协和医学杂志2026，Vol.17Issue(3)：637-645,9.DOI:10.12290/xhyxzz.2026-0133
肺癌多学科诊疗模式的绩效评价与资源利用优化:一项真实世界研究
Performance Evaluation and Resource Utilization Optimization of Multidisciplinary Team Model for Lung Cancer:A Real-World Study
摘要
Abstract
Objective To compare the performance differences between the multidisciplinary team(MDT)model and the conventional diagnostic and treatment model for lung cancer,and to explore a high-qual-ity development pathway for optimizing lung cancer diagnostic and treatment resources.Methods A retrospec-tive analysis was conducted on electronic medical record data of lung cancer patients at Shanghai Chest Hospital from March 2025 to December 2025.Patients were divided into an MDT group and a conventional care group based on whether they were admitted to the integrated oncology ward.Statistical analyses were performed using the Mann-Whitney U test,trend chi-square test,and chi-square test.Subgroup analyses were conducted accord-ing to tumor stage(Ⅰ-Ⅳ)and relative weight(RW)risk stratification.Gamma regression and negative bino-mial regression models with robust standard errors clustered by patient ID were used to analyze the effects of MDT on cost per hospitalization and hospitalization frequency during the observation period.To adjust for differ-ences in observation time,the logarithm of observation days was used as an offset in the negative binomial re-gression,and calculate the incidence rate ratio.Heterogeneity across tumor stage and RW subgroups was as-sessed using interaction models.To enhance the robustness of causal inference,propensity score matching(PSM)and inverse probability of treatment weighting(IPTW)analyses were performed as sensitivity valida-tions.Results A total of 4,758 patients with primary lung cancer were included,comprising 365(7.7％)in the MDT group and 4,393(92.3％)in the conventional care group.After adjusting for confounding factors,the MDT model significantly reduced hospitalization frequency during the observation period by 48.8％(IRR= 0.512,95％CI:0.463-0.567,P<0.001).After further adjusting for observation days,MDT still significantly reduced hospitalization frequency(IRR=0.834,95％CI:0.698-0.997,P= 0.046),with the effect direction consistent with the main analysis.No statistically significant difference was observed in cost per hospitalization(IRR =0.942,95％CI:0.865-1.027,P= 0.178).Heterogeneity analysis revealed that the cost effect varied by tumor stage:cost increased in stageⅠpatients(IRR= 2.002),decreased in stageⅡ(IRR= 0.705)and stage Ⅳ(IRR=0.743)patients,and showed no change in stage Ⅲ patients.No significant cost effects were observed across RW subgroups.The reduction in hospitalization frequency was significant across all tumor stage and RW subgroups(IRR range:0.450-0.680),with no significant interactions(all P>0.05).Sensitivity analyses confirmed the ro-bustness of the hospitalization frequency effect(PSM:IRR= 0.581;IPTW:IRR= 0.520).The PSM analysis showed a significant reduction in cost per hospitalization in the MDT group(IRR= 0.878,95％CI:0.778- 0.992,P=0.036),while the IPTW analysis was consistent with the main analysis and showed no statistical sig-nificance(IRR= 0.943,95％CI:0.862-1.032,P= 0.218).Conclusions The MDT model for lung cancer significantly reduces hospitalization frequency;however,its effect on cost per hospitalization is population-selec-tive,with increased costs in early-stage(stageⅠ)patients and decreased costs in late-stage(stagesⅡand Ⅳ)pa-tients.The implementation of the MDT model should adopt precise patient stratification management,prioritizing the optimal patient population to achieve the optimal allocation of medical resources.关键词
肺癌/多学科诊疗/绩效评价/相对权重Key words
lung cancer/multidisciplinary team/performance evaluation/relative weight分类
医药卫生引用本文复制引用
王盟,张晓丽,刘珏,唐静怡,李子明..肺癌多学科诊疗模式的绩效评价与资源利用优化:一项真实世界研究[J].协和医学杂志,2026,17(3):637-645,9.基金项目
上海市医院协会医院管理研究基金(X2025164) （X2025164）
上海交通大学中国医院发展研究院决策咨询课题(CHDI-2026-Z-066) Shanghai Hospital Association Hospital Management Research Fund(X2025164) （CHDI-2026-Z-066）
Decision Consultation Project of China Hospital Development Institute,Shanghai Jiao Tong University(CHDI-2026-Z-066) （CHDI-2026-Z-066）
