Difference between revisions of "Exploiting the potential of large databases of electronic health records for research using rapid algorithms and an intuitive query interface"
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| − | We have had many struggles with extracting accurate, complete and timely data however we now have, "an end-to-end system, underpinned by an innovative search algorithm, allows the user to extract information in near real-time via an intuitive query [[interface]]." <ref name= "tale ar(2013)">Tale AR, Beloff N, Al-Radwan B, Wickson J, Puri S, Williams T, Staa TV, Bleach A, 5 November 2013, Exploiting the potential of large databases of electronic health records for research using rapid search algorithms and intuitive query interface, Journal of American Medical Informatics Association 2014, 21, 292-298 http://jamia.oxfordjournals.org/content/21/2/292 </ref> | + | We have had many struggles with extracting accurate, complete and timely data however we now have, "an end-to-end system, underpinned by an innovative search algorithm, allows the user to extract information in near real-time via an intuitive query [[Interface Terminology|interface]]." <ref name= "tale ar(2013)">Tale AR, Beloff N, Al-Radwan B, Wickson J, Puri S, Williams T, Staa TV, Bleach A, 5 November 2013, Exploiting the potential of large databases of electronic health records for research using rapid search algorithms and intuitive query interface, Journal of American Medical Informatics Association 2014, 21, 292-298 http://jamia.oxfordjournals.org/content/21/2/292 </ref> |
===Background=== | ===Background=== | ||
Revision as of 05:15, 11 February 2015
Abstract
We have had many struggles with extracting accurate, complete and timely data however we now have, "an end-to-end system, underpinned by an innovative search algorithm, allows the user to extract information in near real-time via an intuitive query interface." [1]
Background
Change in technology allows for large databases to collect vast amounts of information from millions of patients which could potentially assist with research and development of studies or medicine. This data is found in the Clinical Practice Research Datalink (CPRD) database and is accessed by scientists, clinicians and government agencies from around the world.[1]The challenge lies in the amount of time such a large complex query could take to complete as well as the format in which it is extracted is typically in rows and columns. Though this is a start to findings there still may be days of work involved with sorting and filtering data.
Objective
One goal is to have the ability to run a query that will gather the data needed with little experience in coding. The other goal is to reduce the amount of time it takes to run the query."TrialViz is a simple online intuitive interface to the large and complex data held within CPRD."[1]
Methods
Multiple disciplines have come together to collaborate on such an extensive project i.e. data analysts, epidemiologists, software engineers and computer scientists.[1] After developing algorithms and identifying ways of extracting data, TrialViz has become the latest in software that can assist with large data extraction. Throughout the build process of this software they did have user involvement in all stages of development.
Results
The development of TrialViz was found to have a dramatic decrease in query times, for example a query that was typically 5 hours from start to finish was no 2 seconds[1]TrialViz is comparable to similar systems however they do not
References
- ↑ 1.0 1.1 1.2 1.3 1.4 Tale AR, Beloff N, Al-Radwan B, Wickson J, Puri S, Williams T, Staa TV, Bleach A, 5 November 2013, Exploiting the potential of large databases of electronic health records for research using rapid search algorithms and intuitive query interface, Journal of American Medical Informatics Association 2014, 21, 292-298 http://jamia.oxfordjournals.org/content/21/2/292
