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Chinese Journal of Antituberculosis ›› 2024, Vol. 46 ›› Issue (4): 424-432.doi: 10.19982/j.issn.1000-6621.20230367

• Original Articles • Previous Articles     Next Articles

Analysis of influencing factors of tuberculosis patients’ medical experience with the internet hospital platform

Zhou Shuang1, Zong Di2,3, Li Shixue2,3, Du Jian4   

  1. 1Reform and Performance Reform Office, Beijing Chest Hospital,Capital Medical University, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing 101149,China
    2Centre for Health Management and Policy Research, School of Public Health, Shandong University, Ji’nan 250012,China
    3NHC Key Lab of Health Economics and Policy Research, Shandong University, Ji’nan 250012,China
    4Beijing Chest Hospital, Capital Medical University, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing 101149,China
  • Received:2023-10-15 Online:2024-04-10 Published:2024-04-01
  • Contact: Du Jian
  • Supported by:
    Beijing Hospital Management Center 2020 (Phase 6) “Young Seedlings” Program(QMI20201602);The 2020 Open Project of the Hospital Management Institute of Capital Medical University(2020YGS06)

Abstract:

Objective: To investigate and discuss the influencing factors of tuberculosis (TB) patients’ experience of visiting the Internet hospital platform, to improve their experience of “Internet plus” medical services and the service quality of the Internet hospital platform. Methods: Using the form of random number table to sample 175 TB patients who visited the Beijing Chest Hospital Internet Hospital online platform between January and May 2022 and met the enrollment requirements, for telephone interview. A self-developed questionnaire was used to collect the patients’ basic information, medical treatment, and satisfaction data, and the “Internet +” patient experience scale was used to evaluate the patient experience. One hundred and fifty valid questionnaires were collected, with an effective rate of 85.7% (150/175). t test, ANOVA and multiple linear regression analysis were used respectively for univariable analysis and multiple factor analysis. Results: The overall average score of the patient experience was (59.44±7.06), with the highest score (4.41±0.62) for the safety dimension and the lowest score (3.97±0.66) for the accessibility dimension. The results of the univariable analysis showed that patients’ age (F=8.477, P<0.01), residence (F=3.285, P<0.05), and occupation (F=3.158, P<0.01) were statistically related with patient experience; waiting time for consultation (t=-3.099, P<0.01), consultation time (t=3.725, P<0.01), and doctor’s professionalism (F=4.887, P<0.01) were statistically related with patient experience; satisfaction with the overall visit (F=16.134, P<0.01), with the consultation process (F=21.862, P<0.01), with the accessibility to medical resources (F=24.165, P<0.01), with doctors (F=20.458, P<0.01), and with the Beijing Chest Hospital (F=17.176, P<0.01) were statistically related with patient experience. In the multiple linear regression analysis, compared with the suburbs of Beijing, patients from Tianjin City or Hebei Province had better medical experience (t=2.386,P<0.05); Compared with retired people, staffs of government and public institutions, company employees, self-employed people, unemployed people all had better medical experience (t=2.585, P<0.05; t=2.626, P<0.05; t=2.839, P<0.01; t=2.424, P<0.05); Patients with waiting time ≥30 min, having enough time for consultation, having high satisfaction with ease of access to medical resources and satisfaction with doctors had better medical experience (t=3.402,P<0.01;t=-2.775,P<0.01;t=2.329,P<0.05;t=2.064,P<0.05). Conclusion: The overall experience of TB patients in the Internet hospital platform is good, and patients’ age, residence, occupation, waiting time for consultation, consultation time, and satisfaction with resource access and doctors affect the experience of TB patients. Improving the above aspects and paying more attention to key groups will improve patient experience and service quality of the Internet hospital platform.

Key words: Tuberculosis, Questionnaires, Health services, Factor analysis, statistical, Computer communication networks, Patient satisfaction

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