Performance of Administrative Algorithms to Identify Interstitial Lung Disease in Rheumatoid Arthritis
Performance of Administrative Algorithms to Identify Interstitial Lung Disease in Rheumatoid Arthritis
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DOI：
10.1002/acr.24043
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发表时间：
2020-10-01
影响因子：
4.7
通讯作者：
Mikuls, Ted R.
中科院分区：
文献类型：
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作者：
England, Bryant R.;Roul, Punyasha;Mikuls, Ted R.
目的确定基于管理的分类算法对类风湿关节炎（RA）合并间质性肺病（ILD）的分类性能。方法采用国际疾病分类第九次修订版（ICD-9）和ICD-10的编码对一个大型多中心RA登记研究的参与者进行ILD筛查。病历审查证实了筛选阳性的参与者和筛选阴性的随机样本中的ILD。从退伍军人事务部管理数据中提取ICD和程序代码、提供者专业和日期，以构建ILD算法。通过灵敏度、特异性、阳性预测值（PPV）、阴性预测值和kappa（使用逆概率加权来解释采样方法）评估这些算法对病历审查的性能。结果回顾性分析536例RA患者的病历资料，确诊ILD 182例（严格定义），203例（宽松定义）。最初，我们从住院或门诊就诊中确定≥ 2个ICD编码作为最佳鉴别因素（特异性96.0%，PPV 65.5%; kappa = 0.70）。随后，我们构建了一组ICD-9和ICD-10编码，提高了算法特异性（特异性96.8%，PPV 69.5%; kappa = 0.72）。包括肺科医生诊断或胸部计算机断层扫描加肺功能测试或肺活检的算法具有改善的性能（特异性98.0%，PPV 77.4%; kappa = 0.75）。与放宽的ILD定义（82.4%）和敏感性分析（83.4-86.3%）相比，排除其他ILD原因后PPV增加（78.5%）。随着算法要求的提高，特异性和PPV的增加伴随着灵敏度的下降。结论：ICD编码、提供者专业、诊断测试和排除其他ILD原因的最佳组合的管理算法可准确分类RA中的ILD。
Objective To determine the performance of administrative-based algorithms for classifying interstitial lung disease (ILD) complicating rheumatoid arthritis (RA). Methods Participants in a large, multicenter RA registry were screened for ILD using codes from the International Classification of Diseases, Ninth Revision (ICD-9) and the ICD-10. Medical record review confirmed ILD among participants screening positive and a random sample of those screening negative. ICD and procedure codes, provider specialty, and dates were extracted from Veterans Affairs administrative data to construct ILD algorithms. Performance of these algorithms against medical record review was assessed by sensitivity, specificity, positive predictive value (PPV), negative predictive value, and kappa using inverse probability weighting to account for sampling methods. Results Medical records of 536 RA patients were reviewed, confirming 182 (stringent definition) and 203 (relaxed definition) cases of ILD. Initially, we identified >= 2 ICD codes from inpatient or outpatient encounters as optimal discriminating factors (specificity 96.0%, PPV 65.5%; kappa = 0.70). Subsequently, we constructed a set of ICD-9 and ICD-10 codes that improved algorithm specificity (specificity 96.8%, PPV 69.5%; kappa = 0.72). Algorithms that included a pulmonologist diagnosis or chest computed tomography plus pulmonary function testing or lung biopsy had improved performance (specificity 98.0%, PPV 77.4%; kappa = 0.75). PPV increased with exclusion of other ILD causes (78.5%) in comparison with the relaxed ILD definition (82.4%) and in sensitivity analyses (83.4-86.3%). Gains in specificity and PPV with greater algorithm requirements were accompanied by declines in sensitivity. Conclusion Administrative algorithms with optimal combinations of ICD codes, provider specialty, diagnostic testing, and exclusion of other ILD causes accurately classify ILD in RA.