Towards a full picture of the costs of antimicrobial resistance - A first attempt to quantify the hidden cost of in-hospital adjustment reactions in a changing environment of resistance

抗生素耐药性（AMR）的出现和传播仍然是世界范围内尚未解决的问题。AMR最明显的影响是医疗相关感染（HAI），被认为是医疗保健提供中最常见的不良事件。由多重耐药细菌引起的HAI通过疾病的恶化或延长以及随后的住院治疗给医疗保健系统带来了巨大的经济负担。基本上，几乎所有关于AMR负担的研究都集中在患者面临感染的负担上。然而，AMR的出现和蔓延并不仅仅导致HAI数量的增加。AMR也会影响未感染的患者。一般来说，传染病是可传染的，对传播或感染的恐惧导致病人和医生改变他们的行为。由于医院内的耐药模式随着时间的推移而发生变化，合理的加权促使决策者调整他们的行为，以便在不断变化的耐药环境中提供最佳的治疗。这种耐药诱导的适应反应可被视为避免HAI不良事件的预防措施。例如，在耐药微生物普遍存在的情况下，医生通常会根据相关的耐药指标改变经验性抗生素治疗，导致成本、给药方案和/或副作用特征的差异。相对于现有的文献，阻力引起的调整反应往往被假定为具有重大影响的现代医疗保健服务，但很少解决在实证works.The项目的总体目标是确定和应用方法量化的隐性成本的阻力在医院设置。将确定适当的数据来源和统计方法，以显示耐药性对特定临床调整反应的影响，并量化这种关系，以确定耐药性的隐藏成本。这些方法将适用于临床环境中耐药诱导的调整反应的三种特定情况。此外，将保证最大程度的成果可转移性，以供进一步的研究综合。

The emergence and spread of antimicrobial resistance (AMR) is still an unresolved problem worldwide. The most visible effect of AMR, healthcare-associated infections (HAIs), are considered to be the most frequent adverse event in health care delivery. HAIs caused by multidrug-resistant bacteria impose a substantial financial burden on the healthcare system through exacerbation or prolongation of illness and subsequent in-hospital treatment. Basically, nearly any of studies addressing the burden of AMR is focussing on the burden of patients facing infections. The emergence and spread of AMR, however, does not lead to an increase in the number of HAIs only. AMR also impacts patients who do not become infected. Generally spoken, infectious diseases are communicable and the fear of transmission or infection leads patients and physicians to alter their behaviour. As in-hospital resistance patterns change over time, rationale weighting induces decision-makers to adjust their behaviour in order to provide the best possible treatment in a changing environment of resistance. Such resistance-induced adjustment reactions may be seen as prophylactic measures to avoid the adverse events of HAIs. In settings where resistant organisms are prevalent, for instance, physicians routinely change empirical antibiotic therapy in accordance to the relevant resistance indicator leading to differences in costs, dosing schedules and/or side-effect profiles. With respect to the available literature, resistance-induced adjustment reactions were often postulated as having a major influence on modern health care delivery, but rarely addressed in empirical works.The general aim of the project is to identify and apply methods for quantifying the hidden cost of resistance in the hospital setting. Appropriate data sources and statistical approaches will be identified enabling to show the impact of resistance on specific clinical adjustment reactions and allow quantifying this relationship in order to determine the hidden cost of resistance. These methods will be applicable to three specific scenarios of resistance-induced adjustment reactions in the clinical setting. Moreover, a maximum level of transferability of results for further research synthesis will be warranted.