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AHRQ Research Studies
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Research Studies is a compilation of published research articles funded by AHRQ or authored by AHRQ researchers.
Results
1 to 2 of 2 Research Studies DisplayedLiang C, Gong Y
Enhancing patient safety event reporting by K-nearest neighbor classifier.
The debate on structured or unstructured data entry reveals not only a trade-off problem among data accuracy, completeness, and timeliness, but also a technical gap on text mining. The reesarchers suggested a text classification method for predicting subject categories. Their results demonstrated the feasibility of their system and indicated the advantage of such an application to raise data quality and clinical decision support in reporting patient safety events.
AHRQ-funded; HS022895.
Citation: Liang C, Gong Y .
Enhancing patient safety event reporting by K-nearest neighbor classifier.
Stud Health Technol Inform 2015;218:40603.
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Keywords: Adverse Events, Medical Errors, Patient Safety, Public Reporting, Clinical Decision Support (CDS), Health Information Technology (HIT), Data
Panahiazar M, Taslimitehrani V, Pereira NL
Using EHRs for heart failure therapy recommendation using multidimensional patient similarity analytics.
The authors developed a multidimensional patient similarity assessment technique that leverages multiple types of information from the electronic health records and predicts a medication plan for each new patient based on prior knowledge and data from similar patients.Their findings suggest that it is feasible to harness population-based information for an individual patient-specific assessment.
AHRQ-funded; HS023077.
Citation: Panahiazar M, Taslimitehrani V, Pereira NL .
Using EHRs for heart failure therapy recommendation using multidimensional patient similarity analytics.
Stud Health Technol Inform 2015;210:369-73.
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Keywords: Clinical Decision Support (CDS), Data, Electronic Health Records (EHRs), Heart Disease and Health, Patient-Centered Healthcare