Assessment of Evaluation Tools for Integrated Surveillance of Antimicrobial Use and Resistance Based on Selected Case Studies.
Assessment of Evaluation Tools for Integrated Surveillance of Antimicrobial Use and Resistance Based on Selected Case Studies.
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DOI：
10.3389/fvets.2021.620998
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发表时间：
2021
影响因子：
3.2
通讯作者：
Alban L
中科院分区：
文献类型：
--
作者：
Sandberg M;Hesp A;Aenishaenslin C;Bordier M;Bennani H;Bergwerff U;Chantziaras I;De Meneghi D;Ellis-Iversen J;Filippizi ME;Mintiens K;Nielsen LR;Norström M;Tomassone L;van Schaik G;Alban L
需要对动物、人类和环境中的抗菌素使用(AMU)和耐药性(AMR)综合监测进行定期评估，以确保系统的有效性，但问题是如何进行。在这项研究中，将6种不同的评估工具应用于8个国家的AMU和AMR监测后进行了评估：(1)ATLASS：联合国粮食及农业组织(FAO)开发的实验室和AMR监测系统评估工具，(2)ECOSUR：监测工具协作评估，(3)ISSEP：综合监测系统评估项目，(4)Neoh：由欧盟成本行动开发的“一个健康评估网络”，(5)PMP-AMR：由粮农组织开发的AMR累进管理路径工具，和(6)SURVTOOLS：在FP7-EU项目“RISKSUR”中开发。每个工具使用(I)11个预定义的功能方面(例如，关于数据、时间和人员需求的可操作性)进行评分；(Ii)类似于用户体验的优势、劣势、机会和威胁(SWOT)方法(例如，我喜欢的或工具涵盖得很好的东西)；以及(Iii)8个与范围相关的预定义内容主题(例如，开发目的和协作)。PMP-AMR、ATLASS、ECOSUR和NEOH是提供评分系统以获得半定量结果的评估工具，而ISSEP和SURVTOOLS将产生如何进行评估的计划(S)。ISSEP、ECOSUR、NEOH和SURVTOOLS允许进行深入的分析，因此需要更复杂的数据、信息和评估员的专门培训(S)。PMP-AMR、ATLASS和ISSEP是专门为与AMR相关的活动开发的--只有ISSEP包括“整合”和“对决策的影响”的直接衡量标准的产生。Neoh和ISSEP被认为是评估一个健康(OH)方面的最佳工具，ECOSUR是评估合作质量的最佳工具。PMP-AMR和ATLASS似乎是用户最友好的工具，特别是为风险经理设计的。ATLASS是唯一专门关注实验室活动的工具。我们的经验是，需要足够的资源来进行评估(S)。在大多数情况下，评价需要若干评审员和/或利益攸关方的参与，需要数周至数月的时间才能完成。这项研究有助于指导未来AMU和AMR综合监测的评估者使用最合适的工具来实现其特定的评估目的。
Regular evaluation of integrated surveillance for antimicrobial use (AMU) and resistance (AMR) in animals, humans, and the environment is needed to ensure system effectiveness, but the question is how. In this study, six different evaluation tools were assessed after being applied to AMU and AMR surveillance in eight countries: (1) ATLASS: the Assessment Tool for Laboratories and AMR Surveillance Systems developed by the Food and Agriculture Organization (FAO) of the United Nations, (2) ECoSur: Evaluation of Collaboration for Surveillance tool, (3) ISSEP: Integrated Surveillance System Evaluation Project, (4) NEOH: developed by the EU COST Action “Network for Evaluation of One Health,” (5) PMP-AMR: The Progressive Management Pathway tool on AMR developed by the FAO, and (6) SURVTOOLS: developed in the FP7-EU project “RISKSUR.” Each tool was scored using (i) 11 pre-defined functional aspects (e.g., workability concerning the need for data, time, and people); (ii) a strengths, weaknesses, opportunities, and threats (SWOT)-like approach of user experiences (e.g., things that I liked or that the tool covered well); and (iii) eight predefined content themes related to scope (e.g., development purpose and collaboration). PMP-AMR, ATLASS, ECoSur, and NEOH are evaluation tools that provide a scoring system to obtain semi-quantitative results, whereas ISSEP and SURVTOOLS will result in a plan for how to conduct evaluation(s). ISSEP, ECoSur, NEOH, and SURVTOOLS allow for in-depth analyses and therefore require more complex data, information, and specific training of evaluator(s). PMP-AMR, ATLASS, and ISSEP were developed specifically for AMR-related activities—only ISSEP included production of a direct measure for “integration” and “impact on decision making.” NEOH and ISSEP were perceived as the best tools for evaluation of One Health (OH) aspects, and ECoSur as best for evaluation of the quality of collaboration. PMP-AMR and ATLASS seemed to be the most user-friendly tools, particularly designed for risk managers. ATLASS was the only tool focusing specifically on laboratory activities. Our experience is that adequate resources are needed to perform evaluation(s). In most cases, evaluation would require involvement of several assessors and/or stakeholders, taking from weeks to months to complete. This study can help direct future evaluators of integrated AMU and AMR surveillance toward the most adequate tool for their specific evaluation purpose.
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影响因子：
168.9
作者：
Holmes, Alison H.;Moore, Luke S. P.;Piddock, Laura J. V.
通讯作者：
Piddock, Laura J. V.
影响因子：
3.2
作者：
Bordier, Marion;Delavenne, Camille;Hendrikx, Pascal
通讯作者：
Hendrikx, Pascal
影响因子：
3.2
作者：
Falzon, Laura C.;Alumasa, Lorren;Fevre, Eric M.
通讯作者：
Fevre, Eric M.
影响因子：
3.2
作者：
Aenishaenslin C;Häsler B;Ravel A;Parmley EJ;Mediouni S;Bennani H;Stärk KDC;Buckeridge DL
通讯作者：
Buckeridge DL
影响因子：
11.1
作者：
Aenishaenslin, Cecile;Hasler, Barbara;Buckeridge, David
通讯作者：
Buckeridge, David