Frequent use of online medical records: analysis of influence factors based on structural equation modeling
The advent of electronic storage of medical records and the internet has led to an increase in the use of online medical records, thereby enhancing doctor–patient communication and facilitating medical treatment. Based on demographic and personal behavioral characteristics from the National Cancer I...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2025-08-01
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| Series: | Frontiers in Public Health |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fpubh.2025.1609503/full |
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| author | Wei Wang Lei Qin Lei Qin Yang Chen Yinzhi Wang Linglong Ye Ruojia Wang Yingqiu Zhu |
| author_facet | Wei Wang Lei Qin Lei Qin Yang Chen Yinzhi Wang Linglong Ye Ruojia Wang Yingqiu Zhu |
| author_sort | Wei Wang |
| collection | DOAJ |
| description | The advent of electronic storage of medical records and the internet has led to an increase in the use of online medical records, thereby enhancing doctor–patient communication and facilitating medical treatment. Based on demographic and personal behavioral characteristics from the National Cancer Institute’s 2019–2020 National Trends in Health Information Survey data, this study explored the characteristics and factors influencing the frequent use of online medical records and compared them with those that do not. By combining traditional statistical tests and two machine learning algorithms, eight variables were identified as key variables in the frequent use of online medical records. These variables were then divided into three influencing factors (latent variables). The structural equation model was used to conduct impact path analysis of the three influencing factors and target variables. The three impact factors were (1) Whether to provide online medical records, (2) Degree of concern for health, and (3) Whether to use internet. This paper proposes recommendations based on the three impact factors, thereby promoting the usefulness of medical records in a larger group of people. |
| format | Article |
| id | doaj-art-ee521356f86d4f37a2b97066c9fda05d |
| institution | Kabale University |
| issn | 2296-2565 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Public Health |
| spelling | doaj-art-ee521356f86d4f37a2b97066c9fda05d2025-08-20T05:32:56ZengFrontiers Media S.A.Frontiers in Public Health2296-25652025-08-011310.3389/fpubh.2025.16095031609503Frequent use of online medical records: analysis of influence factors based on structural equation modelingWei Wang0Lei Qin1Lei Qin2Yang Chen3Yinzhi Wang4Linglong Ye5Ruojia Wang6Yingqiu Zhu7School of Economics and Management, Guizhou Normal University, Guiyang, ChinaSchool of Statistics, University of International Business and Economics, Beijing, ChinaDong Fureng Institute of Economic and Social Development, Wuhan University, Wuhan, ChinaPetrochina (Beijing) Digital Intelligence Research Institute CO., LTD, Beijing, ChinaSchool of Finance, Shanghai University of International Business and Economics, Shanghai, ChinaSchool of Public Affairs, Xiamen University, Xiamen, ChinaSchool of Management, Beijing University of Traditional Chinese Medicine, Beijing, ChinaSchool of Statistics, University of International Business and Economics, Beijing, ChinaThe advent of electronic storage of medical records and the internet has led to an increase in the use of online medical records, thereby enhancing doctor–patient communication and facilitating medical treatment. Based on demographic and personal behavioral characteristics from the National Cancer Institute’s 2019–2020 National Trends in Health Information Survey data, this study explored the characteristics and factors influencing the frequent use of online medical records and compared them with those that do not. By combining traditional statistical tests and two machine learning algorithms, eight variables were identified as key variables in the frequent use of online medical records. These variables were then divided into three influencing factors (latent variables). The structural equation model was used to conduct impact path analysis of the three influencing factors and target variables. The three impact factors were (1) Whether to provide online medical records, (2) Degree of concern for health, and (3) Whether to use internet. This paper proposes recommendations based on the three impact factors, thereby promoting the usefulness of medical records in a larger group of people.https://www.frontiersin.org/articles/10.3389/fpubh.2025.1609503/fullonline medical recordsinfluence factorsstructural equation modelingHINTSpublic health |
| spellingShingle | Wei Wang Lei Qin Lei Qin Yang Chen Yinzhi Wang Linglong Ye Ruojia Wang Yingqiu Zhu Frequent use of online medical records: analysis of influence factors based on structural equation modeling Frontiers in Public Health online medical records influence factors structural equation modeling HINTS public health |
| title | Frequent use of online medical records: analysis of influence factors based on structural equation modeling |
| title_full | Frequent use of online medical records: analysis of influence factors based on structural equation modeling |
| title_fullStr | Frequent use of online medical records: analysis of influence factors based on structural equation modeling |
| title_full_unstemmed | Frequent use of online medical records: analysis of influence factors based on structural equation modeling |
| title_short | Frequent use of online medical records: analysis of influence factors based on structural equation modeling |
| title_sort | frequent use of online medical records analysis of influence factors based on structural equation modeling |
| topic | online medical records influence factors structural equation modeling HINTS public health |
| url | https://www.frontiersin.org/articles/10.3389/fpubh.2025.1609503/full |
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