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Patient Cohort Identification on Time Series Data Using the OMOP Common Data Model.

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Summary

Arden Syntax enables on-the-fly calculations for clinical trial feasibility queries on OMOP CDM data. This approach avoids pre-calculation, streamlining patient cohort identification for research.

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Area of Science:

  • Clinical informatics
  • Health data analytics
  • Medical logic systems

Background:

  • Patient cohort identification for clinical trials relies on evaluating inclusion/exclusion criteria.
  • Clinical facts needed for criteria evaluation may require calculation at query runtime (feasibility queries).
  • Existing tools like Atlas for OMOP Common Data Model (CDM) lack on-the-fly calculation capabilities.

Purpose of the Study:

  • To investigate the use of Arden Syntax for feasibility queries on the OMOP CDM.
  • To enable on-the-fly calculations for eligibility criteria at query runtime.
  • To eliminate the need for pre-calculating data elements for cohort specification.

Main Methods:

  • Developed a service to read OMOP repository facts for Arden Syntax processing.
  • Implemented an Arden Syntax Medical Logic Module (MLM) to apply eligibility criteria.
  • Performed feasibility queries on patient datasets to identify eligible cases.

Main Results:

  • Successfully implemented an MLM-based feasibility query to identify overventilation cases.
  • Demonstrated on-the-fly calculation capability using a two-MLM approach for reusability.
  • Validated the feasibility of using Arden Syntax for dynamic clinical data analysis.

Conclusions:

  • Arden Syntax Medical Logic Modules (MLMs) are suitable for feasibility queries on OMOP CDM.
  • The on-the-fly calculation method is compatible with any OMOP instance without altering existing infrastructure.
  • This approach offers an effective solution for real-time data calculations in OMOP.