Health Policy, Quality & Informatics Program, Michael E. DeBakey VA Medical Center, Health Services Research & Development Center for Innovations, Houston, TX, USA; Section of Health Services Research, Department of Medicine, Baylor College of Medicine, Houston, TX, USA; Section of Cardiology, Michael E. DeBakey Veterans Affairs Medical Center, Houston, TX, USA; Section of Cardiovascular Research, Department of Medicine, Baylor College of Medicine, Houston, TX, USA.
Health Policy, Quality & Informatics Program, Michael E. DeBakey VA Medical Center, Health Services Research & Development Center for Innovations, Houston, TX, USA; Section of Health Services Research, Department of Medicine, Baylor College of Medicine, Houston, TX, USA.
J Clin Lipidol. 2019 Sep-Oct;13(5):797-803.e1. doi: 10.1016/j.jacl.2019.08.002. Epub 2019 Aug 9.
Accurate identification of patients with statin-associated side effects (SASEs) is critical for health care systems to institute strategies to improve guideline-concordant statin use.
The objective of this study was to determine whether adverse drug reaction (ADR) entry by clinicians in the electronic medical record can accurately identify SASEs.
We identified 1,248,214 atherosclerotic cardiovascular disease (ASCVD) patients seeking care in the Department of Veterans Affairs. Using an ADR data repository, we identified SASEs in 15 major symptom categories. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were assessed using a chart review of 256 ASCVD patients with identified SASEs, who were not on high-intensity statin therapy.
We identified 171,189 patients (13.71%) with documented SASEs over a 15-year period (9.9%, 2.7%, and 1.1% to 1, 2, or >2 statins, respectively). Statin use, high-intensity statin use, low-density lipoprotein cholesterol, and non-high-density lipoprotein cholesterol levels were 72%, 28.1%, 99 mg/dL, and 129 mg/dL among those with vs 81%, 31.1%, 84 mg/dL, and 111 mg/dL among those without SASEs. Progressively lower statin and high-intensity statin use, and higher low-density lipoprotein cholesterol and non-high-density lipoprotein cholesterol levels were noted among those with SASEs to 1, 2, or >2 statins. Two-thirds of SASEs were related to muscle symptoms. Sensitivity, specificity, PPV, NPV compared with manual chart review were 63.4%, 100%, 100%, and 85.3%, respectively.
A strategy of using ADR entry in the electronic medical record is feasible to identify SASEs with modest sensitivity and NPV but high specificity and PPV. Health care systems can use this strategy to identify ASCVD patients with SASEs and operationalize efforts to improve guideline-concordant lipid-lowering therapy use in such patients. The sensitivity of this approach can be further enhanced by the use of unstructured text data.
准确识别他汀类药物相关副作用（SASEs）对于医疗保健系统制定策略以改善指南一致的他汀类药物使用至关重要。
本研究旨在确定临床医生在电子病历中录入的药物不良反应（ADR）是否能准确识别 SASEs。
我们在退伍军人事务部的 1248214 例动脉粥样硬化性心血管疾病（ASCVD）患者中进行了识别。使用 ADR 数据存储库，我们在 15 个主要症状类别中确定了 SASEs。通过对 256 例已识别出 SASEs 但未接受高强度他汀类药物治疗的 ASCVD 患者进行图表回顾，评估了敏感性、特异性、阳性预测值（PPV）和阴性预测值（NPV）。
在 15 年期间，我们共识别出 171189 例（13.71%）有记录的 SASEs 患者（分别为 9.9%、2.7%和 1.1%至 1、2 或>2 种他汀类药物）。与无 SASEs 的患者相比，有 SASEs 的患者的他汀类药物使用、高强度他汀类药物使用、低密度脂蛋白胆固醇和非高密度脂蛋白胆固醇水平分别为 72%、28.1%、99mg/dL 和 129mg/dL；而无 SASEs 的患者分别为 81%、31.1%、84mg/dL 和 111mg/dL。在 SASEs 患者中，随着他汀类药物和高强度他汀类药物的使用逐渐减少，低密度脂蛋白胆固醇和非高密度脂蛋白胆固醇水平逐渐升高，分别达到 1、2 或>2 种。有 SASEs 的患者中，超过三分之二的 SASEs 与肌肉症状有关。与手动图表审查相比，ADR 录入策略的敏感性、特异性、PPV 和 NPV 分别为 63.4%、100%、100%和 85.3%。
使用电子病历中的 ADR 录入策略来识别 SASEs 是可行的，该策略具有中等敏感性和 NPV，但特异性和 PPV 较高。医疗保健系统可以使用该策略识别 ASCVD 患者中的 SASEs，并实施改善此类患者指南一致的降脂治疗使用的工作。通过使用非结构化文本数据，这种方法的敏感性可以进一步提高。
