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

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Summary
This summary is machine-generated.

This study details constructing the Nursing Value Model (NVM) using healthcare data. It highlights challenges in data integration for accurate patient-level nursing value measurement.

Keywords:
electronic health recordnurse assignment datanursing costsnursing value model

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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.