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  11. Nursing Workload: Use Of Artificial Intelligence To Develop A Classifier Model

Nursing workload: use of artificial intelligence to develop a classifier model

Ninon Girardon da Rosa1,2, Tiago Andres Vaz3, Amália de Fátima Lucena1,4,5

  • 1Universidade Federal do Rio Grande do Sul, Escola de Enfermagem, Porto Alegre, RS, Brazil.

Revista Latino-Americana De Enfermagem
|July 10, 2024

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View abstract on PubMed

Summary
This summary is machine-generated.

A new artificial intelligence model predicts nursing workload using electronic health records. This AI tool can effectively automate nursing workload assessment, improving efficiency in healthcare.

Area of Science:

  • Nursing Informatics
  • Artificial Intelligence in Healthcare
  • Machine Learning Applications

Background:

  • Accurate nursing workload assessment is crucial for optimal patient care and resource allocation.
  • Traditional methods of nursing workload assessment can be time-consuming and subjective.
  • The integration of artificial intelligence offers potential for more objective and efficient workload prediction.

Purpose of the Study:

  • To develop and validate a predictive nursing workload classifier model.
  • To utilize artificial intelligence (AI) and machine learning (ML) for workload prediction.
  • To identify key variables from electronic patient records that predict nursing workload.

Main Methods:

  • Retrospective observational study utilizing electronic patient records.

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  • Machine learning algorithms applied to a dataset of 43,871 nursing assessments and 11,774 patient records.
  • Data analysis performed on the Dataiku® data science platform for exploratory, descriptive, and predictive analysis.

    • Main Results:

    • An AI-enabled classifier model for nursing workload was successfully developed.
    • The model achieved 72% accuracy in classifying variables contributing to workload prediction.
    • The area under the Receiver Operating Characteristic curve was 82%, indicating good predictive performance.

    Conclusions:

    • It is feasible to train AI algorithms using electronic health record data to predict nursing workload.
    • AI tools demonstrate effectiveness in automating the nursing workload assessment process.
    • This predictive model has the potential to enhance efficiency and accuracy in healthcare resource management.