Decreasing antibiotic prescribing in acute respiratory infections through implementation of nurse driven clinical decision support

通过实施护士驱动的临床决策支持，减少急性呼吸道感染的抗生素处方

• 批准号: 10337238
• 负责人: David Feldstein
• 金额: $ 75.28万
• 依托单位: NEW YORK UNIVERSITY SCHOOL OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-04-15 至 2024-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10337238
• 关键词: Acute; Acute Disease; Acute respiratory infection; Adoption; Ambulatory Care; Antibiotic Resistance; Antibiotics; Bacterial Infections; Caring; Chronic Disease; Client satisfaction; Clinic; Clinical; Cluster randomized trial; Collaborations; Coughing; Data; Decision Aid; Diagnosis; Diagnostic tests; Electronic Health Record; Elements; Evaluation; Fatigue; Foundations; Funding; Goals; Health; Healthcare; Information Technology; Institution; Intervention; Laboratories; Lead; Licensing; Modeling; Morbidity - disease rate; National Institute of Allergy and Infectious Disease; New York; Nurses; Outcome; Patient Care; Patient risk; Patients; Pattern; Persons; Physical Examination; Physicians; Preventive; Primary Health Care; Proctor framework; Protocols documentation; Provider; Public Health; Recording of previous events; Registered nurse; Research; Resources; Risk; Sore Throat; Standardization; Technology; Telephone; Testing; Time; Training; Training Programs; Triage; Universities; Utah; Visit; Wisconsin; Work; base; care costs; clinical care; clinical decision support; cost; cost effectiveness; empowered; evidence base; health care quality; implementation evaluation; implementation framework; implementation outcomes; implementation tool; improved; innovation; intervention cost; novel; post implementation; risk stratification; success; support tools; theories; tool; uptake; urgent care

Project summary Overuse of antibiotics for acute respiratory infections (ARIs) continues to drive increasing antibiotic resistance. Provider-driven clinical decision support (CDS) has had a minimal impact on decreasing antibiotic prescribing rates. The overall objectives of this application are to 1) implement registered nurse (RN)-driven CDS containing integrated clinical prediction rules (iCPRs) [decision aids embedded into the electronic health record which determine risk of bacterial infection based on elements of the patient history and physical examination] and 2) determine the impact of RN-driven CDS on inappropriate antibiotic prescribing and resource use. The central hypothesis is that RNs using iCPR will accurately determine patients’ risk for bacterial ARI, recommend appropriate testing and treatment based on that risk and will have lower rates of inappropriate antibiotic prescribing compared to providers. The rationale for this project is that a CDS tool can allow RNs to work at the full scope of their licenses and decrease inappropriate antibiotic prescribing. This central hypothesis will be tested using three specific aims: 1) adapt and implement an RN driven iCPR tool for evaluation and treatment of patients with ARIs in primary care and urgent care practices; 2) determine the impact of the RN driven iCPR on antibiotic prescribing, diagnostic test-ordering, resource use patterns, and cost-effectiveness; and 3) use a theory-driven implementation framework to identify barriers and facilitators to, and optimize factors influencing, effective implementation of an RN-driven iCPR. For the first aim, the previously developed and studied provider iCPR will be adapted for RN workflow and a RN training program will be implemented to train RNs in its use for patient evaluation and treatment. For the second aim, a stepped wedge cluster randomized trial will be conducted at primary care and urgent care clinics at the four participating institutions. For the third aim, the Technology Acceptance Model (TAM3) and Proctor’s Framework will be used as guides to assess implementation outcomes and use findings to drive post-implementation tool optimization and create an implementation toolkit. The proposed project is innovative because it: 1) uses CDS tools with risk stratification to enable RNs to lead initial ARI assessment and treatment; 2) uses an evidence-based implementation framework to evaluate outcomes and identify barriers and facilitators; and 3) evaluates the cost of the intervention which is critical in increasing dissemination potential. The proposed research is significant because it is expected to provide a scalable implementation model leveraging CDS and RN training tools to decrease antibiotic overuse, lower the cost of care, and ultimately reduce antibiotic resistance.

项目摘要 过度使用抗生素治疗急性呼吸道感染（阿里斯）继续导致抗生素耐药性增加。 提供者驱动的临床决策支持（CDS）对减少抗生素处方的影响微乎其微 rates.本应用程序的总体目标是：1）实施注册护士（RN）驱动的CDS 包含集成临床预测规则（iCPR）[嵌入电子健康记录的决策辅助工具 根据患者病史和体格检查确定细菌感染风险] 和2）确定RN驱动的CDS对不适当的抗生素处方和资源使用的影响。的 中心假设是使用iCPR的RN将准确地确定患者的细菌性ARI风险，建议 根据这种风险进行适当的检测和治疗，并降低不适当抗生素的使用率 与供应商相比，该项目的基本原理是，CDS工具可以让RN在 全面的许可证范围并减少不适当的抗生素处方。这一核心假设将是 使用三个具体目标进行测试：1）调整并实施RN驱动的iCPR工具进行评估和治疗 初级保健和紧急护理实践中的阿里斯患者; 2）确定RN驱动的iCPR的影响 关于抗生素处方、诊断测试订购、资源使用模式和成本效益;以及3）使用 理论驱动的实施框架，以确定障碍和促进因素，并优化影响因素， 有效实施RN驱动的iCPR。对于第一个目标，先前开发和研究的提供者 iCPR将适用于注册护士的工作流程，并将实施注册护士培训计划，以培训注册护士使用该系统， 患者评估和治疗。对于第二个目标，将进行一项阶梯式楔形分组随机试验， 在四间参与机构的基层护理及紧急护理诊所进行。第三个目标， 技术接受模型（TAM 3）和普罗克特的框架将被用作评估 实施成果，并利用调查结果推动实施后工具的优化， 执行工具包。拟议的项目是创新的，因为它：1）使用CDS工具与风险分层 使RN能够领导ARI的初步评估和治疗; 2）使用循证实施 评估结果并确定障碍和促进因素的框架;以及3）评估 这对提高传播潜力至关重要。所提出的研究是有意义的 因为它预计将提供一个可扩展的实施模型，利用CDS和RN培训工具， 减少抗生素的过度使用，降低护理成本，并最终减少抗生素耐药性。