ORIGINAL RESEARCH article
Front. Public Health
Sec. Digital Public Health
Volume 13 - 2025 | doi: 10.3389/fpubh.2025.1609503
This article is part of the Research TopicUnlocking the Potential of Health Data: Interoperability, Security, and Emerging Challenges in AI, LLM, Precision Medicine, and Their Impact on Healthcare and ResearchView all 6 articles
Frequent Use of Online Medical Records: Analysis of Influence Factors Based on Structural Equation Modeling
Provisionally accepted
- 1Guizhou Normal University, Guiyang, Guizhou Province, China
- 2University of International Business and Economics, Beijing, Beijing Municipality, China
- 3Petrochina (beijing) Digital Intelligence Research Institute CO., LTD, Beijing, China
- 4Shanghai University of International Business and Economics, Shanghai, Shanghai Municipality, China
- 5Xiamen University, Xiamen, Fujian Province, China
- 6Beijing University of Chinese Medicine, Beijing, Beijing Municipality, China
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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.
Keywords: Online medical records, Influence factors, Structural Equation Modeling, hints, Public Health
Received: 17 Apr 2025; Accepted: 06 Aug 2025.
Copyright: © 2025 Wang, QIN, 阳, Wang, Ye, Wang and Zhu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Yingqiu Zhu, University of International Business and Economics, Beijing, Beijing Municipality, China
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