2021
DOI: 10.3389/fresc.2021.638602
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A Multi-Faceted Strategy for Evidence Translation Reduces Healthcare Waiting Time: A Mixed Methods Study Using the RE-AIM Framework

Abstract: Background: Waiting lists are often thought to be inevitable in healthcare, but strategies that address patient flow by reducing complexity, combining triage with initial management, and/or actively managing the relationship between supply and demand can work. One such model, Specific Timely Appointments for Triage (STAT), brings these elements together and has been found in multiple trials to reduce waiting times by 30–40%. The next challenge is to translate this knowledge into practice.Method: A multi-facete… Show more

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Cited by 2 publications
(1 citation statement)
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“…In multi-disciplinary community and outpatient services, trials of the STAT model have resulted in a 30–40% reduction in waiting time [ 13 , 17 , 18 ]. Further, there is early evidence that the model is being implemented outside the research setting in community services [ 19 ]. Reducing waiting in community outpatient settings, where STAT has previously been trialled, is associated with improved patient outcomes [ 20 ].…”
Section: Introductionmentioning
confidence: 99%
“…In multi-disciplinary community and outpatient services, trials of the STAT model have resulted in a 30–40% reduction in waiting time [ 13 , 17 , 18 ]. Further, there is early evidence that the model is being implemented outside the research setting in community services [ 19 ]. Reducing waiting in community outpatient settings, where STAT has previously been trialled, is associated with improved patient outcomes [ 20 ].…”
Section: Introductionmentioning
confidence: 99%