愈合足部：一种由微生物学驱动的电子健康记录算法及医嘱集，用于减少糖尿病足感染中抗假单胞菌药物的使用，一项回顾性、观察性、准实验性研究
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.
作者信息
Acbo Antoinette Marie, Koura-Mola Naida, McSweeney Terrence, Bao Hongkai, Chang Mei, Cowman Kelsie, Nori Priya, Guo Yi
机构信息
Department of Pharmacy, Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, NY, USA.
Network Performance Group, Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, NY, USA.
出版信息
Antimicrob Steward Healthc Epidemiol. 2025 Mar 27;5(1):e89. doi: 10.1017/ash.2025.59. eCollection 2025.
BACKGROUND
Antipseudomonal antibiotics are commonly prescribed for diabetic foot infections (DFI) at our institution despite a low local prevalence of . 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 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, < 0.001). The post-order set group had the lowest antipseudomonal use (347 vs 503, < 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 and 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.
背景
尽管我院所在地区铜绿假单胞菌感染的发生率较低，但我院治疗糖尿病足感染（DFI）时，抗铜绿假单胞菌抗生素的处方仍很常见。一个多学科团队实施了一种嵌入糖尿病足感染电子健康记录（EHR）的治疗算法和医嘱集。
方法
这项多中心、准实验性研究评估了在实施嵌入EHR的治疗算法和医嘱集之前及之后，因糖尿病足感染入住血管外科或内科接受抗生素治疗的成年患者。排除标准：重复纳入的患者、合并感染、从外院转入的患者。主要终点：纳入患者中抗铜绿假单胞菌药物的使用情况（每1000个糖尿病足感染日的用药天数）。次要结局：经验性使用抗铜绿假单胞菌药物的情况、住院时间、30天再入院率、死亡率、截肢率以及感染情况。对患者的人口统计学特征、诊断、治疗及结局进行了评估。
结果
共纳入210例患者，每组70例。与干预前组相比，算法实施后组每1000个糖尿病足感染日的抗铜绿假单胞菌用药天数更低（360 vs 503，P<0.001）。医嘱集实施后组的抗铜绿假单胞菌药物使用量最低（347 vs 503，P<0.001）。经验性使用抗铜绿假单胞菌药物的比例从干预前的85.7%降至算法实施后的72%和医嘱集实施后的68.5%。总体而言，30天死亡率<5%。干预前组（48.6%）、算法实施后组（30%）和医嘱集实施后组（41.4%）在住院期间及住院后30天内的截肢率相似。最常分离出的是对甲氧西林敏感的金黄色葡萄球菌和大肠杆菌。干预前组、算法实施后组和医嘱集实施后组分别有24.3%、22.9%和40%的患者未采集伤口培养样本。
结论
嵌入电子健康记录的临床决策工具可减少糖尿病足感染治疗中抗铜绿假单胞菌药物的使用，且不增加30天死亡率或截肢率。
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