Department of Learning Health Sciences, University of Michigan Medical School, NCRC Building 14, #G100, G014-130, 2800 Plymouth Rd, Ann Arbor, MI, 48109, USA.
Institute for Healthcare Policy & Innovation, University of Michigan, Ann Arbor, MI, USA.
BMC Med Res Methodol. 2020 Mar 4;20(1):54. doi: 10.1186/s12874-020-00937-9.
Claims-based algorithms are commonly used to identify sepsis in health services research because the laboratory features required to define clinical criteria may not be available in administrative data.
We evaluated claims-based sepsis algorithms among adults in the US aged ≥65 years with Medicare health insurance enrolled in the REasons for Geographic And Racial Differences in Stroke (REGARDS) study. Suspected infections from baseline (2003-2007) through December 31, 2012 were analyzed. Two claims-based algorithms were evaluated: (1) infection plus organ dysfunction diagnoses or sepsis diagnoses (Medicare-Implicit/Explicit) and (2) Centers for Medicare and Medicaid Services Severe Sepsis/Septic Shock Measure diagnoses (Medicare-CMS). Three classifications based on clinical criteria were used as standards for comparison: (1) the sepsis-related organ failure assessment (SOFA) score (REGARDS-SOFA), (2) "quick" SOFA (REGARDS-qSOFA), and (3) Centers for Disease Control and Prevention electronic health record criteria (REGARDS-EHR).
There were 2217 suspected infections among 9522 participants included in the current study. The total number of suspected infections classified as sepsis was 468 for Medicare-Implicit/Explicit, 249 for Medicare-CMS, 541 for REGARDS-SOFA, 185 for REGARDS-qSOFA, and 331 for REGARDS-EHR. The overall agreement between Medicare-Implicit/Explicit and REGARDS-SOFA, REGARDS-qSOFA, and REGARDS-EHR was 77, 79, and 81%, respectively, sensitivity was 46, 53, and 57%, and specificity was 87, 82, and 85%. Comparing Medicare-CMS and REGARDS-SOFA, REGARDS-qSOFA, and REGARDS-EHR, agreement was 77, 87, and 85%, respectively, sensitivity was 27, 41, and 36%, and specificity was 94, 92, and 93%. Events meeting the REGARDS-SOFA classification had a lower 90-day mortality rate (140.7 per 100 person-years) compared with the Medicare-CMS (296.1 per 100 person-years), REGARDS-qSOFA (238.6 per 100 person-years), Medicare-Implicit/Explicit (219.4 per 100 person-years), and REGARDS-EHR classifications (201.8 per 100 person-years).
Claims-based sepsis algorithms have high agreement and specificity but low sensitivity when compared with clinical criteria. Both claims-based algorithms identified a patient population with similar 90-day mortality rates as compared with classifications based on qSOFA and EHR criteria but higher mortality relative to SOFA criteria.
在卫生服务研究中，基于索赔的算法通常用于识别败血症，因为定义临床标准所需的实验室特征可能无法在行政数据中获得。
我们评估了美国年龄≥65 岁、有医疗保险的成年人（医疗保险患者）在 REasons for Geographic And Racial Differences in Stroke（REGARDS）研究中的基于索赔的败血症算法。分析了 2003-2007 年基线至 2012 年 12 月 31 日期间的疑似感染。评估了两种基于索赔的算法：（1）感染加器官功能障碍诊断或败血症诊断（医疗保险隐含/明确）和（2）医疗保险和医疗补助服务中心严重败血症/败血症休克测量诊断（医疗保险-CMS）。使用三种基于临床标准的分类作为比较标准：（1）败血症相关器官衰竭评估（SOFA）评分（REGARDS-SOFA），（2）“快速”SOFA（REGARDS-qSOFA），和（3）疾病控制和预防中心电子健康记录标准（REGARDS-EHR）。
在当前研究中，共有 9522 名参与者中纳入了 2217 例疑似感染。分类为败血症的疑似感染总数为 468 例为医疗保险隐含/明确，249 例为医疗保险-CMS，541 例为 REGARDS-SOFA，185 例为 REGARDS-qSOFA，331 例为 REGARDS-EHR。医疗保险隐含/明确与 REGARDS-SOFA、REGARDS-qSOFA 和 REGARDS-EHR 的总体一致性分别为 77%、79%和 81%，灵敏度分别为 46%、53%和 57%，特异性分别为 87%、82%和 85%。医疗保险-CMS 与 REGARDS-SOFA、REGARDS-qSOFA 和 REGARDS-EHR 的一致性分别为 77%、87%和 85%，灵敏度分别为 27%、41%和 36%，特异性分别为 94%、92%和 93%。符合 REGARDS-SOFA 分类的事件的 90 天死亡率（每 100 人年 140.7 例）低于医疗保险-CMS（每 100 人年 296.1 例）、REGARDS-qSOFA（每 100 人年 238.6 例）、医疗保险隐含/明确（每 100 人年 219.4 例）和 REGARDS-EHR 分类（每 100 人年 201.8 例）。
与临床标准相比，基于索赔的败血症算法具有较高的一致性和特异性，但灵敏度较低。这两种基于索赔的算法确定的患者人群与 qSOFA 和 EHR 标准分类的 90 天死亡率相似，但与 SOFA 标准分类相比，死亡率更高。
