Feasibility of Representing Data from Published Nursing Research Using the OMOP Common Data Model.

We explored the feasibility of representing nursing research data with the Observational Medical Outcomes Partners (OMOP) Common Data Model (CDM) to understand the challenges and opportunities in representing various types of health data not limited to diseases and drug treatments. We collected 1,431 unique data items from 256 nursing articles and mapped them to the OMOP CDM. A deeper level of mapping was explored by simulating 10 data search use cases.

Explorative Analyses of Nursing Research Data.

As a first step of pursuing the vision of "Big Data science in nursing," we described the characteristics of nursing research data reported in 194 published nursing studies. We also explored how completely the Version 1 metadata specification of biomedical and healthCAre Data Discovery Index Ecosystem (bioCADDIE) represents these metadata. The metadata items of the nursing studies were all related to one or more of the bioCADDIE metadata entities.

Developing a Semantic Model to Describe Physical Activity Data.

The importance of data in the social and behavioral domains to biomedical research is increasing, but ensuring the reusability of such data through standardization is not a trivial task. To start addressing this challenge, we developed a semantic model of the physical activity domain by reviewing 302 physical activity questions collected from standardized questionnaires and public data repositories. Our semantic model is comprised of activity keywords, qualifiers, response measures and context.