Validation of acute myocardial infarction in the Food and Drug Administration's Mini-Sentinel program.
Validation of acute myocardial infarction in the Food and Drug Administration's Mini-Sentinel program.
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DOI：
10.1002/pds.3310
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发表时间：
2013-01
影响因子：
2.6
通讯作者：
Gurwitz, Jerry H.
中科院分区：
文献类型：
--
作者：
Cutrona, Sarah L.;Toh, Sengwee;Iyer, Aarthi;Foy, Sarah;Daniel, Gregory W.;Nair, Vinit P.;Ng, Daniel;Butler, Melissa G.;Boudreau, Denise;Forrow, Susan;Goldberg, Robert;Gore, Joel;McManus, David;Racoosin, Judith A.;Gurwitz, Jerry H.
关键词：
验证基于国际疾病分类第9版临床修改（ICD-9-CM）代码的算法，用于微型哨兵分布式数据库（MSDD）中记录的急性心肌梗死（AMI）。使用基于ICD-9-CM的算法（主要位置为410.x0或410.x1的住院患者），我们从参与Mini-Sentinel计划的4个数据合作伙伴中确定了2009年潜在AMI病例的随机样本。心脏病专家评审员使用从医院记录中提取的信息，根据欧洲心脏病学会和美国心脏病学会全球工作组的联合标准评估AMI诊断的可能性。计算基于ICD-9算法的阳性预测值（PPV）。在确定的153例潜在AMI病例中，检索并提取了143例（93%）的医院记录。总体而言，PPV为86.0%（95%置信区间; 79.2%，91.2%）。4个数据合作伙伴的PPV范围为76.3%至94.3%。使用基于ICD-9-CM的算法确定的潜在AMI病例的总体PPV对于安全性监测可能是可接受的;但是，PPV确实因数据合作伙伴而异。该验证工作提供了对该算法可靠性的当代估计，以用于使用FDA的MSDD进行的未来监测工作。
To validate an algorithm based upon International Classification of Diseases, 9th revision, Clinical Modification (ICD-9-CM) codes for acute myocardial infarction (AMI) documented within the Mini-Sentinel Distributed Database (MSDD). Using an ICD-9-CM-based algorithm (hospitalized patients with 410.x0 or 410.x1 in primary position), we identified a random sample of potential cases of AMI in 2009 from 4 Data Partners participating in the Mini-Sentinel Program. Cardiologist reviewers used information abstracted from hospital records to assess the likelihood of an AMI diagnosis based on criteria from the joint European Society of Cardiology and American College of Cardiology Global Task Force. Positive predictive values (PPVs) of the ICD-9-based algorithm were calculated. Of the 153 potential cases of AMI identified, hospital records for 143 (93%) were retrieved and abstracted. Overall, the PPV was 86.0% (95% confidence interval; 79.2%, 91.2%). PPVs ranged from 76.3% to 94.3% across the 4 Data Partners. The overall PPV of potential AMI cases, as identified using an ICD-9-CM-based algorithm, may be acceptable for safety surveillance; however, PPVs do vary across Data Partners. This validation effort provides a contemporary estimate of the reliability of this algorithm for use in future surveillance efforts conducted using the FDA’s MSDD.
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