Volume 23 Issue 6
Jun.  2025
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ZHAO Zichao, HU Bei, JIANG Fengjue, JIANG Zheng, SHI Xiaoyan, LI Linfei. Epidemiological characteristics and risk factors of 1 174 patients transferred between primary healthcare institutions[J]. Chinese Journal of General Practice, 2025, 23(6): 1031-1035. doi: 10.16766/j.cnki.issn.1674-4152.004059
Citation: ZHAO Zichao, HU Bei, JIANG Fengjue, JIANG Zheng, SHI Xiaoyan, LI Linfei. Epidemiological characteristics and risk factors of 1 174 patients transferred between primary healthcare institutions[J]. Chinese Journal of General Practice, 2025, 23(6): 1031-1035. doi: 10.16766/j.cnki.issn.1674-4152.004059

Epidemiological characteristics and risk factors of 1 174 patients transferred between primary healthcare institutions

doi: 10.16766/j.cnki.issn.1674-4152.004059
Funds:

 82072139

 KJ012021184

  • Received Date: 2024-06-19
    Available Online: 2025-09-04
  •   Objective  To analyze the epidemiological characteristics and influencing factors of inter-hospital patient transfers at the grassroots level, in order to provide a basis for optimizing regional healthcare capabilities and inter-hospital transfer processes.  Methods  Collected data on all inter-hospital transfers conducted by the Shaodong Emergency Medical Center from January 1, 2021 to December 31, 2023. The data included demographic characteristics, transfer distances, departments involved in sending and receiving, clinical assessments, and treatment measures. Statistical analysis was conducted to evaluate the factors influencing transfer outcomes.  Results  A total of 1 174 patients were included, with 804 males (68.48%) and 370 females (31.52%), and ages primarily concentrated between 50 and 79 years. Short-distance transfers (less than 50 km) accounted for 61.33% of all cases, with a median transfer distance of 45 km. The main sending departments were emergency medicine (16.70%), cardiology (12.95%), and neurology (11.41%), while the main receiving departments were emergency medicine (38.07%), emergency surgery (13.88%), and the intensive care unit (10.39%). Successful transfers were achieved in 97.10% of cases, while 2.90% resulted in transfer failure. There were statistically significant differences in the consciousness status, clinical assessments, respiratory support, and treatment measures of patients with different transfer results. The national early warning score can predict transfer result, with higher scores correlating with lower transfer success rates.  Conclusion  Grassroots inter-hospital transfers predominantly involve middle-aged and elderly male patients, with most transfers being short-distance. There is currently no single reliable tool for assessing transfer risk, necessitating a multifactorial evaluation approach. Future efforts should focus on strengthening regional medical alliances, optimizing resource allocation, and improving information-sharing mechanisms to enhance the efficiency and safety of inter-hospital transfers. Additionally, further development and validation of new transfer risk assessment tools are required to improve risk prediction during the transfer process.

     

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