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Using Learning Outcome Measures to assess Doctoral Nursing Education

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Published on: June 21, 2010

Transforming nursing documentation data into the Observational Medical Outcomes Partners common data model.

Hyesil Jung¹, Sooyoung Yoo², Seok Kim²

¹School of Nursing, Inha University, South Korea.

International Journal of Medical Informatics

|February 24, 2026

Summary

This summary is machine-generated.

This study standardized nursing documentation data into the Observational Medical Outcomes Partnership (OMOP) common data model (CDM) format, significantly increasing the cohort size for nausea research compared to traditional methods.

Keywords:

Common data model Data reuse Nursing records Observational Medical Outcomes Partnership Standardization

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Area of Science:

Health Informatics
Clinical Data Standardization
Observational Research

Background:

Nursing documentation in Electronic Health Records (EHRs) contains valuable patient data but is often underutilized due to low quality.
Standardizing nursing notes is crucial for leveraging this rich data source in research.
Existing research often overlooks the detailed insights available in nursing narratives.

Purpose of the Study:

To transform nursing documentation data into the Observational Medical Outcomes Partnership (OMOP) common data model (CDM) format.
To create a comprehensive cohort of inpatients experiencing nausea using standardized nursing data.
To demonstrate the effectiveness of data standardization in enhancing research cohort generation.

Main Methods:

Extracted 4006 unique nursing statements from EHRs of a South Korean hospital.
Standardized statements using Systematized Nomenclature Of Medicine Clinical Terms (SNOMED CT) and mapped them to the OMOP CDM.
Generated an inpatient nausea cohort using standardized nursing statements and compared it with a cohort derived from diagnoses and chief complaints.

Main Results:

Achieved 98.9% mapping rate of nursing statements to SNOMED CT concepts.
Standardized nearly 200 million nursing statements from over 2.5 million cases into OMOP CDM.
The cohort generated from nursing data (214,830 cases) was substantially larger than that from diagnoses/chief complaints (12,381 cases).

Conclusions:

This study represents the first successful conversion of nursing documentation into the OMOP CDM format.
Standardization of nursing data significantly expands research cohort identification, particularly for conditions like nausea.
Further expansion of these standardization methods across institutions participating in the OMOP CDM project is recommended.