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

抗菌素耐药(AMR)的出现和蔓延仍然是一个世界性的难题。AMR最明显的影响是医疗保健相关感染(HAI)，被认为是医疗保健提供过程中最常见的不良事件。由多药耐药细菌引起的人类免疫缺陷病毒通过病情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财政负担。基本上，几乎所有关于AMR负担的研究都集中在面临感染的患者的负担上。然而，AMR的出现和蔓延并不仅仅导致人类免疫缺陷病毒数量的增加。AMR还会影响没有感染的患者。一般来说，传染病是可以传染的，对传播或感染的恐惧导致患者和医生改变他们的行为。随着医院内耐药模式随着时间的推移而变化，理性权衡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尽可能好的治疗。这种耐药性诱导的调整反应可以被视为避免HAIs不良事件的预防性措施。例如，在耐药微生物普遍存在的情况下，医生会根据相关的耐药性指标定期改变经验抗生素治疗，从而导致成本、给药时间表和/或副作用情况的差异。在现有的文献中，耐药性诱导的调整反应通常被认为对现代医疗服务有重大影响，但在实证研究中很少涉及。该项目的总体目标是确定和应用方法来量化医院环境中耐药性的隐藏成本。将确定适当的数据源和统计方法，以便能够显示耐药性对特定临床调整反应的影响，并允许量化这种关系，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调整反应的三个特定场景。此外，将保证最大程度的成果可转移性，以用于进一步的研究综合。

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.