Antoinette Marie Acbo, Naida Koura-Mola, Terrence McSweeney, Hongkai Bao, Mei Chang, Kelsie Cowman, Priya Nori, Yi Guo
{"title":"愈合鞋底:微生物驱动的电子健康记录算法和顺序设置,以减少糖尿病足感染的抗假单孢菌使用,回顾性,观察性,准实验研究。","authors":"Antoinette Marie Acbo, Naida Koura-Mola, Terrence McSweeney, Hongkai Bao, Mei Chang, Kelsie Cowman, Priya Nori, Yi Guo","doi":"10.1017/ash.2025.59","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Antipseudomonal antibiotics are commonly prescribed for diabetic foot infections (DFI) at our institution despite a low local prevalence of <i>Pseudomonas aeruginosa</i>. A multidisciplinary team implemented a DFI electronic health record (EHR)-embedded treatment algorithm and order set.</p><p><strong>Methods: </strong>This multi-center, quasi-experimental study evaluated adults on antibiotics admitted for DFI to vascular surgery or medical units pre- and post-implementation of an EHR-embedded treatment algorithm and order set. Exclusion criteria: duplicate patients, concomitant infection, transfer from an outside hospital. Primary endpoint: antipseudomonal use among included patients (DOT/1000 DFI days present). Secondary outcomes: empiric antipseudomonal use, length of stay, 30-day readmission, mortality, amputation, and <i>Clostridioides difficile</i> infection. Patient demographics, diagnostics, treatments, and outcomes were evaluated.</p><p><strong>Results: </strong>Two hundred ten patients were included with 70 patients included in each group. The post-algorithm group had lower antipseudomonal DOT/1000 DFI days present compared to the pre-intervention group (360 vs 503, <i>P</i> < 0.001). The post-order set group had the lowest antipseudomonal use (347 vs 503, <i>P</i> < 0.001). Empiric antipseudomonal use decreased from 85.7% pre-intervention to 72% post-algorithm and 68.5% post-order set. Collectively, 30-day mortality was < 5%. Amputation during and within 30 days of hospitalization was similar in the pre-intervention (48.6%), post-algorithm (30%), and post-order set (41.4%) groups. Methicillin-susceptible <i>Staphylococcus aureus</i> and <i>Streptococcus</i> spp. were most frequently isolated. Wound cultures were not collected in 24.3%, 22.9%, and 40% of the pre-intervention, post-algorithm, and post-order set group.</p><p><strong>Conclusions: </strong>EHR-embedded clinical decision-making tools reduce antipseudomonal use for DFI treatment without increasing 30-day mortality or amputation.</p>","PeriodicalId":72246,"journal":{"name":"Antimicrobial stewardship & healthcare epidemiology : ASHE","volume":"5 1","pages":"e89"},"PeriodicalIF":0.0000,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11951233/pdf/","citationCount":"0","resultStr":"{\"title\":\"Healing soles: a microbiology-driven electronic health record-algorithm and order set to decrease antipseudomonal use in diabetic foot infections, a retrospective, observational, quasi-experimental study.\",\"authors\":\"Antoinette Marie Acbo, Naida Koura-Mola, Terrence McSweeney, Hongkai Bao, Mei Chang, Kelsie Cowman, Priya Nori, Yi Guo\",\"doi\":\"10.1017/ash.2025.59\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Antipseudomonal antibiotics are commonly prescribed for diabetic foot infections (DFI) at our institution despite a low local prevalence of <i>Pseudomonas aeruginosa</i>. A multidisciplinary team implemented a DFI electronic health record (EHR)-embedded treatment algorithm and order set.</p><p><strong>Methods: </strong>This multi-center, quasi-experimental study evaluated adults on antibiotics admitted for DFI to vascular surgery or medical units pre- and post-implementation of an EHR-embedded treatment algorithm and order set. Exclusion criteria: duplicate patients, concomitant infection, transfer from an outside hospital. Primary endpoint: antipseudomonal use among included patients (DOT/1000 DFI days present). Secondary outcomes: empiric antipseudomonal use, length of stay, 30-day readmission, mortality, amputation, and <i>Clostridioides difficile</i> infection. Patient demographics, diagnostics, treatments, and outcomes were evaluated.