Taylor Stephanie Parks, Weissman Gary E, Kowalkowski Marc, Admon Andrew J, Skewes Sable, Xia Yunfei, Chou Shih-Hsuing
Department of Internal Medicine, Wake Forest University School of Medicine, Atrium Health, Charlotte NC, USA.
Critical Illness Injury and Recovery Research Center, Wake Forest School of Medicine, Charlotte NC, USA.
Med Decis Making. 2023 Feb;43(2):175-182. doi: 10.1177/0272989X221121279. Epub 2022 Sep 5.
Clinicians' decision thresholds for initiating antibiotics in patients with suspected sepsis have not been quantified. We aimed to define an average threshold of infection likelihood at which clinicians initiate antibiotics when treating a patient with suspected infection and to evaluate the influence of severity of illness and clinician-related factors on the threshold.
This was a prospective survey of 153 clinicians responding to 8 clinical vignettes constructed from real-world data from 3 health care systems in the United States. We treated each hour in the vignette as a decision to treat or not treat with antibiotics and assigned an infection probability to each hour using a previously developed infection prediction model. We then estimated decision thresholds using regression models based on the timing of antibiotic initiation. We compared thresholds across categories of severity of illness and clinician-related factors.
Overall, the treatment threshold occurred at a 69% probability of infection, but the threshold varied significantly across severity of illness categories-when patients had high severity of illness, the treatment threshold occurred at a 55% probability of infection; when patients had intermediate severity, the threshold for antibiotic initiation occurred at an infection probability of 69%, and the threshold was 84% when patients had low severity of illness ( < 0.001 for group differences). Thresholds differed significantly across specialty, highest among infectious disease and lowest among emergency medicine clinicians and across years of experience, decreasing with increasing years of experience.
The threshold infection probability above which physicians choose to initiate antibiotics in suspected sepsis depends on illness severity as well as clinician factors.
Incorporating these context-dependent thresholds into discriminating and well-calibrated models will inform the development of future sepsis clinical decision support systems. Clinician-related differences in treatment thresholds suggests potential unwarranted variation and opportunities for performance improvement.
Decision making about antibiotic initiation in suspected sepsis occurs under uncertainty, and little is known about clinicians' thresholds for treatment.In this prospective study, 153 clinicians from 3 health care systems reviewed 8 real-world clinical vignettes representing patients with sepsis and indicated the time that they would initiate antibiotics.Using a model-based approach, we estimated decision thresholds and found that thresholds differed significantly across illness severity categories and by clinician specialty and years of experience.
临床医生对疑似脓毒症患者启动抗生素治疗的决策阈值尚未得到量化。我们旨在确定临床医生在治疗疑似感染患者时启动抗生素的平均感染可能性阈值，并评估疾病严重程度和临床医生相关因素对该阈值的影响。
这是一项对153名临床医生进行的前瞻性调查，他们对根据美国3个医疗系统的真实数据构建的8个临床病例进行了回应。我们将病例中的每一小时视为是否使用抗生素治疗的决策，并使用先前开发的感染预测模型为每一小时分配感染概率。然后，我们根据抗生素启动的时间，使用回归模型估计决策阈值。我们比较了不同疾病严重程度类别和临床医生相关因素的阈值。
总体而言，治疗阈值出现在感染概率为69%时，但该阈值在不同疾病严重程度类别中差异显著——当患者疾病严重程度高时，治疗阈值出现在感染概率为55%时；当患者疾病严重程度为中等时,抗生素启动阈值出现在感染概率为69%时，而当患者疾病严重程度低时（<0.001组间差异），阈值为84%。阈值在不同专业之间差异显著，在传染病专业中最高，在急诊医学临床医生中最低，并且在不同的经验年限中也有差异，随着经验年限的增加而降低。
医生在疑似脓毒症中选择启动抗生素治疗的阈值感染概率取决于疾病严重程度以及临床医生因素。
将这些依赖于上下文的阈值纳入有区分度且校准良好的模型中，将为未来脓毒症临床决策支持系统的开发提供信息。临床医生在治疗阈值上的差异表明存在潜在的不必要的差异以及性能改进的机会。
关于疑似脓毒症中抗生素启动的决策是在不确定的情况下做出的，而且对于临床医生的治疗阈值知之甚少。在这项前瞻性研究中，来自3个医疗系统的153名临床医生审查了8个代表脓毒症患者的真实世界临床病例，并指出了他们将启动抗生素治疗的时间。使用基于模型的方法，我们估计了决策阈值，发现阈值在不同疾病严重程度类别以及临床医生专业和经验年限方面存在显著差异。
