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利用数据挖掘方法和健康管理信息系统分析减重手术后的治疗轨迹。

Analysis of Trajectories of Care After Bariatric Surgery Using Data Mining Method and Health Administrative Information Systems.

机构信息

Sorbonne Universités, UPMC Univ Paris 06, UMRS 1138, Centre de Recherche des Cordeliers, Paris, France.

INSERM, UMRS 1138, Centre de Recherche des Cordeliers, Paris, France.

出版信息

Obes Surg. 2020 Jun;30(6):2206-2216. doi: 10.1007/s11695-020-04430-6.

Abstract

CONTEXT

The 30-day readmission rate after bariatric surgery is considered an important metric of the quality of hospital care. However, readmission rate beyond 30 days is rarely reported and does not provide any information about trajectories of care which would be of great interest for healthcare planning. The aim of this study was to analyze trajectories of care during the first year after bariatric surgery on a nationwide basis using data mining methods.

METHOD

This was a retrospective descriptive study on the trajectories of care within the first year after bariatric surgery. Data were extracted from a national administrative claims database (the PMSI database) and trajectories were defined as principal diagnosis of successive readmissions. Formal Concept Analysis was performed to find common concepts of trajectories of care.

RESULTS

We included for analysis 198,389 bariatric procedures performed on 196,323 patients. Twelve main concepts were selected. About one third of patients (32.4%) were readmitted in the first year after surgery. Most common trajectories were as follows: regular follow-up (14.9%), cholelithiasis (2.2%), abdominal pain (1.9%), and abdominal sepsis (1.3%). Important differences were found in trajectories among different bariatric procedures: 1.8% of gastric banding patients had pregnancy-related events (delivery or medical abortion), while we observed a readmission rate for abdominal sepsis in 2.7% and 5.1% of patients operated of gastric bypass and sleeve gastrectomy respectively.

CONCLUSION

Administrative claim data can be analyzed through Formal Concept Analysis in order to classify trajectories of care. This approach permits to quantify expected postoperative complications and to identify unexpected events.

摘要

背景

减重手术后 30 天的再入院率被认为是医院护理质量的一个重要指标。然而,超过 30 天的再入院率很少被报道,并且不能提供任何有关护理轨迹的信息,这对于医疗保健规划非常重要。本研究的目的是使用数据挖掘方法,基于全国范围的研究,分析减重手术后一年内的护理轨迹。

方法

这是一项关于减重手术后一年内护理轨迹的回顾性描述性研究。数据从国家行政索赔数据库(PMSI 数据库)中提取,轨迹定义为连续再入院的主要诊断。通过形式概念分析找到护理轨迹的常见概念。

结果

我们分析了 196323 名患者的 198389 例减重手术。选择了 12 个主要概念。大约三分之一的患者(32.4%)在手术后的第一年再次入院。最常见的轨迹如下:常规随访(14.9%)、胆石症(2.2%)、腹痛(1.9%)和腹部脓毒症(1.3%)。不同减重手术之间的轨迹存在显著差异:胃带术患者中有 1.8%发生与妊娠相关的事件(分娩或药物流产),而胃旁路术和袖状胃切除术患者的腹部脓毒症再入院率分别为 2.7%和 5.1%。

结论

可以通过形式概念分析对行政索赔数据进行分析,以对护理轨迹进行分类。这种方法可以量化预期的术后并发症,并识别意外事件。

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