2019
DOI: 10.1186/s12992-019-0500-z
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Getting the most from after action reviews to improve global health security

Abstract: Background After Action Reviews (AARs) provide a means to observe how well preparedness systems perform in real world conditions and can help to identify – and address – gaps in national and global public health emergency preparedness (PHEP) systems. WHO has recently published guidance for voluntary AARs. This analysis builds on this guidance by reviewing evidence on the effectiveness of AARs as tools for system improvement and by summarizing some key lessons about ensuring that AARs result in … Show more

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Cited by 35 publications
(30 citation statements)
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“…The disease marched relentlessly westward until the WHO stated that Europe was the center of the pandemic (March 13, 2020). However, the possibility of a global pandemic had already been flagged by the WHO (Stoto et al, 2019).…”
Section: Introductionmentioning
confidence: 99%
“…The disease marched relentlessly westward until the WHO stated that Europe was the center of the pandemic (March 13, 2020). However, the possibility of a global pandemic had already been flagged by the WHO (Stoto et al, 2019).…”
Section: Introductionmentioning
confidence: 99%
“…Nonetheless, the analysis offered by an AAR is critical to future risk mitigation. 18 Oftentimes, organizations experience a disconnect between the observation of challenges and the implementation of solutions, even when specifically suggested in after action reports. 19 Those reports can better guide institutional change if formalized procedures are developed to guide improvement efforts.…”
Section: Discussionmentioning
confidence: 99%
“…After Action Reviews provide experiential learning opportunities and document both successes and failures, ensuring improved performance during future responses. The After Action Reviews have recently been included in the IHR Monitoring and Evaluation Framework to facilitate the sharing of best practices (Stoto et al, 2019).…”
Section: Implement Learning and Feedback Loopsmentioning
confidence: 99%