Application of Cross-department Collaborative Intervention Based on Seamless Nursing Objective in Interventional Thrombolysis of Deep Vein Thrombosis of Lower Extremities
Objective To investigate the clinical effect of cross-department collaboration based on seamless nursing objective in the interventional thrombolysis treatment of deep vein thrombosis of lower extremities.Methods A total of 80 patients with interventional thrombolysis of deep vein thrombosis of lower limbs admitted to the Department of Sur-gery of Putian Fifth Hospital from May 2021 to May 2022 were simple and randomly selected as the research objects and divided into two groups according to random number table method,with 40 cases in each group.The control group was treated with routine nursing intervention,while the observation group was treated with cross-department collabora-tive intervention based on seamless nursing goal.The scores of anxiety state,complication rate and quality of life were compared between the two groups before and after intervention.Results After intervention,the scores of state anxiety and trait anxiety in the observation group were lower than those in the control group,the differences were statistically significant(both P<0.05).The complication rate of observation group was 2.50%lower than that of control group(20.00%),the difference was statistically significant(χ2=4.507,P<0.05).After intervention,the quality of life scale score of the observation group was higher than that of the control group,and the differences were statistically signifi-cant(all P<0.05).Conclusion In the interventional thrombolytic treatment of deep vein thrombosis of lower extremi-ties,the effect of cross-department collaborative intervention based on the goal of seamless nursing is significant,which can not only effectively reduce the anxiety state of patients,but also reduce the occurrence of complications and improve their quality of life.
Lower extremity deep vein thrombosisInterventional thrombolysisSeamless nursingCross-department collaboration
万方数据
维普
