OPTIMIZING ANTIBIOTIC USE IN LONG-TERM CARE

拟议研究的主要目标是确定 治疗老年人尿路感染的临床方法 长期护理设施（LTCF）中的成年人可以减少整体 在LTCF中使用抗生素。 三个次要目标是：1）证明 实施循证诊疗临床的可行性 LTCF中的算法，2）评估减少 目标人群中UTI的诊断测试和抗生素使用，3） 评估LTCF中采用所提出的算法的过程。 减少 在LTCF中使用抗生素将降低1） 抗生素耐药性的发展，2）药物不良反应的可能性 影响和有害的药物相互作用，3）与 抗生素使用不当。 为了实现研究目标， 对照试验，参与的LTCF随机接受任一干预 （临床算法）或对照组。 循证 开发了诊断和治疗算法，并增加了反馈 来自在住宅LTCF工作的初级保健医生和护士。 的 研究将采用定量和定性相结合的方法来评估 实施临床算法的过程和结果。 一项随机 将使用匹配对设计，在12对LTCF中的每一对内， 一人将被随机分配到干预组（临床算法）。 另 一半将提供常规的管理假定尿路感染。 定量结果将包括以下内容：1） 为泌尿系适应症开的抗生素疗程，2） 抗生素使用疗程，3）尿培养率，4） 泌尿道感染的住院率，和5）死亡率。 在研究的头两个月，该算法将进行试点测试 在干预之家。 通过前瞻性案例研究评价 健康服务干预（诊断和治疗算法 关于LTCF居民中UTI的抗生素使用）将检查 易于实施，医疗保健提供者对诊断的满意度 和治疗算法。 使用标准抽样，两组受访者 将接受采访，参与LTCF的主要临床管理人员 （医务主任、护理主任、感染控制干事）和 护理人员谁将实现算法。

The primary objective of the proposed study is to determine if a clinical algorithm for managing urinary tract infections (UTIs) in older adults in residential long-term care facilities (LTCFs) can reduce the overall use of antibiotics in LTCFs. Three secondary aims are 1) to demonstrate the feasibility of implementing evidence-based diagnostic and therapeutic clinical algorithms in LTCFs, 2) to assess the safety of reducing the number of diagnostic tests and antibiotic use for UTIs in the target population, 3) to evaluate the process of adopting the proposed algorithms in LTCFs. Reducing the use of antibiotics in LTCFs will reduce 1) the potential for the development of antibiotic resistance, 2) the potential for adverse drug effects and harmful drug interactions, 3) significant costs associated with inappropriate use of antibiotics. To achieve the research goals, a randomized controlled trial with participating LTCFs randomized to either intervention (clinical algorithm) or control group will be conducted. An evidence-based diagnostic and a treatment algorithm were developed, augmented with feedback from primary care physicians and nurses working in residential LTCFs. The study will use a combined quantitative and qualitative approach to evaluate the process and outcomes of implementing the clinical algorithm. A randomized matched pair design will be used where, within each of the 12 pairs of LTCFs, one will be randomized to the intervention (clinical algorithm). The other half will provide usual management of presumptive urinary tract infections. Quantitative outcomes will include the following: 1) the proportion of antibiotic courses prescribed for urinary indications, 2) the total number of courses of antibiotics used, 3) rates of urine cultures ordered, 4) hospitalization rates for urinary tract infections, and 5) mortality rates. During the first two months of the study, the algorithm will be pilot tested in the intervention homes. Adoption of the prospective case study evaluation of a health service intervention (diagnostic and treatment algorithms concerning antibiotic use for UTIs in residents of LTCFs) will examine the ease of implementation and healthcare provider satisfaction with diagnostic and treatment algorithms. Using criterion sampling, two groups of respondents will be interviewed, key clinical administrators in the participating LTCFs (medical directors, directors of nursing, infection control officers) and nursing staff who will implement the algorithms.