Feasibility of Representing Data from Published Nursing Research Using the OMOP Common Data Model.
Hyeoneui Kim1, Jeeyae Choi2, Imho Jang3
1Health System Department of Biomedical Informatics, UC San Diego, La Jolla, CA.
AMIA ... Annual Symposium Proceedings. AMIA Symposium
|March 9, 2017
Summary
This study assessed the Observational Medical Outcomes Partners (OMOP) Common Data Model (CDM) for nursing data, finding most data mappable but noting potential loss for patient-reported outcomes and interventions.
Area of Science:
- Health Informatics
- Nursing Research Data Standards
Background:
- Standardizing diverse health data is crucial for research.
- The Observational Medical Outcomes Partners (OMOP) Common Data Model (CDM) is a widely used standard.
- Nursing data presents unique representation challenges beyond traditional clinical data.
Purpose of the Study:
- To evaluate the feasibility of mapping nursing research data to the OMOP CDM.
- To identify challenges and opportunities in representing varied nursing data types.
- To inform future metadata development for nursing data discovery.
Main Methods:
- Collected 1,431 unique data items from 256 nursing articles.
- Mapped collected nursing data items to the OMOP CDM structure.
- Simulated 10 data search use cases to test mapping depth.
Main Results:
- The majority of nursing research data items were representable within the OMOP CDM.
- Information loss was identified for patient-reported outcomes, socio-economic data, and local nursing interventions.
- The study highlighted areas requiring further investigation for comprehensive data representation.
Conclusions:
- The OMOP CDM is largely feasible for nursing research data but has limitations.
- Specific nursing data domains require further attention for complete standardization.
- Lessons learned will guide metadata development for improved nursing data discovery.
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