基于分阶段导航的数智化闭环护理在胰腺癌根治术患者中的应用研究

Objective To evaluate the effect of a staged navigation-based digital-intelligent closed-loop nursing model in patients undergoing radical pancreatic cancer surgery and to provide evidence for clinical nursing practice. Methods Using convenience sampling, 80 inpatients with pancreatic cancer admitted to a tertiary hospital in Shaanxi Province from July to November 2024 were selected as the control group, and another 80 inpatients admitted from January to May 2025 were assigned to the intervention group. The control group received the conventional care process encompassing outpatient consultation, hospital admission, and follow-up. The intervention group received the staged navigation-based digital-intelligent closed-loop nursing model. This model optimized care across pre-hospital assessment, the preadmission period, the in-hospital perioperative period, and post-discharge rehabilitation—through iterative cycles of identification, focusing, implementation, and quality control. Nutritional indicators were compared between the two groups before surgery, after surgery, and one month after discharge, along with postoperative complication rates, length of hospital stay, and hospitalization costs. Results Time and interaction effects for serum total protein, albumin, and globulin were statistically significant in both groups(P<0.05). The intervention group showed significantly lower rates of postoperative gastroparesis, pulmonary infection, and hemorrhage, as well as shorter hospital stay and lower total hospitalization costs than the control group(P<0.05). Conclusion The staged navigation-based digital-intelligent closedloop nursing model can effectively improve nutritional status, reduce postoperative complications, accelerate recovery, and alleviate the financial burden of care in patients undergoing radical pancreatic cancer surgery. It is worthy of further clinical promotion.