Applied Research on Antimicrobial Resistance (AR)

描述（由申请人提供）：人类细菌病原体中的抗生素耐药性正在以惊人的速度增长，并威胁到抗生素的有效性。耐药感染与易感微生物感染相比，具有更高的发病率、死亡率和医疗费用。重要的是制定一个简单但强大的方法来估计耐药性的成本，可供各级医疗保健系统的政策制定者使用。该提案使用利用率而不是成本作为我们估计、推断和指导成本模型开发的主要结果度量。利用率反映了实际提供的护理，并为具有不同成本概念的用户提供了成本估算的共同基础。我们计划建立一个利用概况，包括个别元素，如逗留时间蚂蚁程序。我们还将通过案例访谈收集间接成本，例如误工天数。由于金黄色葡萄球菌（SA）是人类感染性疾病发病率和死亡率的最重要的细菌原因之一，是病原体成功适应广泛使用抗生素的经典例子，我们将使用SA感染开发我们的模型。为了使该模型具有普遍性，有必要对SA疾病有一个完整的了解，而不是将其限于成人住院感染。我们将研究医疗保健和社区相关的SA疾病，包括侵入性和非侵入性病例。我们将使用来自不同来源的前瞻性和回顾性数据，并利用我们正在进行的监测系统。由于利用组分之间预期的高度相关性，将使用多变量统计分析来分析抗性和敏感SA的利用概况的差异。这将使该方法对差异的检测和估计更敏感。统计分析的结果将用于为制定和选择一个单一的“最佳”成本模型提供信息，该模型将在电子表格工具中实施。该工具可以适应不同决策者的观点，包括医疗保健提供者，健康计划和医院管理者，政府等。成本模型的输出将为更一般的社会经济模型提供输入，该模型将纳入社区传播和与MRSA向社区其他人传播相关的成本。这是第一次尝试在全社会范围内估计抵抗的成本。

Description (provided by applicant): Anti-microbial resistance among human bacterial pathogens is growing at an alarming rate and threatens the effectiveness of antibiotics. Resistant infections are associated with higher morbidity, mortality, and healthcare costs than infection with susceptible organisms. It is important to formulate a simple but robust method for estimating the cost of resistance that can be used by policy makers at all levels of the healthcare system. This proposal uses utilization rather than cost as our main outcome measure for estimation, inference, and guiding cost model development. Utilization reflects care actually rendered and provides common ground for cost estimation by users with different concepts of cost. We plan to construct a utilization profile comprised of individual elements such as length-of-stay ant procedures. We will also collect indirect costs, such as days lost from work, through case interviews. Because Staphylococcus aureus (SA) is one of the most important bacterial causes of human infectious disease morbidity and mortality and is a classic example of the successful adaptation of a pathogen to widespread antibiotic use, we will develop our model using SA infections. In order to make the model generalizable, it is necessary to have a complete picture of SA disease and not limit it to adult inpatient infection. We will study healthcare; and community-associated SA disease encompassing invasive and non-invasive cases. We will use prospective and retrospective data from heterogeneous sources and capitalize on our ongoing surveillance systems. Differences in utilization profiles of resistant and susceptible SA will be analyzed using multivariate statistical analysis due to expected high correlations among utilization components. This will make the method more sensitive to detection and estimation of differences. The results of statistical analysis will be used to inform the development and selection of a single "best" cost model that will be implemented in a spreadsheet tool. This tool can be adapted to the perspectives of different decision makers including healthcare providers, healthplan and hospital administrators, government, and others. The output of the cost model will feed the input of a more general societal economic model that will incorporate community transmission and costs associated with spread of MRSA to others in the community. This is the first time a society-wide estimate of the cost of resistance has been attempted.