健康索赔数据中慢性肾病的诊断效力随时间变化:德国社区老年人队列研究结果

IF 3.4 2区 医学 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH Clinical Epidemiology Pub Date : 2024-02-22 DOI:10.2147/clep.s438096
Tim Bothe, Anne-Katrin Fietz, Elke Schaeffner, Antonios Douros, Anna Pöhlmann, Nina Mielke, Cédric Villain, Muhammad Helmi Barghouth, Volker Wenning, Natalie Ebert
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引用次数: 0

摘要

目的:对于健康索赔数据中慢性肾脏病(CKD)的 ICD-10 诊断代码在普通人群中的有效性以及随着时间推移的有效性还没有进行充分的研究:我们使用了柏林倡议研究(BIS)的数据,该研究是对德国柏林年龄≥ 70 岁的社区居民进行的前瞻性纵向队列研究。以估算的肾小球滤过率(eGFR)为参考,我们评估了 CKD G3-5 期(eGFR < 60mL/min/1。73m²:ICD-10 N18.x-N19)、G3(eGFR 30-< 60mL/min/1.73m²:N18.3)和 G4-5(eGFR < 30mL/min/1.73m²:N18.4- 5)。我们分析了五次研究访问(2009-2019 年)的趋势:我们纳入了基线(2009- 2011年)时的2068名参与者和随访4(2018- 2019年)时的870名参与者的数据,其中分别有784人(38.9%)和440人(50.6%)患有CKD G3-5。基线时,根据所包含的 ICD-10 编码,理赔数据中 CKD 的灵敏度在 0.25(95% 置信区间 [CI] 0.22- 0.28)到 0.51(95%-CI 0.48-0.55)之间,G3 为 0.20(95%-CI 0.18-0.24),G4-5 为 0.36(95%-CI 0.25-0.49)。在 10 年的时间里,所有组别的灵敏度都增加了 0.17 至 0.29。随着时间的推移,特异性、PPV 和 NPV 基本保持稳定,在所有研究访问中分别为 0.82-0.99、0.47-0.89 和 0.66-0.98:德国的理赔数据显示,在识别患有慢性肾脏病的老年人方面总体表现良好,但对不同阶段的区分有限。我们的结果表明,随着时间的推移,灵敏度在不断提高,这可能归因于对 CKD 诊断和认识的提高:慢性肾脏病 诊断有效性 健康索赔数据 敏感性 特异性
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Diagnostic Validity of Chronic Kidney Disease in Health Claims Data Over Time: Results from a Cohort of Community-Dwelling Older Adults in Germany
Purpose: The validity of ICD-10 diagnostic codes for chronic kidney disease (CKD) in health claims data has not been sufficiently studied in the general population and over time.
Patients and Methods: We used data from the Berlin Initiative Study (BIS), a prospective longitudinal cohort of community-dwelling individuals aged ≥ 70 years in Berlin, Germany. With estimated glomerular filtration rate (eGFR) as reference, we assessed the diagnostic validity (sensitivity, specificity, positive [PPV], and negative predictive values [NPV]) of different claims-based ICD-10 codes for CKD stages G3-5 (eGFR < 60mL/min/1.73m²: ICD-10 N18.x-N19), G3 (eGFR 30–< 60mL/min/1.73m²: N18.3), and G4-5 (eGFR < 30mL/min/1.73m²: N18.4– 5). We analysed trends over five study visits (2009– 2019).
Results: We included data of 2068 participants at baseline (2009– 2011) and 870 at follow-up 4 (2018– 2019), of whom 784 (38.9%) and 440 (50.6%) had CKD G3-5, respectively. At baseline, sensitivity for CKD in claims data ranged from 0.25 (95%-confidence interval [CI] 0.22– 0.28) to 0.51 (95%-CI 0.48– 0.55) for G3-5, depending on the included ICD-10 codes, 0.20 (95%-CI 0.18– 0.24) for G3, and 0.36 (95%-CI 0.25– 0.49) for G4-5. Over the course of 10 years, sensitivity increased by 0.17 to 0.29 in all groups. Specificity, PPVs, and NPVs remained mostly stable over time and ranged from 0.82– 0.99, 0.47– 0.89, and 0.66– 0.98 across all study visits, respectively.
Conclusion: German claims data showed overall agreeable performance in identifying older adults with CKD, while differentiation between stages was limited. Our results suggest increasing sensitivity over time possibly attributable to improved CKD diagnosis and awareness.

Keywords: CKD, diagnostic validity, health claims data, sensitivity, specificity
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来源期刊
Clinical Epidemiology
Clinical Epidemiology Medicine-Epidemiology
CiteScore
6.30
自引率
5.10%
发文量
169
审稿时长
16 weeks
期刊介绍: Clinical Epidemiology is an international, peer reviewed, open access journal. Clinical Epidemiology focuses on the application of epidemiological principles and questions relating to patients and clinical care in terms of prevention, diagnosis, prognosis, and treatment. Clinical Epidemiology welcomes papers covering these topics in form of original research and systematic reviews. Clinical Epidemiology has a special interest in international electronic medical patient records and other routine health care data, especially as applied to safety of medical interventions, clinical utility of diagnostic procedures, understanding short- and long-term clinical course of diseases, clinical epidemiological and biostatistical methods, and systematic reviews. When considering submission of a paper utilizing publicly-available data, authors should ensure that such studies add significantly to the body of knowledge and that they use appropriate validated methods for identifying health outcomes. The journal has launched special series describing existing data sources for clinical epidemiology, international health care systems and validation studies of algorithms based on databases and registries.
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