Heliyon (Jan 2024)

Design and evaluation of an intelligent physical examination system in improving the satisfaction of patients with chronic disease

  • Xin Chen,
  • Ruxin Duan,
  • Yao Shen,
  • Hua Jiang

Journal volume & issue
Vol. 10, no. 1
p. e23906

Abstract

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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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