Evaluation of a New Digital Automated Glycemic Pattern Detection Tool.

ABSTRACT:

Background

Blood glucose meters are reliable devices for data collection, providing electronic logs of historical data easier to interpret than handwritten logbooks. Automated tools to analyze these data are necessary to facilitate glucose pattern detection and support treatment adjustment. These tools emerge in a broad variety in a more or less nonevaluated manner. The aim of this study was to compare eDetecta, a new automated pattern detection tool, to nonautomated pattern analysis in terms of time investment, data interpretation, and clinical utility, with the overarching goal to identify early in development and implementation of tool areas of improvement and potential safety risks.

Methods

Multicenter web-based evaluation in which 37 endocrinologists were asked to asses

SUBMITTER: Comellas MJ 

PROVIDER: S-EPMC5689116 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature