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Global Health Policy, Health Services and System, and E-health
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Global Health Policy, Health Services and System, and E-health

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Health, Well-Being and Sustainability".

Deadline for manuscript submissions: closed (31 October 2020) | Viewed by 7221

Special Issue Editors

Dr. Son Nghiem

E-Mail Website
Guest Editor
1. Centre for Applied Health Economics, Griffith University, Nathan, QLD 4111, Australia
2. Menzies Health Institutte Queensland, Griffith University, Gold Coast, QLD 4215, Australia
Interests: health economics; applied econometrics; data linkage; big data analytics
Special Issues, Collections and Topics in MDPI journals
Dr. Bach Tran

E-Mail Website
Guest Editor
Department of Health Economics, Hanoi Medical University, Hanoi, Vietnam
Interests: global health policy; health services and system; e-health

Special Issue Information

Dear Colleagues,

With the increasing availability of big data and machine learning techniques, artificial intelligence has reached all aspects of our lives. Healthcare is no exception. A recent literature review1 revealed that the number of studies on applications of AI in healthcare has increased exponentially in the past ten years. The most common areas of AI applications in healthcare include robot-assisted surgery, disease diagnosis and prediction, and personalised medicine. Not much many AI studies have investigated issues regarding clinical effectiveness, patient safety, and cost-effectiveness2. The ability to identify causal relationships rather than statistical correlations is also a challenge that has not been overcome by current AI health studies.

This Special Issue invites AI studies on healthcare, especially thorough examinations of clinical effectiveness, patient safety and cost-effectiveness of AI applications in healthcare. Answers to these three areas will lead to improving the confidence of policymakers and the public in AI-based health services.

Studies to be presented in this Special Issue will provide more diverse evidence of the efficacy of AI applications in healthcare. This Special Issue also aims to fill the knowledge gap in identifying the clinical- and cost-effectiveness of AI. Risk-mitigation strategies to address the potential moral or technical failure of potential AI-based health services will also be discussed in this Special Issue.

References:

  1. Bach X Tran, Son Nghiem, Oz Sahin, Giang H Ha, Giang T Vu, Hai Q Pham, Hoa Thi Do, Carl A Latkin, Wilson Tam, Cyrus SH Ho, Roger CM Ho. Modeling Research Topics of Artificial Intelligence Applications in Medicine (GAPRESEARCH): a Latent Dirichlet Allocation application, Journal of Medical Internet Research, 2019, DOI:10.2196/15511
  2. Maddox TM, Rumsfeld JS, Payne PRO. Questions for Artificial Intelligence in Health Care. JAMA. 2019;321(1):31–32. DOI:10.1001/jama.2018.18932

Dr. Son Nghiem
Dr. Bach Tran
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • artificial intelligence
  • healthcare
  • big data
  • machine learning
  • efficacy

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Published Papers (2 papers)

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Research

14 pages, 1300 KiB  
Article
The Impact of New Technologies on Individuals’ Health Perceptions in the European Union
by Gabriel Brătucu, Andra Ioana Maria Tudor, Lavinia Dovleac, Silvia Sumedrea, Ioana Bianca Chițu and Adrian Trifan
Sustainability 2020, 12(24), 10349; https://doi.org/10.3390/su122410349 - 11 Dec 2020
Cited by 9 | Viewed by 2838
Abstract
The healthcare systems of European countries currently face challenges regarding the sustainability of healthcare provision. The growing sophistication of new technologies is transforming the accessibility and management of health services and information, while also challenging society’s ability to offer fair access to health [...] Read more.
The healthcare systems of European countries currently face challenges regarding the sustainability of healthcare provision. The growing sophistication of new technologies is transforming the accessibility and management of health services and information, while also challenging society’s ability to offer fair access to health services for all people. The aim of this paper is to identify and analyze some of the determinants of the self-perceived health status across the EU28 area and to determine how the digitalization of health is impacting the self-rated health of the European populations, given the fact that a healthier population is one of the 17 goals of sustainable development on the 2030 Agenda. The research method used is panel-data regression using secondary data from international databases. The results indicate that there is a direct relationship between the way people are assessing personal health, the ability to use the Internet for seeking health-related information, and the use of various apps to purchase health-related items online. Our findings are useful for academics, industry specialists, and public authorities in designing sustainable health products and policies by focusing on the development of suitable mHealth programs for generating more patient-centered services where the idea of self-care is encouraged. Full article
(This article belongs to the Special Issue Global Health Policy, Health Services and System, and E-health)
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18 pages, 4597 KiB  
Article
Sustainable Smartphone-Based Healthcare Systems: A Systems Engineering Approach to Assess the Efficacy of Respiratory Monitoring Apps
by Misagh Faezipour and Miad Faezipour
Sustainability 2020, 12(12), 5061; https://doi.org/10.3390/su12125061 - 22 Jun 2020
Cited by 18 | Viewed by 3767
Abstract
Recent technological developments along with advances in smart healthcare have been rapidly changing the healthcare industry and improving outcomes for patients. To ensure reliable smartphone-based healthcare interfaces with high levels of efficacy, a system dynamics model with sustainability indicators is proposed. The focus [...] Read more.
Recent technological developments along with advances in smart healthcare have been rapidly changing the healthcare industry and improving outcomes for patients. To ensure reliable smartphone-based healthcare interfaces with high levels of efficacy, a system dynamics model with sustainability indicators is proposed. The focus of this paper is smartphone-based breathing monitoring systems that could possibly use breathing sounds as the data acquisition input. This can especially be useful for the self-testing procedure of the ongoing global COVID-19 crisis in which the lungs are attacked and breathing is affected. The method of investigation is based on a systems engineering approach using system dynamics modeling. In this paper, first, a causal model for a smartphone-based respiratory function monitoring is introduced. Then, a systems thinking approach is applied to propose a system dynamics model of the smartphone-based respiratory function monitoring system. The system dynamics model investigates the level of efficacy and sustainability of the system by studying the behavior of various factors of the system including patient wellbeing and care, cost, convenience, user friendliness, in addition to other embedded software and hardware breathing monitoring system design and performance metrics (e.g., accuracy, real-time response, etc.). The sustainability level is also studied through introducing various indicators that directly relate to the three pillars of sustainability. Various scenarios have been applied and tested on the proposed model. The results depict the dynamics of the model for the efficacy and sustainability of smartphone-based breathing monitoring systems. The proposed ideas provide a clear insight to envision sustainable and effective smartphone-based healthcare monitoring systems. Full article
(This article belongs to the Special Issue Global Health Policy, Health Services and System, and E-health)
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