Presentation Title

Clinical Data Discovery Tool

Presenter Information

Dave Anderson, Optum LabsFollow

Domain

Clinical Informatics

Type

Conceptual or Process Model/Framework

Theme

effectiveness; population; quality; operations

Start Date

7-6-2014 1:15 PM

End Date

7-6-2014 2:45 PM

Structured Abstract

Purpose

“Clinical Data Discovery Tool” (CDDT) is an application that allows medical researchers and hospital operations staff to create, explore and compare demographically matched cohorts in clinical and financial scenarios using large EMR data sets.

Methods

The tool maps source data of all available EMR elements through a template HL7 schema into an attribute-tag, attribute-tag-value database. Using this data, users can create simple or complex clinical hypotheses of interest. CDDT will then find the populations, demographically match the two populations, and present the findings in an interactive and visually compelling manner. Empirical evidence includes, but is not limited to differences in: costs, diseases, treatments, medications, demographics, lab results, vital signs, orders, locations, etc. All these finding are generated in seconds using massively parallel processing and rich data retrieval schemes.

Innovation

CDDT addresses many issues associated with EMR based clinical discovery and does so with speed, flexibility, scope and scale.

Discussion

The demographically matched groups created by CDDT can be used in a myriad of head to head hypothesis testing scenarios including: hospital to hospital, racial disparity, insurance type, ED vs. non-ED initiated, year over year, cross gender, cross age, treatment differences and combinations thereof.

Conclusion

Using the CDDT prototype, a number of discoveries related to racial disparity, treatment differences, indicators of child abuse and EMR quality measures have already surfaced. We will continue to refine CDDT’s features, affordability and use cases as the product matures.

Acknowledgements

N/A

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License.

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Jun 7th, 1:15 PM Jun 7th, 2:45 PM

Clinical Data Discovery Tool

Purpose

“Clinical Data Discovery Tool” (CDDT) is an application that allows medical researchers and hospital operations staff to create, explore and compare demographically matched cohorts in clinical and financial scenarios using large EMR data sets.

Methods

The tool maps source data of all available EMR elements through a template HL7 schema into an attribute-tag, attribute-tag-value database. Using this data, users can create simple or complex clinical hypotheses of interest. CDDT will then find the populations, demographically match the two populations, and present the findings in an interactive and visually compelling manner. Empirical evidence includes, but is not limited to differences in: costs, diseases, treatments, medications, demographics, lab results, vital signs, orders, locations, etc. All these finding are generated in seconds using massively parallel processing and rich data retrieval schemes.

Innovation

CDDT addresses many issues associated with EMR based clinical discovery and does so with speed, flexibility, scope and scale.

Discussion

The demographically matched groups created by CDDT can be used in a myriad of head to head hypothesis testing scenarios including: hospital to hospital, racial disparity, insurance type, ED vs. non-ED initiated, year over year, cross gender, cross age, treatment differences and combinations thereof.

Conclusion

Using the CDDT prototype, a number of discoveries related to racial disparity, treatment differences, indicators of child abuse and EMR quality measures have already surfaced. We will continue to refine CDDT’s features, affordability and use cases as the product matures.