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Search All Research Studies
Topics
- Adverse Events (1)
- (-) Clinical Decision Support (CDS) (4)
- (-) Data (4)
- Electronic Health Records (EHRs) (2)
- Health Information Technology (HIT) (1)
- Heart Disease and Health (1)
- Infectious Diseases (1)
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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 4 of 4 Research Studies DisplayedRoosan D, Samore M, Jones M
Big-data based decision-support systems to improve clinicians' cognition.
This study focused on answers from the experts on how clinical reasoning can be supported by population-based Big-Data. It found cognitive strategies such as trajectory tracking, perspective taking, and metacognition has the potential to improve clinicians' cognition to deal with complex problems. These cognitive strategies all have important implications for the design of Big-Data based decision-support tools that could be embedded in electronic health records.
AHRQ-funded; HS023349.
Citation: Roosan D, Samore M, Jones M .
Big-data based decision-support systems to improve clinicians' cognition.
IEEE Int Conf Healthc Inform 2016;2016:285-88. doi: 10.1109/ichi.2016.39.
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Keywords: Clinical Decision Support (CDS), Shared Decision Making, Data, Electronic Health Records (EHRs)
Roosan D, Del Fiol G, Butler J
Feasibility of population health analytics and data visualization for decision support in the infectious diseases domain: a pilot study.
The objectives of this study were: 1) to explore the feasibility of extracting and displaying population-based information from an actual clinical population's database records, 2) to explore specific design features for improving population display, 3) to explore perceptions of population information displays, and 4) to explore the impact of population information display on cognitive outcomes. It concluded that a population database has great potential for reducing complexity and uncertainty in medicine to improve clinical care.
AHRQ-funded; HS023349.
Citation: Roosan D, Del Fiol G, Butler J .
Feasibility of population health analytics and data visualization for decision support in the infectious diseases domain: a pilot study.
Appl Clin Inform 2016 Jun 29;7(2):604-23. doi: 10.4338/aci-2015-12-ra-0182.
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Keywords: Clinical Decision Support (CDS), Data, Shared Decision Making, Infectious Diseases, Public Health
Liang 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