From the Departments of Epidemiology.
Sex Transm Dis. 2018 Oct;45(10):696-702. doi: 10.1097/OLQ.0000000000000854.
The ideal approach to triaging sexually transmitted disease (STD) clinic patients between testing-only express visits and standard visits with clinician evaluation is uncertain.
In this cross-sectional study, we used classification and regression tree analysis to develop and validate the optimal algorithm for predicting which patients need a standard visit with clinician assessment (i.e., to maximize correct triage). Using electronic medical record data, we defined patients as needing a standard visit if they reported STD symptoms, received any empiric treatment, or were diagnosed as having an infection or syndrome at the same visit. We considered 11 potential predictors for requiring medical evaluation collected via computer-assisted self-interview when constructing the optimized algorithm. We compared test characteristics of the optimized algorithm, the Public Health-Seattle and King County STD Clinic's current 13-component algorithm, and a simple 2-component algorithm including only presence of symptoms and contact to STD.
From October 2010 to June 2015, 18,653 unique patients completed a computer-assisted self-interview. In the validation samples, the optimized, current, and simple algorithms appropriately triaged 90%, 85%, and 89% of patients, respectively. The optimized algorithm had lower sensitivity for identifying patients needing standard visits (men, 94%; women, 93%) compared with the current algorithm (men, 95%; women, 98%), as did the simple algorithm (men, 91%; women, 93%). The optimized, current, and simple algorithms triaged 31%, 23%, and 33% of patients to express visits, respectively.
The overall performance of the statistically optimized algorithm did not differ meaningfully from a simple 2-component algorithm. In contrast, the current algorithm had the highest sensitivity but lowest overall performance.
对性病（STD）诊所患者进行分类，将仅检测的快速就诊和有临床医生评估的标准就诊区分开来，理想方法仍不确定。
在这项横断面研究中，我们使用分类和回归树分析来制定和验证预测哪些患者需要临床医生评估的标准就诊（即最大程度正确分诊）的最佳算法。使用电子病历数据，如果患者报告 STD 症状、接受任何经验性治疗或在同一就诊时被诊断为感染或综合征，则将其定义为需要标准就诊。在构建优化算法时，我们考虑了通过计算机辅助自访谈收集的 11 种可能的预测因素。我们比较了优化算法、西雅图和金县公共卫生 STD 诊所当前的 13 个组成部分算法以及仅包括症状和接触 STD 的简单 2 个组成部分算法的测试特征。
2010 年 10 月至 2015 年 6 月，共有 18653 名患者完成了计算机辅助自访谈。在验证样本中，优化、当前和简单算法分别适当分诊了 90%、85%和 89%的患者。与当前算法相比（男性 95%，女性 98%），优化算法识别需要标准就诊的患者的敏感性较低（男性 94%，女性 93%），简单算法也是如此（男性 91%，女性 93%）。优化、当前和简单算法分别将 31%、23%和 33%的患者分诊至快速就诊。
统计学优化算法的整体性能与简单的 2 个组成部分算法没有显著差异。相比之下，当前算法的敏感性最高，但整体性能最低。
