Reducing Antimicrobial Overuse in HCAP Through Personalized Antimicrobial Recommendations

 描述（由申请人提供）：肺炎是住院和死亡的主要原因。抗生素是治疗的主要手段，但引起肺炎的细菌中抗生素耐药性的增加威胁着我们治疗这种疾病的能力。在与医疗保健系统接触后发生肺炎的患者被指定为患有医疗保健相关性肺炎（HCAP），并且具有对常用抗生素具有耐药性的细菌的风险增加。当这些患者发生肺炎时，目前的指南建议同时使用3种不同的抗生素进行治疗，以确保对耐药微生物进行充分治疗。然而，这种广泛的治疗可能会伤害患者，无论是通过直接毒性（如肾损伤）或通过与其他细菌（如C。艰难梭菌感染，可导致危及生命的腹泻）。广泛 使用不必要的抗生素也会增加耐药微生物的流行，使更多的病人处于危险之中。在照顾HCAP患者时，美国医生面临着几个挑战。首先，仅仅因为患者暴露于医疗保健系统并不意味着患者具有耐药性感染。事实上，大多数HCAP患者接受标准治疗会更好。然而，医生没有办法准确地确定个体患者的耐药感染风险。第二，即使他们知道病人有耐药感染的高风险，他们也不知道哪种抗生素会耐药，直到培养出来，这通常需要几天时间。该提案的目的是使用来自全国大样本患者的数据来创建工具，医生可以使用这些工具来评估个体患者发生耐药感染的风险并选择适当的抗生素。一个经验丰富的团队将开发和测试这些工具，然后将它们以智能订单集的形式整合到广泛使用的商业电子健康记录（EHR）中，从而提供个性化的抗生素建议。然后，我们将在一项随机试验中评估顺序集对医生行为和患者结局的影响。检查嵌入在EHR中的电子决策辅助的有效性将测试智能订单集是否可以通过将患者特定因素纳入这个复杂的决策过程来安全地减少抗生素过度使用。该提案建立在我们跨学科团队创建风险评估工具并将其纳入EHR的坚实基础之上。获得的知识将为每年数十万患者的HCAP治疗提供最佳实践。

 DESCRIPTION (provided by applicant): Pneumonia is a leading cause of hospitalization and death. Antibiotics are the mainstay of treatment, but increasing antibiotic resistance among the bacteria that cause pneumonia threatens our ability to treat this disease. Patients who develop pneumonia after contact with the healthcare system are designated as having healthcare-associated pneumonia (HCAP), and are at increased risk for harboring bacteria that are resistant to the usual antibiotics. When such patients develop pneumonia, current guidelines recommend they be treated with 3 different antibiotics simultaneously to ensure adequate treatment for resistant organisms. However, such broad treatment can harm patients, either through direct toxicity (e.g. kidney damage) or through the development of superinfections with other bacteria (e.g. C. difficile infection, which can cause life-threatening diarrhea). Widespread use of unnecessary antibiotics can also increase the prevalence of resistant organisms, putting additional patients at risk. In caring for patients with HCAP, US physicians face several challenges. First, just because a patient was exposed to the healthcare system does not mean that the patient has a resistant infection. In fact, most patients with HCAP would be better off with standard therapy. However, physicians do not have a way of accurately determining an individual patient's risk for a resistant infection. Second, even if they knew the patient was at high risk for having a resistant infection, they do not know which antibiotic it will be resistant o until cultures are available, which usually takes several days. The aim of this proposal is to use data from a large national sample of patients to create tools that physicians can use to assess an individual patient's risk of having a resistant infection and to choose the appropriate antibiotic. An experienced team will develop and test these tools, and then incorporate them into a widely-used commercially available electronic health record (EHR) in the form of a smart order set that will make a personalized antibiotic recommendation. We will then assess the effects of the order set on physician behavior and patient outcomes in a randomized trial. Examining the effectiveness of an electronic decision aid embedded in an EHR will test whether a smart order set can safely reduce antibiotic overuse by incorporating patient-specific factors into this complex decision process. This proposal builds upon our inter-disciplinary team's strong foundation of creating risk assessment tools and incorporating them into the EHR. Knowledge to be gained will inform best practices for HCAP treatment for hundreds of thousands of patients each year.