Demonstration of Near Zero Antibiotic Prescribing for Acute Bronchitis

描述（由申请人提供）：背景：研究表明，指南指出，性能指标断言，无并发症的急性支气管炎的抗菌药物处方是不合适的。然而，在美国，每年2250万急性支气管炎患者中，临床医生处方抗菌药物的比例超过60%。以前成功的干预措施虽然在流行病学上严格，但仅将抗菌药物处方率降低到40%或50%。目前尚不清楚在实际操作中，急性支气管炎的抗菌药物处方率是否可以接近于零，同时保持患者的安全性和满意度。研究计划：该项目的具体目标1是开发一种EHR集成算法，用于诊断和治疗成人急性支气管炎，目标是将抗菌药物处方率降至接近零。具体目标2是在一个大型的、多样化的初级保健实践中，对急性支气管炎进行受控的、持续监测的EHR集成诊断和治疗算法的实施。我们将使用多模式实施-包括计算机化的决策支持，报告工具和临床医生反馈-和质量改进技术，以确保遵守算法并将抗菌药物处方率降至接近零。主要结果是急性支气管炎患者的抗菌药物处方率。次要结局包括患者症状、患者满意度、患者安全性和医疗费用。为了确保算法和干预措施在未来的有效传播，一个主要的结果是捕获和描述对抗菌药物处方率影响最大的成分。具体目标2a是开发EHR独立版本的算法和实现方法，用于没有EHR的诊所。具体目标3是在11个诊所的基于初级保健实践的研究网络中传播算法和实施方法，并将急性支气管炎的抗菌药物处方率降低到接近零。未来的方向和影响：在未来，我们计划广泛传播，并继续测试EHR依赖和EHR独立版本的算法和实现方法的有效性和安全性。开发、证明和广泛传播一种有效的算法，将急性支气管炎的抗菌药物处方减少到接近零的比例，有可能减少美国的药物不良事件、医疗保健成本和抗菌药物耐药菌的流行。该项目还将研究各种工具的有效性，以改变门诊实践，可以推广到其他临床条件。 公共卫生相关性：抗生素对急性支气管炎患者没有帮助，但在2250万次急性支气管炎就诊中，医生处方抗生素的比例超过60%，而此前的努力仅将抗生素处方率降至约40%。我们建议开发和测试急性支气管炎的诊断和治疗算法，将抗生素处方率降低到接近零，确保这对患者是安全的。通过开发、测试和传播这样一种算法，我们希望降低医疗成本、药物不良反应和耐药性细菌的流行。

DESCRIPTION (provided by applicant): Background: Studies show, guidelines state, and performance measures assert that antimicrobial prescribing for uncomplicated acute bronchitis is inappropriate. However, clinicians prescribe antimicrobials in over 60% of the 22.5 million acute bronchitis visits in the United States each year. Previous successful interventions, while epidemiologically rigorous, have only reduced the antimicrobial prescribing rate to 40% or 50%. It is unknown if the antimicrobial prescribing rate for acute bronchitis can be brought to near zero percent in actual practice while maintaining patient safety and satisfaction. Research Plan: Specific Aim 1 of this project is to develop an EHR-integrated algorithm for the diagnosis and treatment of adults with acute bronchitis with a goal of reducing the antimicrobial prescribing rate to near zero percent. Specific Aim 2 is to perform a controlled, continuously-monitored, implementation of an EHR-integrated diagnosis and treatment algorithm for acute bronchitis in a large, diverse primary care practice. We would use a multi-modal implementation - including computerized decision support, reporting tools, and clinician feedback - and quality improvement techniques to ensure adherence to the algorithm and reduce the antimicrobial prescribing rate to near zero percent. The primary outcome would be the antimicrobial prescribing rate for patients with acute bronchitis. Secondary outcomes would include patient symptoms, patient satisfaction, patient safety, and healthcare costs. To ensure the effective future dissemination of the algorithm and intervention, a major outcome would be the capture and description of the components that had the greatest effect on the antimicrobial prescribing rate. Specific Aim 2a is to develop an EHR-independent version of the algorithm and implementation method for use in clinics that do not have EHRs. Specific Aim 3 is to disseminate the algorithm and implementation method throughout an 11-clinic Primary Care Practice-Based Research Network and reduce the antimicrobial prescribing rate for acute bronchitis to near zero percent. Future Directions and Implications: In the future, we plan to broadly disseminate and continue to test the effectiveness and safety of the EHR-dependent and EHR-independent versions of the algorithm and implementation method. Development, demonstration, and broad dissemination of an effective algorithm to reduce antimicrobial prescribing to near zero percent for acute bronchitis has the potential to decrease adverse drug events, healthcare costs, and the prevalence of antimicrobial resistant bacteria in the United states. This project will also examine the effectiveness of a variety of tools for changing ambulatory practice that can generalize to other clinical conditions. PUBLIC HEALTH RELEVANCE: Antibiotics do not help patients with acute bronchitis, but doctors prescribe antibiotics in over 60% of the 22.5 million visits for acute bronchitis and previous efforts have only reduced the antibiotic prescribing rate to about 40%. We propose to develop and test a diagnosis and treatment algorithm for acute bronchitis that would reduce the antibiotic prescribing rate to near zero percent, making sure this is safe for patients. By developing, testing, and disseminating such an algorithm, we hope to decrease healthcare costs, adverse drug reactions, and the prevalence of antibiotic-resistant bacteria.