Center for Access and Delivery Research and Evaluation, Iowa City Veterans Affairs Health Care System, Iowa City, Iowa, USA.
Division of Infectious Diseases, University of Iowa Carver College of Medicine, Iowa City, Iowa, USA.
Clin Infect Dis. 2024 Sep 26;79(3):588-595. doi: 10.1093/cid/ciae224.
Antibiotic overuse at hospital discharge is common, but there is no metric to evaluate hospital performance at this transition of care. We built a risk-adjusted metric for comparing hospitals on their overall post-discharge antibiotic use.
This was a retrospective study across all acute-care admissions within the Veterans Health Administration during 2018-2021. For patients discharged to home, we collected data on antibiotics and relevant covariates. We built a zero-inflated, negative, binomial mixed model with 2 random intercepts for each hospital to predict post-discharge antibiotic exposure and length of therapy (LOT). Data were split into training and testing sets to evaluate model performance using absolute error. Hospital performance was determined by the predicted random intercepts.
1 804 300 patient-admissions across 129 hospitals were included. Antibiotics were prescribed to 41.5% while hospitalized and 19.5% at discharge. Median LOT among those prescribed post-discharge antibiotics was 7 (IQR, 4-10) days. The predictive model detected post-discharge antibiotic use with fidelity, including accurate identification of any exposure (area under the precision-recall curve = 0.97) and reliable prediction of post-discharge LOT (mean absolute error = 1.48). Based on this model, 39 (30.2%) hospitals prescribed antibiotics less often than expected at discharge and used shorter LOT than expected. Twenty-eight (21.7%) hospitals prescribed antibiotics more often at discharge and used longer LOT.
A model using electronically available data was able to predict antibiotic use prescribed at hospital discharge and showed that some hospitals were more successful in reducing antibiotic overuse at this transition of care. This metric may help hospitals identify opportunities for improved antibiotic stewardship at discharge.
医院出院时抗生素过度使用很常见，但目前还没有评估医院在这一护理过渡期表现的指标。我们构建了一个风险调整指标，用于比较医院出院后整体抗生素使用情况。
这是一项在退伍军人健康管理局 2018-2021 年所有急症住院患者中进行的回顾性研究。对于出院回家的患者，我们收集了抗生素和相关协变量的数据。我们构建了一个零膨胀、负二项混合模型，每个医院有 2 个随机截距，用于预测出院后抗生素暴露和治疗时长 (LOT)。数据分为训练集和测试集，使用绝对误差评估模型性能。医院的表现由预测的随机截距来确定。
纳入了 129 家医院的 1 804 300 例患者入院数据。住院期间开具抗生素的比例为 41.5%，出院时开具抗生素的比例为 19.5%。出院后开具抗生素的患者 LOT 中位数为 7（IQR，4-10）天。该预测模型准确地检测到出院后抗生素的使用情况，包括准确识别任何暴露（精度-召回曲线下面积 = 0.97）和可靠预测出院后 LOT（平均绝对误差 = 1.48）。根据该模型，39 家（30.2%）医院出院时开具抗生素的频率低于预期，使用的 LOT 也短于预期。28 家（21.7%）医院出院时开具抗生素的频率高于预期，使用的 LOT 也长于预期。
一个使用电子数据的模型能够预测医院出院时开具的抗生素，并表明一些医院在这一护理过渡期减少抗生素过度使用方面更为成功。该指标可能有助于医院发现出院时改善抗生素管理的机会。
