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Modeling Medical Services with Mobile Health Applications

The rapid development of mobile health technology (m-Health) provides unprecedented opportunities for improving health services. As the bridge between doctors and patients, mobile health applications enable patients to communicate with doctors through their smartphones, which is becoming more and mo...

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Detalles Bibliográficos
Autores principales: Wang, Zhenfei, Zhang, Liying, Ma, Ling, Liu, Bing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5914102/
https://www.ncbi.nlm.nih.gov/pubmed/29849991
http://dx.doi.org/10.1155/2018/1385034
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author Wang, Zhenfei
Zhang, Liying
Ma, Ling
Liu, Bing
author_facet Wang, Zhenfei
Zhang, Liying
Ma, Ling
Liu, Bing
author_sort Wang, Zhenfei
collection PubMed
description The rapid development of mobile health technology (m-Health) provides unprecedented opportunities for improving health services. As the bridge between doctors and patients, mobile health applications enable patients to communicate with doctors through their smartphones, which is becoming more and more popular among people. To evaluate the influence of m-Health applications on the medical service market, we propose a medical service equilibrium model. The model can balance the supply of doctors and demand of patients and reflect possible options for both doctors and patients with or without m-Health applications in the medical service market. In the meantime, we analyze the behavior of patients and the activities of doctors to minimize patients' full costs of healthcare and doctors' futility. Then, we provide a resolution algorithm through mathematical reasoning. Lastly, based on artificially generated dataset, experiments are conducted to evaluate the medical services of m-Health applications.
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spelling pubmed-59141022018-05-30 Modeling Medical Services with Mobile Health Applications Wang, Zhenfei Zhang, Liying Ma, Ling Liu, Bing J Healthc Eng Research Article The rapid development of mobile health technology (m-Health) provides unprecedented opportunities for improving health services. As the bridge between doctors and patients, mobile health applications enable patients to communicate with doctors through their smartphones, which is becoming more and more popular among people. To evaluate the influence of m-Health applications on the medical service market, we propose a medical service equilibrium model. The model can balance the supply of doctors and demand of patients and reflect possible options for both doctors and patients with or without m-Health applications in the medical service market. In the meantime, we analyze the behavior of patients and the activities of doctors to minimize patients' full costs of healthcare and doctors' futility. Then, we provide a resolution algorithm through mathematical reasoning. Lastly, based on artificially generated dataset, experiments are conducted to evaluate the medical services of m-Health applications. Hindawi 2018-04-10 /pmc/articles/PMC5914102/ /pubmed/29849991 http://dx.doi.org/10.1155/2018/1385034 Text en Copyright © 2018 Zhenfei Wang et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Wang, Zhenfei
Zhang, Liying
Ma, Ling
Liu, Bing
Modeling Medical Services with Mobile Health Applications
title Modeling Medical Services with Mobile Health Applications
title_full Modeling Medical Services with Mobile Health Applications
title_fullStr Modeling Medical Services with Mobile Health Applications
title_full_unstemmed Modeling Medical Services with Mobile Health Applications
title_short Modeling Medical Services with Mobile Health Applications
title_sort modeling medical services with mobile health applications
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5914102/
https://www.ncbi.nlm.nih.gov/pubmed/29849991
http://dx.doi.org/10.1155/2018/1385034
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