2018
DOI: 10.1097/pts.0000000000000459
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A Library of Logic Models to Explain How Interventions to Reduce Diagnostic Errors Work

Abstract: Objectives:We aimed to create a library of logic models for interventions to reduce diagnostic error. This library can be used by those developing, implementing, or evaluating an intervention to improve patient care, to understand what needs to happen, and in what order, if the intervention is to be effective. Methods:To create the library, we modified an existing method for generating logic models. The following five ordered activities to include in each model were defined: preintervention; implementation of … Show more

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Cited by 4 publications
(1 citation statement)
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“…To foster an assessment culture, the Assessment Coordinator at the University Library decided to develop and offer a workshop designed for library staff to illustrate the use of a logic model followed by individual consultations. The logic model was chosen as the workshop topic because logic models have been used as a framework in grant proposals (e.g., IMLS), strategic planning (Dubicki, 2011), library assessment (Stoddart & Lajoie, 2014), program evaluation (Markless & Streatfield, 2017), and program intervention (Kletter, Mendelez-Torres, Lilford & Taylor, 2018). Additionally, logic models are an important training topic (e.g., CARLI Counts, 2019).…”
Section: Evidencementioning
confidence: 99%
“…To foster an assessment culture, the Assessment Coordinator at the University Library decided to develop and offer a workshop designed for library staff to illustrate the use of a logic model followed by individual consultations. The logic model was chosen as the workshop topic because logic models have been used as a framework in grant proposals (e.g., IMLS), strategic planning (Dubicki, 2011), library assessment (Stoddart & Lajoie, 2014), program evaluation (Markless & Streatfield, 2017), and program intervention (Kletter, Mendelez-Torres, Lilford & Taylor, 2018). Additionally, logic models are an important training topic (e.g., CARLI Counts, 2019).…”
Section: Evidencementioning
confidence: 99%