Development, Implementation and Evaluation of Novel Strategies to Reduce Inapprop

描述(由申请人提供)：常见细菌中抗生素耐药性的迅速上升正在对社区获得性感染的临床病程和卫生保健费用产生不利影响。由于抗生素耐药模式与抗生素使用模式密切相关，多个组织已宣布减少不必要的抗生素使用是抗击抗生素耐药性努力的关键组成部分。在人类中，绝大多数不必要的抗生素处方都用于治疗具有病毒病原学的急性呼吸道感染(ARI)。特别是，尽管许多对照试验表明抗生素治疗对急性支气管炎患者没有好处，但大多数被诊断为急性支气管炎的患者继续在不同的治疗环境中接受抗生素治疗。最近，国家质量保证委员会采用了在HEDIS数据集中没有开抗生素作为质量衡量标准的成人就诊比例，诊断为急性支气管炎。HEDIS数据集的最新结果强调，急性支气管炎患者的抗生素处方率仍然很高。在治疗下呼吸道感染患者(如急性支气管炎)中过度使用抗生素的一个关键因素是诊断的不确定性和对此类患者潜在肺炎的不准确风险估计。最近，我们的研究小组观察到，在将诊断和治疗算法纳入急性护理环境后，抗生素处方大幅减少。这种急性咳嗽管理算法结合了有关生命体征和症状的数据，将社区获得性肺炎患者与其他急性咳嗽疾病患者，特别是急性支气管炎患者区分开来。近年来，由于引入了强调对社区获得性肺炎患者及时使用抗生素的质量措施，急性咳嗽管理算法变得更加有价值。因此，这种算法有效性的强有力的经验证据可能会导致该算法的广泛采用和抗生素处方的实质性改进。调查小组提议与大型综合健康网络盖辛格健康系统建立独特的合作伙伴关系，以实施和评估该算法。利用33个实践站点的整群随机试验设计，我们将解决以下目标：1)与使用两种不同实施策略(一个基于海报和一个基于电子健康记录)的常规护理站点相比，通过合并算法来衡量抗生素处方的减少；2)测量与算法实施相关的复诊、延迟住院和净经济成本；以及3)评估影响干预站点实施水平和最终绩效成功的当地实践特征。在这项研究的最后一部分，调查人员将与NCQA合作，通过参与计划的全国网络传播研究结果，并推动算法和质量改进方法的广泛采用。

DESCRIPTION (provided by applicant): The rapid rise in antibiotic resistance among common bacteria is adversely affecting the clinical course and health care costs of community-acquired infections. Because antibiotic resistance patterns are strongly correlated with antibiotic use patterns, multiple organizations have declared reductions in unnecessary antibiotic use to be critical components of efforts to combat antibiotic resistance. Among humans, the vast majority of unnecessary antibiotic prescriptions are used to treat acute respiratory tract infections (ARIs) that have a viral etiology. In particular, despite the fact that numerous controlled trials have demonstrated no benefit of antibiotic therapy for patients with acute bronchitis, the majority of patients diagnosed with acute bronchitis continue to receive antibiotic therapy across diverse treatment settings. Recently, the National Committee on Quality Assurance adopted the proportion of adult visits diagnosed as acute bronchitis when an antibiotic was NOT prescribed as a quality measure within the HEDIS data set. Recent results from the HEDIS dataset emphasize the continued high rates of antibiotic prescribing for patients with acute bronchitis. One key factor driving overuse of antibiotics in the management of patients with lower respiratory tract infections-such as acute bronchitis-is diagnostic uncertainty and inaccurate risk estimation of underlying pneumonia in such patients. Recently, our study team has observed substantial reductions in antibiotic prescribing following the incorporation of a diagnostic and treatment algorithm into an acute care setting. This acute cough management algorithm incorporates data on vital signs and symptoms distinguishing patients with community- acquired pneumonia from other patients with acute cough illness, specifically those with acute bronchitis. The acute cough management algorithm has become even more valuable in recent years due to the introduction of quality measures that emphasize the timely administration of antibiotics for patients with community-acquired pneumonia. Thus, strong empirical evidence of the effectiveness of such an algorithm could lead to wide adoption of the algorithm and substantial improvements in antibiotic prescribing. The investigative team is proposing a unique partnership with Geisinger Health System, a large integrated health network, to implement and evaluate the algorithm. Utilizing a cluster-randomized trial design across 33 practice sites, we will address the following aims: 1) To measure the reduction in antibiotic prescribing resulting from incorporation of the algorithm compared to usual care sites utilizing two different implementation strategies, one poster-based and one electronic health record-based, 2) To measure revisits, delayed hospitalizations and net economic costs associated with algorithm implementation, and 3) To evaluate local practice characteristics influencing the level of implementation and ultimate performance success at intervention sites. In a final component of the study, the investigators will partner with NCQA to disseminate study results through the national network of participating plans and stimulate wide spread adoption of the algorithm and quality improvement methods.