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Use of an Automated Decision Support Tool Optimizes Clinicians’ Ability to Interpret and Appropriately Respond to Structured Self-Monitoring of Blood Glucose Data
OBJECTIVE: We evaluated the impact of an automated decision support tool (DST) on clinicians’ ability to identify glycemic abnormalities in structured self-monitoring of blood glucose (SMBG) data and then make appropriate therapeutic changes based on the glycemic patterns observed. RESEARCH DESIGN A...
Autores principales: | Rodbard, Helena W., Schnell, Oliver, Unger, Jeffrey, Rees, Christen, Amstutz, Linda, Parkin, Christopher G., Jelsovsky, Zhihong, Wegmann, Nathan, Axel-Schweitzer, Matthias, Wagner, Robin S. |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Diabetes Association
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3308297/ https://www.ncbi.nlm.nih.gov/pubmed/22344611 http://dx.doi.org/10.2337/dc11-1351 |
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