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Online medical consultation in China: Evidence from obesity doctors
OBJECTIVE: Online medical consultation (OMC) is increasingly used in China, but there have been few in-depth studies of consultation arrangements and fee structures of online doctors in China. This research assessed the consultation arrangements and fee structure of OMC in China by undertaking a cas...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10278408/ https://www.ncbi.nlm.nih.gov/pubmed/37342094 http://dx.doi.org/10.1177/20552076231182789 |
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author | Yu, Donglei Hu, Yaolin Wang, Jian Nicholas, Stephen Maitland, Elizabeth |
author_facet | Yu, Donglei Hu, Yaolin Wang, Jian Nicholas, Stephen Maitland, Elizabeth |
author_sort | Yu, Donglei |
collection | PubMed |
description | OBJECTIVE: Online medical consultation (OMC) is increasingly used in China, but there have been few in-depth studies of consultation arrangements and fee structures of online doctors in China. This research assessed the consultation arrangements and fee structure of OMC in China by undertaking a case study of obesity doctors from four representative OMC platforms. METHODS: Detailed information, including fees, waiting time and doctor information, was collected from four obesity OMC platforms and analyzed using descriptive statistical analysis. RESULTS: The obesity OMC platforms in China shared similarities in the use of big data and artificial intelligence (AI) but differed across service access, specific consultation arrangements and fees. Big data search and AI response technologies were used by most platforms to match users with doctors and reduce doctors’ pressure. The descriptive statistical analysis showed that the higher the rank of the online doctor, the higher the online fee and the longer the wait time. Through a comparison with offline hospitals, we found online doctors’ fees exceeded offline hospital doctors’ fees by up to 90%. CONCLUSIONS: OMC platforms can gain competitive advantages over offline medical institutions through the following measures: make fuller use of big data and AI technologies to provide users with longer duration, lower cost and more efficient consultation services; provide better user experience than offline medical institutions; use big data and fee advantages to screen doctors to match users’ consultation needs instead of screening by the rank of doctors only; and cooperate with commercial insurance providers to provide innovative health care packages. |
format | Online Article Text |
id | pubmed-10278408 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-102784082023-06-20 Online medical consultation in China: Evidence from obesity doctors Yu, Donglei Hu, Yaolin Wang, Jian Nicholas, Stephen Maitland, Elizabeth Digit Health Original Research OBJECTIVE: Online medical consultation (OMC) is increasingly used in China, but there have been few in-depth studies of consultation arrangements and fee structures of online doctors in China. This research assessed the consultation arrangements and fee structure of OMC in China by undertaking a case study of obesity doctors from four representative OMC platforms. METHODS: Detailed information, including fees, waiting time and doctor information, was collected from four obesity OMC platforms and analyzed using descriptive statistical analysis. RESULTS: The obesity OMC platforms in China shared similarities in the use of big data and artificial intelligence (AI) but differed across service access, specific consultation arrangements and fees. Big data search and AI response technologies were used by most platforms to match users with doctors and reduce doctors’ pressure. The descriptive statistical analysis showed that the higher the rank of the online doctor, the higher the online fee and the longer the wait time. Through a comparison with offline hospitals, we found online doctors’ fees exceeded offline hospital doctors’ fees by up to 90%. CONCLUSIONS: OMC platforms can gain competitive advantages over offline medical institutions through the following measures: make fuller use of big data and AI technologies to provide users with longer duration, lower cost and more efficient consultation services; provide better user experience than offline medical institutions; use big data and fee advantages to screen doctors to match users’ consultation needs instead of screening by the rank of doctors only; and cooperate with commercial insurance providers to provide innovative health care packages. SAGE Publications 2023-06-15 /pmc/articles/PMC10278408/ /pubmed/37342094 http://dx.doi.org/10.1177/20552076231182789 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by-nc-nd/4.0/This article is distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 License (https://creativecommons.org/licenses/by-nc-nd/4.0/) which permits non-commercial use, reproduction and distribution of the work as published without adaptation or alteration, without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
spellingShingle | Original Research Yu, Donglei Hu, Yaolin Wang, Jian Nicholas, Stephen Maitland, Elizabeth Online medical consultation in China: Evidence from obesity doctors |
title | Online medical consultation in China: Evidence from obesity doctors |
title_full | Online medical consultation in China: Evidence from obesity doctors |
title_fullStr | Online medical consultation in China: Evidence from obesity doctors |
title_full_unstemmed | Online medical consultation in China: Evidence from obesity doctors |
title_short | Online medical consultation in China: Evidence from obesity doctors |
title_sort | online medical consultation in china: evidence from obesity doctors |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10278408/ https://www.ncbi.nlm.nih.gov/pubmed/37342094 http://dx.doi.org/10.1177/20552076231182789 |
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