ArticleHeliyon2024
Design and evaluation of an intelligent physical examination system in improving the satisfaction of patients with chronic disease.
Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Article
- Optimization of Batch Centralized Health Examination Scheduling Considering Inter-Item Transition Time and Sex Differences: An Empirical Optimization Study.Health science reports · 2026Article
- An empirical investigation into the altering health perspectives in the internet of health things.International journal of information technology : an official journal of Bharati Vidyapeeth's Institute of Computer Applications and Management · 2023Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: and Purpose: Enhancing patient satisfaction remains crucial for healthcare quality. The utilization of artificial intelligence (AI) in the Internet of Health Things (loHT) can streamline the medical examination process. Most Traditional Chinese Medicine (TCM) examinations are non-invasive and contribute significantly to patient satisfaction. Our aim was to establish an intelligent physical examination system that amalgamates TCM and Western medicine and to conduct a preliminary investigation into its effectiveness in enhancing the satisfaction of patients with chronic diseases. Materials and methods: Experts from clinical departments, the equipment department, and the software development department were invited to participate in group discussions to determine the design principles and organizational structure of the intelligent physical examination system. This system integrates TCM and Western medicine. We compared the satisfaction levels of patients examined using the intelligent physical examination system with those examined using the traditional medical examination system. Results: An intelligent physical examination system, combining TCM and Western medicine, was developed. A total of 106 patients were finally enrolled (intelligent group vs. control group) to evaluate satisfaction. There were no statistically significant differences between the intelligent group and the control group in age, gender, education, or income level. We identified significant differences in five aspects of satisfaction: 1) the physical examination environment; 2) the attitude and responsiveness of doctors; 3) the attitude and responsiveness of nurses; 4) the effectiveness of obtaining results; and 5) the information regarding physical examination and medical advice (p < 0.05). Furthermore, these differences remained statistically significant even after adjusting for age, gender, education, and income level. Conclusions: The intelligent physical examination system effectively capitalized on the advantages of combining AI with the integration of TCM and Western medicine, substantially optimizing the medical examination process. In comparison to the traditional physical examination system, the intelligent system significantly enhanced patient satisfaction. Future improvements could involve integrating chronic disease follow-up technology into the system.
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Registered trials
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