Modeling a Production Function to Evaluate the Effect of Medical Staffing on Antimicrobial Stewardship Performance in China, 2009-2016: Static and Dynamic Panel Data Analyses.
Modeling a Production Function to Evaluate the Effect of Medical Staffing on Antimicrobial Stewardship Performance in China, 2009-2016: Static and Dynamic Panel Data Analyses.
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DOI：
10.3389/fphar.2018.00775
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发表时间：
2018
影响因子：
5.6
通讯作者：
Zhang X
中科院分区：
文献类型：
--
作者：
Liu J;Yin C;Liu C;Tang Y;Zhang X
背景：抗菌药物耐药性（Antimicrobial resistance，AMR）是一个国际性问题。AMR的出现和传播与抗菌药物的过度使用或不当使用密切相关。抗菌药物管理确保抗菌药物的适当使用，是控制AMR的有效方法。本研究旨在了解中国医疗人员配置与抗菌药物管理绩效之间的关系。方法：使用2009 - 2016年省级面板数据集。一个宏观生产函数被用来量化的关系。产出，抗菌管理性能，是衡量的变化，甲氧西林耐药率的葡萄球菌。金黄色葡萄球菌（S.金黄色葡萄球菌）和凝固酶阴性葡萄球菌（CoNS）。劳动力投入是以每10万人口中医院的传染病医生、药剂师、临床微生物学家和护士的数量来衡量的，而资本投入则是以每10万人口中医院的床位数量来衡量的。技术是由时间指数捕获的。静态和动态面板数据的方法。结果：根据动态模型（Coef. =-0.191，-0.351; p = 0.070，0.004）。护士人数越多，耐药率越高。金黄色葡萄球菌（Coef. = 0.648; p = 0.044）。此外，其他两组医疗专业人员的数量与管理绩效没有显着关联。结论：该研究表明临床微生物学家在抗菌药物管理中的关键作用。随着护士人数的增加，预计耐药风险增加，这可能是由于护士缺乏相关知识，以及他们在抗菌药物管理方面的功能未得到认可。
Background: Antimicrobial resistance (AMR) is an international problem. Emergence and spread of AMR are strongly associated with overuse or inappropriate use of antimicrobials. Antimicrobial stewardship ensures the appropriate use of antimicrobials, and is an effective approach to control AMR. This study aims to understand the relationship between medical staffing and antimicrobial stewardship performance in China. Methods: A provincial-level panel dataset from 2009 to 2016 is used. A macro production function is used to quantify the relationship. The output, antimicrobial stewardship performance, is measured by changes in methicillin resistance rates of Staphylococcus. aureus (S. aureus) and coagulase-negative staphylococci (CoNS). The labor input is measured by the numbers of infectious diseases physicians, pharmacists, clinical microbiologists, and nurses in hospitals per 100,000 populations, whereas the capital input is represented by the number of hospital beds per 100,000 populations. The technology is captured by the time index. Both static and dynamic panel data approaches are employed. Results: The increasing number of clinical microbiologists is a significant predictor of lower resistance of CoNS according to dynamic models (Coef. = −0.191, −0.351; p = 0.070, 0.004, respectively). However, a larger number of nurses is significantly associated with higher resistance of S. aureus (Coef. = 0.648; p = 0.044). In addition, the numbers of the other two groups of medical professionals exhibit no significant associations with stewardship performance. Conclusions: The study demonstrates the crucial role of clinical microbiologists in antimicrobial stewardship. The predicted increased risk of resistance with the higher number of nurses may be attributable to their lack of related knowledge and their unrecognized functions in antimicrobial stewardship.
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