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首页> 外文期刊>The Canadian Journal of Neurological Sciences: le Journal Canadien des Sciences Neurologiques >Diagnostic Accuracy of Transient Ischemic Attack from Physician Claims
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Diagnostic Accuracy of Transient Ischemic Attack from Physician Claims

机译：医师索赔的瞬态缺血攻击诊断准确性

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摘要

Background: Hospitalization data underestimate the occurrence of transient ischemic attack (TIA). As TIA is frequently diagnosed in primary care, methodologies for the accurate ascertainment of a TIA from physician claims data are required for surveillance and health systems planning in this population. The present study evaluated the diagnostic accuracy of multiple algorithms for TIA from a longitudinal population-based physician billing database. Methods: Population-based administrative data from the province of British Columbia were used to identify the base population (1992-2007; N = 102,492). Using discharge records for hospital admissions for acute ischemic stroke with a recent (< 90 days) TIA as the reference standard, we performed receiver-operating characteristic analyses to calculate sensitivity, specificity, positive and negative predictive values and overall accuracy, and to compare area under the curve for each physician billing algorithm. To evaluate the impact of different case definitions on population-based TIA burden, we also estimated the annual TIA occurrence associated with each algorithm. Results: Physician billing algorithms showed low to moderate sensitivity, with the algorithm for two consecutive physician visits within 90 days showing the highest sensitivity at 37.7% (CI95% = 37.4-38.1). All algorithms demonstrated high specificity and moderate to high overall accuracy, resulting in low positive predictive values (<= 5%), low discriminability (0.53-0.57) and high false positive rates (1 - specificity). Population-based estimates of TIA occurrence were comparable to prior studies and declined over time. Conclusions: Physician billing data have insufficient sensitivity to identify TIAs but may be used in combination with hospital discharge data to improve the accuracy of estimating the population-based occurrence of TIAs.
机译：背景：住院数据低估了瞬时缺血攻击（TIA）的发生。由于TIA经常被诊断为初级保健，从医生声称数据准确确定TIA的方法是本人的监督和卫生系统规划所必需的。本研究评估了从纵向群体的医疗账单数据库中对TIA的多种算法的诊断准确性。方法：来自英国哥伦比亚省的基于人口的行政数据，用于识别基础人群（1992-2007; n = 102,492）。使用近期（<90天）TIA作为参考标准的急性缺血性卒中的出院记录，我们执行了接收器操作特征分析，以计算灵敏度，特异性，正负预测值和整体准确性，并比较区域在每个医生计费算法的曲线下。为了评估不同案例定义对基于人口的TIA负担的影响，我们还估计与每种算法相关的年度TIA发生。结果：医师计费算法显示出低于中等灵敏度，算法在90天内进行两次连续的医生访问，显示出37.7％的最高敏感性（CI95％= 37.4-38.1）。所有算法都表现出高的特异性和中度至高总体精度，导致低阳性预测值（<= 5％），低分辨率（0.53-0.57）和高误率（1特异性）。基于人口的TIA估计发生与先前的研究相当并随着时间的推移下降。结论：医师计费数据的敏感性不足以识别TIA，但可以与医院放电数据结合使用，以提高估算基于人口的蒂亚斯的替代的准确性。

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