Abstract: Objective To design a whole-process management system of analgesic pumps led by pain specialist nurses,and to evaluate its application effects. Methods We constructed the whole-process management system of intelligent analgesia pumps that integrated specialized nurse workstation modules and ward nurse workstation modules,led by pain specialist nurses,and with ward nurses as the main body. Meanwhile,a system trial was conducted in a tertiary Grade A general hospital from July 2021 to October 2021 to compare the differences of the inadequate analgesia rate within postoperative 24 hours,positive detection rate of adverse reactions related to analgesia,patient satisfaction,and nurse work time before and after the application of the system. Results After the application of whole-process management system of analgesic pumps,the rate of inadequate analgesia at 20：00 on the same day decreased from 12.09% to 5.9%（χ²=21.749,P<0.001),the rate of inadequate analgesia at 9:00 on the second day decreased from 20.1% to 15.1%（χ²=6.759,P=0.009）,the rate of inadequate analgesia at 16：00 on the second day had no statistically difference. The positive detection rate of analgesic related adverse reactions increased,the positive detection rate of nausea and vomiting increased from 9.2% to 31.5%（χ²=119.469,P<0.001) and the positive detection rate of dizziness increased from 3.6% to 8.1%（χ²=13.96,P<0.001). The patient satisfaction also increased from （4.90 ± 0.40） to （4.96 ± 0.25）,the average work time per day of specialized pain nurses decrea-sed from （93.85 ± 11.14） min/d to less than 20 minutes,and the average evaluation time for the analgesic pumps by ward nurses decreased from （29.72±8.80） s/time to 2 s/time,and the differences were statistically significant（P<0.05）. Conclusion Analgesia pump whole-process management system led by pain specialist nurses can not only effectively improve the quality of postoperative pain management and patient satisfaction,but also optimize the workflow and efficiency of pain management.

Key words: Analgesic, Specialist Nurse, Artificial Intelligence, Pain Management, Pain Care Specialty