Difference between revisions of "Automated Clinical Decision Support (CDS) using Pattern Recognition/Temporal Relationships"

From Clinfowiki
Jump to: navigation, search
(Overview)
Line 1: Line 1:
 
== Overview ==
 
== Overview ==
  
CDS has come a long way, most notably when one thinks of decision support, we think of alerts, reminders, drug-drug interaction checking, order sets, and note templates.  As “big data” only gets bigger on a daily basis, data warehouses fill with unstructured and structured data which provide a means for developing CDS.  “One of the “grand challenges” in CDS is thus the automatic production of CDS from the bottom-up by data-mining clinical data sources” [1].
+
Clinical decision support (CDS) has come a long way, most notably when one thinks of decision support, we think of alerts, reminders, drug-drug interaction checking, order sets, and note templates.  As “big data” only gets bigger on a daily basis, data warehouses fill with unstructured and structured data which provide a means for developing CDS.  “One of the “grand challenges” in CDS is thus the automatic production of CDS from the bottom-up by data-mining clinical data sources” [1].
  
 
== Related Projects ==
 
== Related Projects ==

Revision as of 16:35, 22 October 2015

Overview

Clinical decision support (CDS) has come a long way, most notably when one thinks of decision support, we think of alerts, reminders, drug-drug interaction checking, order sets, and note templates. As “big data” only gets bigger on a daily basis, data warehouses fill with unstructured and structured data which provide a means for developing CDS. “One of the “grand challenges” in CDS is thus the automatic production of CDS from the bottom-up by data-mining clinical data sources” [1].

Related Projects

Veterans Like Mine – Support for therapeutic decision making VLMine is planned to serve as a CDS tool when resources like PubMed or UpToDate are not adequately detailed or specific enough to answer questions in patients with clinical uncertainty. VLMine will retrieve data from data warehouses about other patients similar to the individual patient at hand and present information to clinicians to facilitate management.