</p><p><strong>Results: </strong>Two hundred ten patients were included with 70 patients included in each group. The post-algorithm group had lower antipseudomonal DOT/1000 DFI days present compared to the pre-intervention group (360 vs 503, <i>P</i> < 0.001). The post-order set group had the lowest antipseudomonal use (347 vs 503, <i>P</i> < 0.001). Empiric antipseudomonal use decreased from 85.7% pre-intervention to 72% post-algorithm and 68.5% post-order set. Collectively, 30-day mortality was < 5%. Amputation during and within 30 days of hospitalization was similar in the pre-intervention (48.6%), post-algorithm (30%), and post-order set (41.4%) groups. Methicillin-susceptible <i>Staphylococcus aureus</i> and <i>Streptococcus</i> spp. were most frequently isolated. Wound cultures were not collected in 24.3%, 22.9%, and 40% of the pre-intervention, post-algorithm, and post-order set group.</p><p><strong>Conclusions: </strong>EHR-embedded clinical decision-making tools reduce antipseudomonal use for DFI treatment without increasing 30-day mortality or amputation.</p>\",\"PeriodicalId\":72246,\"journal\":{\"name\":\"Antimicrobial stewardship & healthcare epidemiology : ASHE\",\"volume\":\"5 1\",\"pages\":\"e89\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-03-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11951233/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Antimicrobial stewardship & healthcare epidemiology : ASHE\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1017/ash.2025.59\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Antimicrobial stewardship & healthcare epidemiology : ASHE","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1017/ash.2025.59","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"","JCRName":"","Score":null,"Total":0}
Healing soles: a microbiology-driven electronic health record-algorithm and order set to decrease antipseudomonal use in diabetic foot infections, a retrospective, observational, quasi-experimental study.
Background: Antipseudomonal antibiotics are commonly prescribed for diabetic foot infections (DFI) at our institution despite a low local prevalence of Pseudomonas aeruginosa. A multidisciplinary team implemented a DFI electronic health record (EHR)-embedded treatment algorithm and order set.
Methods: This multi-center, quasi-experimental study evaluated adults on antibiotics admitted for DFI to vascular surgery or medical units pre- and post-implementation of an EHR-embedded treatment algorithm and order set. Exclusion criteria: duplicate patients, concomitant infection, transfer from an outside hospital. Primary endpoint: antipseudomonal use among included patients (DOT/1000 DFI days present). Secondary outcomes: empiric antipseudomonal use, length of stay, 30-day readmission, mortality, amputation, and Clostridioides difficile infection. Patient demographics, diagnostics, treatments, and outcomes were evaluated.
Results: Two hundred ten patients were included with 70 patients included in each group. The post-algorithm group had lower antipseudomonal DOT/1000 DFI days present compared to the pre-intervention group (360 vs 503, P < 0.001). The post-order set group had the lowest antipseudomonal use (347 vs 503, P < 0.001). Empiric antipseudomonal use decreased from 85.7% pre-intervention to 72% post-algorithm and 68.5% post-order set. Collectively, 30-day mortality was < 5%. Amputation during and within 30 days of hospitalization was similar in the pre-intervention (48.6%), post-algorithm (30%), and post-order set (41.4%) groups. Methicillin-susceptible Staphylococcus aureus and Streptococcus spp. were most frequently isolated. Wound cultures were not collected in 24.3%, 22.9%, and 40% of the pre-intervention, post-algorithm, and post-order set group.
Conclusions: EHR-embedded clinical decision-making tools reduce antipseudomonal use for DFI treatment without increasing 30-day mortality or amputation.