further investigations are required to highlight the limitations of the prioritisation of patients with MCDs over a telemedicine environment. This study introduces a comprehensive and inclusive review on the prioritisation of patients with MCDs in telemedicine applications. Furthermore, it presents the challenges and open issues regarding patient prioritisation in telemedicine. The findings of this study are as follows: (1) The limitations and problems of existing patients' prioritisation with MCDs are presented and emphasised. (2) Based on the analysis of the academic literature, an accurate solution for remote prioritisation in a large scale of patients with MCDs was not presented. (3) There is an essential need to produce a new multiple-criteria decisionmaking theory to address the current problems in the prioritisation of patients with MCDs.

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e-Health and Co-production: Critical Drivers for Chronic Diseases Management

Cited by 10 publications

References 34 publications

The Combat against COVID-19 in Portugal: How State Measures and Data Availability Reinforce Some Organizational Values and Contribute to the Sustainability of the National Health System

The Combat against COVID-19 in Portugal: How State Measures and Data Availability Reinforce Some Organizational Values and Contribute to the Sustainability of the National Health System

Brain Tumor Analysis Empowered with Deep Learning: A Review, Taxonomy, and Future Challenges

Real-Time Remote-Health Monitoring Systems: a Review on Patients Prioritisation for Multiple-Chronic Diseases, Taxonomy Analysis, Concerns and Solution Procedure

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