Application of intelligent information system of transfusion reactions in the supervision and management of transfusion reactions

Abstract

Objective To analyze the application effect of intelligent information system of transfusion reactions(referred to as the system) in the supervision and management of transfusion reactions. Methods A retrospective analysis was conducted on the clinical data of a total of 67 914 blood transfusion patients in our hospital from January 2018 to August 2023. The patients were divided into the control group (n =36 367, with conventional transfusion management) and the observation group (n =31 547, with management by the system).The incidence of adverse reactions, the supervision and management scores, reporting time and processing time of adverse reactions, and patient satisfaction with blood transfusion in the two groups was observed. Results The incidence of transfusion reactions in the observation group and the control group was 0.23% (72/31 547) and 0.24% (86/36 367), with no statistically significant difference (P>0.05). The quality scores of the reporting, registration, processing and supervision, and the total scores of the observation group were higher than those of the control group:(21.46±2.76) vs (17.38±2.74) points, (21.65±2.80) vs (16.98±3.20) points, (22.30±2.42) vs (18.80±3.15) points, (22.85±2.10) vs (18.55 ± 3.06) points, and (90.38±5.96) vs (75.26 ± 6.10) points, with statistically significant difference(P<0.05). The reporting time and processing time of transfusion reactions in the observation group were shorter than those in the control group: (3.26±0.45) vs (7.25±1.26) minutes, (10.38±2.96) vs (20.26±2.10) minutes, with statistically significant differences (P<0.05). The satisfaction rate with blood transfusion of the observation group was 99.95% (31 532/31 547), higher than 99.62% (36 229/36 367) of the control group, with significant difference (P<0.05). Conclusion The application of the system in the supervision and management of transfusion reactions has achieved ideal results, including improving the quality of monitoring and management, shortening the reporting and processing time of transfusion reactions, and improving patient satisfaction with transfusion, which is worth popularizing.

Keywords

• intelligent information system of transfusion reactions
• transfusion reactions
• reporting time
• processing time
• satisfaction