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Validity of ICD-10-CM diagnoses to identify hospitalizations for serious Infections among patients treated with biologic therapies

机译:ICD-10-CM的有效性诊断识别治疗生物疗法治疗的患者的严重感染住院治疗

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Purpose: Identifying hospitalizations for serious infections among patients dispensed biologic therapies within healthcare databases is important for post-marketing surveillance of these drugs. We determined the positive predictive value (PPV) of an ICD-10-CM-based diagnostic coding algorithm to identify hospitalization for serious infection among patients dispensed biologic therapy within the FDA's Sentinel Distributed Database. Methods: We identified health plan members who met the following algorithm criteria: (1) hospital ICD-10-CM discharge diagnosis of serious infection between July 1, 2016 and August 31, 2018; (2) either outpatient/emergency department infection diagnosis or outpatient antimicrobial treatment within 7 days prior to hospitalization; (3) inflammatory bowel disease, psoriasis, or rheumatological diagnosis within 1 year prior to hospitalization, and (4) were dispensed outpatient biologic therapy within 90 days prior to admission. Medical records were reviewed by infectious disease clinicians to adjudicate hospitalizations for serious infection. The PPV (95% confidence interval [Cl]) for confirmed events was determined after further weighting by the prevalence of the type of serious infection in the database. Results: Among 223 selected health plan members who met the algorithm, 209 (93.7% [95% Cl, 90.1%-96.9%]) were confirmed to have a hospitalization for serious infection. After weighting by the prevalence of the type of serious infection, the PPV of the ICD-10-CM algorithm identifying a hospitalization for serious infection was 80.2% (95% Cl, 75.3%-84.7%). Conclusions: The ICD-10-CM-based algorithm for hospitalization for serious infection among patients dispensed biologic therapies within the Sentinel Distributed Database had 80% PPV for confirmed events and could be considered for use within pharmacoepidemiologic studies.
机译:目的:在医疗保健数据库中确定使用生物疗法的患者中因严重感染而住院的情况,对于这些药物的上市后监测非常重要。我们确定了基于ICD-10-CM的诊断编码算法的阳性预测值(PPV),用于在FDA的Sentinel分布式数据库中确定接受生物治疗的患者因严重感染住院的情况。方法:我们确定符合以下算法标准的健康计划成员:(1)2016年7月1日至2018年8月31日期间,医院ICD-10-CM出院诊断为严重感染;(2) 住院前7天内门诊/急诊感染诊断或门诊抗菌治疗;(3) 住院前1年内诊断为炎症性肠病、银屑病或风湿病;(4)入院前90天内接受门诊生物治疗。传染病临床医生审查医疗记录,以判定严重感染的住院治疗。根据数据库中严重感染类型的患病率进一步加权后,确定确诊事件的PPV(95%置信区间[Cl])。结果:在223名符合该算法的健康计划成员中,209人(93.7%[95%Cl,90.1%-96.9%])被确认因严重感染住院。根据严重感染类型的患病率进行加权后,ICD-10-CM算法识别严重感染住院的PPV为80.2%(95%Cl,75.3%-84.7%)。结论:基于ICD-10-CM的算法用于在哨兵分布式数据库中分配生物疗法的患者因严重感染住院治疗,对于确诊事件的PPV为80%,可以考虑在药物流行病学研究中使用。

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