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A Prototype for Executable and Portable Electronic Clinical Quality Measures Using the KNIME Analytics Platform.

Mo H, Pacheco JA, Rasmussen LV, Speltz P, Pathak J, Denny JC, Thompson WK - AMIA Jt Summits Transl Sci Proc (2015)

Bottom Line: To prototype this capability, we implemented eCQM CMS30 (titled: Statin Prescribed at Discharge) using KNIME.The implementation contains value set modules with connections to the National Library of Medicine's Value Set Authority Center, QDM Data Elements that can query a local EHR database, and logical and temporal operators.We successfully executed the KNIME implementation of CMS30 using data from the Vanderbilt University and Northwestern University EHR systems.

View Article: PubMed Central - PubMed

Affiliation: Vanderbilt University, Nashville, TN.

ABSTRACT
Electronic clinical quality measures (eCQMs) based on the Quality Data Model (QDM) cannot currently be executed against non-standardized electronic health record (EHR) data. To address this gap, we prototyped an implementation of a QDM-based eCQM using KNIME, an open-source platform comprising a wide array of computational workflow tools that are collectively capable of executing QDM-based logic, while also giving users the flexibility to customize mappings from site-specific EHR data. To prototype this capability, we implemented eCQM CMS30 (titled: Statin Prescribed at Discharge) using KNIME. The implementation contains value set modules with connections to the National Library of Medicine's Value Set Authority Center, QDM Data Elements that can query a local EHR database, and logical and temporal operators. We successfully executed the KNIME implementation of CMS30 using data from the Vanderbilt University and Northwestern University EHR systems.

No MeSH data available.


Related in: MedlinePlus

Implementation of CMS30 (Statin at Discharge) on KNIME. Arrow-headed lines denote transmission of data tables; square-headed lines denote database connections; round-headed lines denote transmission of flow variables. Pie chart in lower right is generated from visualization nodes in Region D.
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f1-2091960: Implementation of CMS30 (Statin at Discharge) on KNIME. Arrow-headed lines denote transmission of data tables; square-headed lines denote database connections; round-headed lines denote transmission of flow variables. Pie chart in lower right is generated from visualization nodes in Region D.

Mentions: Figure 1 shows the overall KNIME workflow for CMS30. It can be conceptually divided into four regions, as shown in the figure. Here we focus on the elements most relevant to implementing the QDM.


A Prototype for Executable and Portable Electronic Clinical Quality Measures Using the KNIME Analytics Platform.

Mo H, Pacheco JA, Rasmussen LV, Speltz P, Pathak J, Denny JC, Thompson WK - AMIA Jt Summits Transl Sci Proc (2015)

Implementation of CMS30 (Statin at Discharge) on KNIME. Arrow-headed lines denote transmission of data tables; square-headed lines denote database connections; round-headed lines denote transmission of flow variables. Pie chart in lower right is generated from visualization nodes in Region D.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4525225&req=5

f1-2091960: Implementation of CMS30 (Statin at Discharge) on KNIME. Arrow-headed lines denote transmission of data tables; square-headed lines denote database connections; round-headed lines denote transmission of flow variables. Pie chart in lower right is generated from visualization nodes in Region D.
Mentions: Figure 1 shows the overall KNIME workflow for CMS30. It can be conceptually divided into four regions, as shown in the figure. Here we focus on the elements most relevant to implementing the QDM.

Bottom Line: To prototype this capability, we implemented eCQM CMS30 (titled: Statin Prescribed at Discharge) using KNIME.The implementation contains value set modules with connections to the National Library of Medicine's Value Set Authority Center, QDM Data Elements that can query a local EHR database, and logical and temporal operators.We successfully executed the KNIME implementation of CMS30 using data from the Vanderbilt University and Northwestern University EHR systems.

View Article: PubMed Central - PubMed

Affiliation: Vanderbilt University, Nashville, TN.

ABSTRACT
Electronic clinical quality measures (eCQMs) based on the Quality Data Model (QDM) cannot currently be executed against non-standardized electronic health record (EHR) data. To address this gap, we prototyped an implementation of a QDM-based eCQM using KNIME, an open-source platform comprising a wide array of computational workflow tools that are collectively capable of executing QDM-based logic, while also giving users the flexibility to customize mappings from site-specific EHR data. To prototype this capability, we implemented eCQM CMS30 (titled: Statin Prescribed at Discharge) using KNIME. The implementation contains value set modules with connections to the National Library of Medicine's Value Set Authority Center, QDM Data Elements that can query a local EHR database, and logical and temporal operators. We successfully executed the KNIME implementation of CMS30 using data from the Vanderbilt University and Northwestern University EHR systems.

No MeSH data available.


Related in: MedlinePlus