{"doi":"10.1017/ash.2024.437","title":"Effect of automated identification of antimicrobial stewardship opportunities for suspected urinary tract infections","abstract":"Abstract Objective: We aimed to determine whether automated identification of antibiotic targeting suspected urinary tract infection (UTI) shortened the time to antimicrobial stewardship (AS) intervention. Design: Retrospective before-and-after study. Setting: Tertiary and quaternary care academic medical center. Patients: Emergency department (ED) or admitted adult patients meeting best practice alert (BPA) criteria during pre- and post-BPA periods. Methods: We developed a BPA to alert AS pharmacists of potential ASB triggered by the following criteria: ED or admitted status, antibiotic order with genitourinary indication, and a preceding urinalysis with ≤ 10 WBC/hpf. We evaluated the median time from antibiotic order to AS intervention and overall percent of UTI-related interventions among patients in pre-BPA (01/2020–12/2020) and post-BPA (04/15/2021–04/30/2022) periods. Results: 774 antibiotic orders met inclusion criteria: 355 in the pre- and 419 in the post-BPA group. 43 (35 UTI-related) pre-BPA and 117 (94 UTI-related) post-BPA interventions were documented. The median time to intervention was 28 hours (IQR 18–65) in the pre-BPA group compared to 16 hours (IQR 2–34) in the post-BPA group ( P < 0.01). Despite absent pyuria, there were six cases with gram-negative bacteremia presumably from a urinary source. Conclusions: Automated identification of antibiotics targeting UTI without pyuria on urinalysis reduced the time to stewardship intervention and increased the rate of UTI-specific interventions. Clinical decision support aided in the efficiency of AS review and syndrome-targeted impact, but cases still required AS clinical review.","journal":"Antimicrobial Stewardship & Healthcare Epidemiology","year":2024,"id":504161,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9567,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2024-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":497673,"name":"Rebekah W. Moehring","orcid":"0000-0001-7741-6029","position":1,"is_corresponding":false},{"id":3909,"name":"Nicholas A. Turner","orcid":"0000-0003-0650-4894","position":2,"is_corresponding":false},{"id":1354318,"name":"Justin Spivey","orcid":"0000-0002-4349-8932","position":3,"is_corresponding":false},{"id":698182,"name":"Sonali D. Advani","orcid":"0000-0001-5162-6482","position":4,"is_corresponding":false},{"id":3916,"name":"Rebekah Wrenn","orcid":"0000-0002-3394-3633","position":5,"is_corresponding":false},{"id":929022,"name":"Michael E Yarrington","orcid":"0000-0003-3186-1519","position":6,"is_corresponding":false},{"id":1266998,"name":"Connor R Deri","orcid":"0000-0002-9626-1197","position":0,"is_corresponding":true}],"reference_count":24,"raw_metadata":null,"created_at":"2026-07-19T02:10:35.597333Z","pmid":"39371441","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}