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...

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Detalles Bibliográficos
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.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Diabetes Association 2012
Materias:
Original Research
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

Internet

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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