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目的:开发基于“云+端”数据驱动技术的加速康复信息管理系统，用于全膝关节置换术围手术期的医护患交互和患者康复管理，并评价其实施效果。方法:回顾性分析山东大学齐鲁医院骨外科96例单侧全膝关节置换术患者的临床资料，2018年2—8月的48例患者为对照组，采用传统管理；2019年2—8月的48例患者为干预组，采用基于数据驱动技术，医护患三者之间信息可自动匹配、相互交互和推送的加速康复信息管理系统进行管理。比较2组患者的美国纽约特种外科医院膝关节评分（HSS）、疼痛视觉模拟评分（VAS）、焦虑自评量表评分（SAS）、术后住院天数及患者就医过程满意度。结果:住院日干预组SAS评分为（41.52 ± 4.65）分，优于对照组的（52.60 ± 4.84）分，2组比较差异有统计学意义（n F值为11.446，n P<0.05），术后3 d干预组的HSS、VAS、SAS评分分别为（56.31 ± 5.81）、（2.79 ± 0.68）、（38.69 ± 3.81）分，优于对照组的（51.31 ± 5.20）、（4.31 ± 0.78）、（46.02 ± 3.86）分，2组比较差异均有统计学意义（n F值为4.44、10.19、9.37，均n P<0.05）；术后1周干预组的HSS、VAS、SAS评分分别为（71.35 ± 3.59）、（1.98 ± 0.67）、（36.81 ± 4.03）分，优于对照组的（67.15 ± 3.67）、（2.60 ± 0.87）、（39.48 ± 4.04）分，2组比较差异均有统计学意义（n F值为5.683、3.951、3.237，均n P<0.05）；干预组患者术后住院天数为（3.98 ± 0.84）d，小于对照组的（6.00 ± 0.80）d，差异有统计学意义（n F值为146.286，n P<0.05）；干预组患者就医过程满意度为（97.46 ± 1.73）分，高于对照组的（94.35 ± 2.04）分，差异有统计学意义（n F值为64.911，n P<0.05）。n 结论:通过基于“云+端”数据驱动的全膝关节置换术加速康复管理系统可以提升对全膝关节置换术患者的管理水平，降低患者住院时间和提升患者满意度。“,”Objective:To develop an total knee arthroplasty(TKA) enhanced recovery after surgery information management system based on “cloud + terminal” data-drivene technology, which can be used in the perioperative interaction between doctors and patients and rehabilitation management of TKA, and evaluate its implementation effect.Methods:The clinical data of 96 patients with unilateral TKA from Qilu Hospital Shandong University were analyzed retrospectively. Forty eight patients in the control group from February to August, 2018 were treated with traditional management. From February to August, 2019, 48 patients in the research group adopted the accelerated rehabilitation information management system based on data-driven technology, which can automatically match, interact and push the information between medical and patient.Results:The Self-rating Anxiety Scale(SAS) score of the intervention group on hospitalization day was 41.52±4.65, which was better than that of the control group (52.60±4.84). The difference between the two groups was statistically significant (n F value was 11.446, n P<0.05). The scores of Hospital for Special Surgery(HSS), Visual Analogue Scale(VAS) and SAS in the intervention group 3 days after operation were 56.31±5.81, 2.79±0.68, 38.69±3.81, which were better than those of the control group (51.31±5.20, 4.31±0.78, 46.02±3.86). The difference between the two groups was statistically significant (n F value was 4.44, 10.19, 9.37, all n P<0.05); the HSS, VAS, and SAS scores of the intervention group one week after operation were 71.35±3.59, 1.98± 0.67, 36.81±4.03, better than the control group (67.15±3.67, 2.60±0.87, 39.48±4.04), the difference between the two groups was statistically significant (n F value was 5.683, 3.951, 3.237, all n P<0.05); the postoperative hospital stay in the intervention group was (3.98±0.84) days, which was less than (6.00±0.80) days in the control group, the difference was statistically significant (n F value was 146.286, n P<0.05); The patients′ satisfaction score in the intervention group during medical treatment was 97.46±1.73, which was higher than the control group (94.35±2.04), the difference was statistically significant (n F value was 64.911, n P<0.05).n Conclusions:TKA enhanced recovery management system based on “cloud + terminal” data-drivene can improve the management level of TKA patients, reduce the length of stay and improve satisfaction of patients.