Risk factors for drug-related problems in a general hospital: A large prospective cohort

综合医院药物相关问题的风险因素:一项大型前瞻性队列研究

阅读:1

Abstract

OBJECTIVE: To identify risk factors for potential Drug-Related Problems (DRP) at admission in hospitalized patients. METHODOLOGY: Prospective cohort study conducted in adults patients hospitalized (May 2016 to May 2018) in a general tertiary care hospital in Brazil. Potential DRP were detected by daily review of 100% of electronic medication orders by hospital pharmacists and classified by the Pharmaceutical Care Network Europe classification system (PCNE version 6.2). For the identification of risk factors of potential DRP, backward stepwise logistic regression was used to identify the set of independent predictors among over 120 variables collected in the initial 48 hours after admission in a training set consisting of 2/3 of the study population. The model was validated in the remaining sample. RESULTS: The study population consisted of 1686 patients aged 52.0+/- 18.3 years-old, 51.4% females, with a median length of stay of 3.24 days, and 4.5% in-hospital mortality. The cumulative incidence of potential DRP was 14.5%. Admission for elective surgery and main diagnosis of disease of the circulatory system were associated with reduced risk of DRP (OR 0.41 and 0.57, respectively, p<0.05). The independent risk factors of DRP are heart rate ≥ 80 bpm (OR 1.41, p = 0.05), prescription of more than seven drugs in day 2 (OR 1.63, p = 0.05), prescription in day 1 of drugs of the Anatomical Therapeutic Chemical Code (ATC) class A (alimentary tract and metabolism, OR 2.24, p = 0.003), prescription in day 2 of two or more ATC class A drugs (OR = 3.52, p<0.001), and in day 1 of ATC class J drugs (antiinfectives for systemic use, OR 1.97, p = 0.001). In the validation set, the c-statistic of the predictive model was 0.65, the sensitivity was 56.1% and the specificity was 65.2%. CONCLUSION: This study identified seven independent risk factors of potential DRP in patients hospitalized in a general hospital that have fair predictive performance for utilization in clinical practice.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。