Constructing the Nursing Value Model Using Readily Available Datasets: Putting the Puzzle Pieces Together

Area of Science:

• Healthcare Informatics
• Nursing Research
• Data Science

Background:

• The Nursing Value Model (NVM) is a framework for measuring patient-level nursing care value.
• Limited research exists on NVM construction and feasibility using real-world data.
• Electronic health records (EHR) and administrative data are key sources for healthcare analytics.

Purpose of the Study:

• To introduce a method for constructing the NVM using available healthcare data.
• To discuss the feasibility of NVM development by identifying insights and challenges.
• To explore patient-level nursing cost estimation through data synthesis.

Main Methods:

• Collected and merged six datasets from four distinct data sources.
• Described data acquisition, wrangling, construction, and integrability processes.
• Analyzed strengths and weaknesses of individual datasets for NVM development.

Main Results:

• Successfully constructed a dataset for NVM exploration from multiple sources.
• Identified significant challenges in merging datasets due to non-uniform unique codes for patients and nurses.
• Highlighted the complexity and difficulty encountered during the data integration process.

Conclusions:

• Developing the NVM requires robust data systems capable of easy data collection, organization, and synthesis.
• Addressing data uniformity issues is crucial for accurate patient-level nursing value computation.
• Future efforts should focus on improving data infrastructure to support comprehensive nursing value assessment.