New Garrett P, Nazir Arif, Logan Penny, Kistler Christine E
Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC 27599, USA.
SHC Medical Partners, 12201 Bluegrass Pkwy, Louisville, KY 40299, USA.
Antibiotics (Basel). 2022 Sep 20;11(10):1276. doi: 10.3390/antibiotics11101276.
Urinary tract infections (UTIs) are commonly suspected in nursing home (NH) residents, commonly resulting in antimicrobial prescriptions, even when symptoms are non-specific. To improve the diagnosis and management of suspected UTIs in NH residents, we conducted a pilot test of a paper-based clinical algorithm across NHs in the southern U.S. with ten advanced practice providers (APPs). The paper-based algorithm was modified based on the clinical care needs of our APPs and included antimicrobial treatment recommendations. The APPs found the UTI antimicrobial stewardship and clinical decision support acceptable. The educational sessions and algorithm improved baseline confidence toward UTI diagnosing and treatment. The APPs thought the algorithm was useful and did not negatively impact workload. Feedback from the pilot study will be used to improve the next iteration of the algorithm as we assess its impact on prescribing outcomes.
疗养院(NH)的居民常被怀疑患有尿路感染(UTI),即使症状不具特异性,这通常也会导致抗菌药物的处方开具。为改善疗养院居民疑似尿路感染的诊断和管理,我们在美国南部的多家疗养院与十位高级执业提供者(APP)对一种纸质临床算法进行了试点测试。该纸质算法根据我们的APP的临床护理需求进行了修改,并包括抗菌治疗建议。APP们认为尿路感染抗菌药物管理和临床决策支持是可以接受的。教育课程和算法提高了对尿路感染诊断和治疗的基线信心。APP们认为该算法有用,且不会对工作量产生负面影响。在我们评估其对处方结果的影响时,试点研究的反馈将用于改进该算法的下一版本。