The Department of Orthopaedic Surgery and Rehabilitation, University of Iowa Hospitals and Clinics, Iowa City, Iowa.
The Department of Surgery and Perioperative Care, Dell Medical School at the University of Texas at Austin, Austin, Texas.
J Arthroplasty. 2018 Jan;33(1):41-45.e3. doi: 10.1016/j.arth.2017.09.003. Epub 2017 Sep 13.
Use of large databases for orthopedic research has become extremely popular in recent years. Each database varies in the methods used to capture data and the population it represents. The purpose of this study was to evaluate how these databases differed in reported demographics, comorbidities, and postoperative complications for primary total hip arthroplasty (THA) patients.
Primary THA patients were identified within National Surgical Quality Improvement Programs (NSQIP), Nationwide Inpatient Sample (NIS), Medicare Standard Analytic Files (MED), and Humana administrative claims database (HAC). NSQIP definitions for comorbidities and complications were matched to corresponding International Classification of Diseases, 9th Revision/Current Procedural Terminology codes to query the other databases. Demographics, comorbidities, and postoperative complications were compared.
The number of patients from each database was 22,644 in HAC, 371,715 in MED, 188,779 in NIS, and 27,818 in NSQIP. Age and gender distribution were clinically similar. Overall, there was variation in prevalence of comorbidities and rates of postoperative complications between databases. As an example, NSQIP had more than twice the obesity than NIS. HAC and MED had more than 2 times the diabetics than NSQIP. Rates of deep infection and stroke 30 days after THA had more than 2-fold difference between all databases.
Among databases commonly used in orthopedic research, there is considerable variation in complication rates following THA depending upon the database used for analysis. It is important to consider these differences when critically evaluating database research. Additionally, with the advent of bundled payments, these differences must be considered in risk adjustment models.
近年来，利用大型数据库进行骨科研究已变得非常流行。每个数据库在用于捕获数据的方法和代表的人群方面都有所不同。本研究的目的是评估这些数据库在报告的人口统计学、合并症和初次全髋关节置换术（THA）患者的术后并发症方面有何不同。
在国家外科质量改进计划（NSQIP）、全国住院患者样本（NIS）、医疗保险标准分析文件（MED）和Humana 行政索赔数据库（HAC）中确定初次 THA 患者。将合并症和并发症的 NSQIP 定义与相应的国际疾病分类第 9 版/当前程序术语代码相匹配，以查询其他数据库。比较人口统计学、合并症和术后并发症。
每个数据库的患者数量分别为 HAC 中的 22644 例、MED 中的 371715 例、NIS 中的 188779 例和 NSQIP 中的 27818 例。年龄和性别分布在临床上相似。总体而言，各数据库之间的合并症患病率和术后并发症发生率存在差异。例如，NSQIP 的肥胖症患病率是 NIS 的两倍多。HAC 和 MED 的糖尿病患者比 NSQIP 多两倍多。THA 后 30 天深部感染和中风的发生率在所有数据库之间存在 2 倍以上的差异。
在骨科研究中常用的数据库中，根据用于分析的数据库，THA 后并发症发生率存在很大差异。在批判性评估数据库研究时，必须考虑这些差异。此外，随着捆绑支付的出现，在风险调整模型中必须考虑这些差异。
