Invited Commentary The Electronic Health Record as Practice-Improvement Coach Unnecessary diagnostic imaging is a prevalent form of medical overuse, and leads to unnecessary invasive procedures, radiation exposure, emotional stress, and nosocomial infection. Research has focused on how to identify clinicians who are more likely to overuse diagnostic imaging and how to intervene. For example, studies have identified the number of magnetic resonance images (MRIs) that physicians ordered for uncomplicated low back pain1 and the number of antibiotic prescriptions for upper respiratory tract infections.2 In this issue of JAMA Internal Medicine, Chong and colleagues3 consider the overuse of computed tomographic pulmonary angiography (CTPA) in the diagnosis of pulmonary embolism. They report on the use of “diagnostic yield” (the number of positive studies/total number of studies ordered) as a metric to help identify overuse. Low diagnostic yield results from performing CTPA in patients at low risk of pulmonary embolism. Their study found marked variation in diagnostic yield between providers, with the absolute number of CTPAs ordered being more predictive of low diagnostic yield than physician characteristics such as age, specialty, and years of experience.3 These results are in accord with other research showing that a large number of CT scans are being performed in low-risk patients,4 and suggest that diagnostic imaging is being disproportionately ordered by a select group of clinicians. Chong et al3 make the case that low diagnostic yield can help identify physicians who may be ordering too many CTPAs in lowrisk patients. It is important to note, however, that a high diagnostic yield implies that a provider may only be ordering CTPA for the highest-risk patients, thus potentially missing the diagnosis of pulmonary embolism in some. Given that there are good estimates of the prevalence of pulmonary embolism in various clinical situations, as well as good data on the sensitivity and specificity of CTPE, an expected diagnostic yield could be calculated, and used as a standardized point of comparison.5,6 Even in situations where there is inadequate evidence to calculate an expected diagnostic yield, the mean diagnostic yield from a large group of physicians might suggest a reasonable starting point for analysis. What might this approach add to other implementation strategies for value-based care? One possibility is to use the electronic health record to develop real-time performance metrics, and then to use these metrics to target interventions based on the electronic record, such as decision support tools and peer comparisons toward individual clinicians. Electronic medical record platforms are sophisticated enough to keep a running calculation of a range of quality metrics per physician, such as dollars spent per diagnosis, and trends in the prescription of various analgesic classes over time. Such clinical data can then be used to provide personalized support to clinicians who are either outliers among their peers or whose metrics are far from the expected value. Such personalized approaches to feedback may be more impactful than more general low-value care alerts, such as the obligatory used of a decision support tool based on Wells’ risk-stratification criteria before ordering CTPA. They also may be more visible to clinicians than peer comparisons that are communicated through an online dashboard or email. Further, targeted interventions through the electronic health record could potentially reduce alert fatigue by decreasing the overall number of reminders for physicians. As a metric for appropriate use of imaging technologies, diagnostic yield has limits. The use of sensitive imaging modalities may result in high numbers of incidental findings that increase diagnosticyieldandthecostofcarewithoutaffectingclinicaloutcomes. This is the case with the use of carotid ultrasound in the initial work-up of syncope, an established form of medical overuse. In patients with uncomplicated musculoskeletal pain, imaging findings are often poorly correlated with clinical outcomes. Thus, the meaning of a high diagnostic yield would be unclear.7 Nonetheless, the study by Chong et al3 is thought provoking, and demonstrates how the electronic health record can be used as a performance coach to help physicians improve patient care.

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作为实践改进教练的电子健康记录

特邀评论 电子健康记录作为实践改进教练 不必要的诊断成像是医疗过度使用的一种普遍形式，并导致不必要的侵入性手术、辐射暴露、情绪压力和医院感染。研究的重点是如何识别更有可能过度使用诊断成像的临床医生以及如何进行干预。例如，研究已经确定了医生为无并发症的腰痛 1 订购的磁共振图像 (MRI) 的数量以及用于上呼吸道感染的抗生素处方的数量。 2 在本期 JAMA Internal Medicine 上，Chong 及其同事 3 考虑了过度使用计算机断层扫描肺血管造影（CTPA）在肺栓塞诊断中的应用。他们报告使用“诊断产量”（阳性研究的数量/订购的研究总数）作为帮助识别过度使用的指标。对肺栓塞风险低的患者进行 CTPA 导致诊断率低。他们的研究发现提供者之间的诊断率存在显着差异，与年龄、专业和经验年限等医生特征相比，订购 CTPA 的绝对数量更能预测低诊断率。3 这些结果与其他研究一致，表明正在对低风险患者进行大量 CT 扫描 4，这表明一组选定的临床医生不成比例地订购了诊断成像。Chong 等人 3 认为低诊断率可以帮助识别可能在低风险患者中订购过多 CTPA 的医生。然而，重要的是要注意，高诊断率意味着提供者可能只为风险最高的患者订购 CTPA，因此可能会遗漏某些肺栓塞的诊断。鉴于对各种临床情况下肺栓塞的患病率有很好的估计，以及关于 CTPE 敏感性和特异性的良好数据，可以计算出预期的诊断率，并将其用作标准化的比较点。 5,6即使在没有足够证据来计算预期诊断率的情况下，来自一大群医生的平均诊断率也可能为分析提供一个合理的起点。这种方法可以为基于价值的护理的其他实施策略增加什么？一种可能性是使用电子健康记录来开发实时绩效指标，然后使用这些指标根据电子记录来针对干预措施，例如决策支持工具和与个别临床医生的同行比较。电子病历平台足够复杂，可以持续计算每位医生的一系列质量指标，例如每次诊断花费的美元，以及各种镇痛药处方随时间的趋势。然后可以使用此类临床数据为临床医生提供个性化支持，这些医生要么是同行中的异常值，要么是其指标与预期值相差甚远。这种个性化的反馈方法可能比更一般的低价值护理警报更有影响力，例如在订购 CTPA 之前必须使用基于 Wells 的风险分层标准的决策支持工具。与通过在线仪表板或电子邮件传达的同行比较相比，它们对临床医生来说也可能更明显。此外，通过电子健康记录进行的有针对性的干预可以通过减少医生提醒的总数来潜在地减少警报疲劳。作为适当使用成像技术的衡量标准，诊断率是有限的。使用敏感的成像方式可能会导致大量的偶然发现，从而在不影响临床结果的情况下增加诊断率和护理成本。在晕厥的初始检查中使用颈动脉超声就是这种情况，晕厥是一种既定的医疗过度使用形式。在无并发症的肌肉骨骼疼痛患者中，影像学结果通常与临床结果的相关性较差。因此，高诊断率的含义尚不清楚。7 尽管如此，Chong 等人 3 的研究发人深省，并展示了如何将电子健康记录用作绩效指导以帮助医生改善患者护理。