Systematic Review of Validation Studies of the Use of Administrative Data to Identify Serious Infections
Systematic Review of Validation Studies of the Use of Administrative Data to Identify Serious Infections
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DOI：
10.1002/acr.21959
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发表时间：
2013-08-01
影响因子：
4.7
通讯作者：
Fortin, Paul R.
中科院分区：
文献类型：
--
作者：
Barber, Claire;Lacaille, Diane;Fortin, Paul R.
objective.为了进行系统的文献回顾的验证算法识别感染的管理数据，为未来使用的人群与风湿性疾病。使用1950年至2012年10月期间的主题"管理数据"和"感染"检索Medline和EMBase。入选标准包括对成人人群中识别感染的管理数据进行验证研究。文章的质量进行了评估，使用一个有效的工具。共识别出5，941篇文章，对90篇文章进行了详细审查，纳入了24项研究。大多数（17/24）检查细菌感染，9检查机会性感染。18项研究来自美国，除4项研究外，所有研究均使用国际疾病分类第九版代码。24篇文献中有6篇研究了风湿性关节炎患者。一般而言，细菌感染研究报告了使用管理数据诊断感染的高度可变的灵敏度和阳性预测值（PPV）（灵敏度范围为4.4 - 100%，PPV范围为21.7 - 100%）。识别机会性感染的算法同样具有高度可变的灵敏度（范围20 - 100%）和PPV（范围1.3 - 100%）。13项研究比较了不同算法的诊断准确性，结果表明，包括使用更多诊断代码或在任何位置使用代码的综合算法的策略对感染诊断的敏感性最高。将微生物学或药学数据与诊断代码相结合的算法改进了PPV用于识别结核病。应根据研究目的选择使用管理数据识别感染的算法，并仔细考虑是否需要高灵敏度或PPV。
Objective. To conduct a systematic review of the literature on the validation of algorithms identifying infections in administrative data for future use in populations with rheumatic diseases.Methods. Medline and EMBase were searched using the themes "administrative data" and "infection" between 1950 and October 2012. Inclusion criteria consisted of validation studies of administrative data identifying infections in adult populations. Article quality was assessed using a validated tool.Results. A total of 5,941 articles were identified, 90 articles underwent detailed review, and 24 studies were included. The majority (17 of 24) examined bacterial infections and 9 examined opportunistic infections. Eighteen studies were from the US and all but 4 studies used International Classification of Diseases, Ninth Revision codes. Rheumatoid arthritis patients were studied in 6 of 24 articles. The studies on bacterial infections in general reported highly variable sensitivity and positive predictive value (PPV) for the diagnosis of infections using administrative data (sensitivity range 4.4-100%, PPV range 21.7-100%). Algorithms to identify opportunistic infections similarly had a highly variable sensitivity (range 20-100%) and PPV (range 1.3-100%). Thirteen studies compared the diagnostic accuracy of different algorithms, which revealed that strategies including a comprehensive algorithm using a greater number of diagnostic codes or codes in any position had the highest sensitivity for the diagnosis of infection. Algorithms that incorporated microbiologic or pharmacy data in combination with diagnostic codes had improved PPV for identification of tuberculosis.Conclusion. Algorithms for identifying infections using administrative data should be selected based on the purpose of the study, with careful consideration as to whether a high sensitivity or PPV is required.