2017
DOI: 10.1371/journal.pone.0173021
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Development of a clinical decision support system for diabetes care: A pilot study

Abstract: Management of complex chronic diseases such as diabetes requires the assimilation and interpretation of multiple laboratory test results. Traditional electronic health records tend to display laboratory results in a piecemeal and segregated fashion. This makes the assembly and interpretation of results related to diabetes care challenging. We developed a diabetes-specific clinical decision support system (Diabetes Dashboard) interface for displaying glycemic, lipid and renal function results, in an integrated … Show more

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Cited by 44 publications
(30 citation statements)
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References 40 publications
(46 reference statements)
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“…graphs) [ 89 , 90 ]. Data can be trended over time and anomalous results identified [ 91 ]. If the system is linked to clinical guidelines, it can be used to aid decision making [ 90 ].…”
Section: How Can Pros Be Combined With New Technologies To Improve Thmentioning
confidence: 99%
“…graphs) [ 89 , 90 ]. Data can be trended over time and anomalous results identified [ 91 ]. If the system is linked to clinical guidelines, it can be used to aid decision making [ 90 ].…”
Section: How Can Pros Be Combined With New Technologies To Improve Thmentioning
confidence: 99%
“…Over the years, the adoption rate of the PI-CDSS has demonstrated steady increase, from approximately 11% to 53%. This PI-CDSS has met the requirement of a tier-3 CDSS with the capabilities to execute relevant expert knowledge using patient-specific information [22,23]. It follows that the rule sets of PI-CDSS are evidence-adaptive [14,24,25]: the clinical knowledge of the CDSS not only is founded upon the most up-to-date evidence from the literature and practice-based sources, but offers a representation of those resources [25].…”
Section: Discussionmentioning
confidence: 99%
“…Apart from image-based CDSSs, there exist those that rely solely on non-image clinical information. This group may be represented by systems for diagnosing diabetes (Sim et al, 2017). Finally, there is also a growing group of CDSSs built using genomic data, thus providing support for personalized medicine (Douali and Jaulent, 2012).…”
Section: Related Workmentioning
confidence: 99%