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Using existing Emergency Department data from the National Hospital Ambulatory Medical Care Survey (NHAMCS) to predict future triage waiting times from patient information.

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dlon450/Hospital-ED-Triage-Waiting-Time-Predictions

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Hospital-ED-Triage-Waiting-Time-Predictions

Estimating wait times and triage level for patients planning to go to an emergency department based on their symptoms and medical history. This project aims to help with the existing shortage of nurses in New Zealand, particularly enabling nurses to spend less time doing monotonous triage work so that more time can be spent caring for patients.

Data

The ed2017_sas.sas7bdat file contains the Emergency Department data from the 2017 National Hospital Ambulatory Medical Care Survey (NHAMCS), which was converted to the csv file ed2017_data.csv that is used in the main.ipynb and main.py files. To read and understand how the data from the NHAMCS was collected, you can look at the documentation in the NHAMCS2017-documentation.pdf file, and to look at how to use the original sas file, you can look through NHAMCS2017-file-use.txt.

Getting Started

To look at the output, open main.ipynb. To make changes and run the model, use main.py.

Built With

  • VS Code
  • Python
  • Jupyter notebooks
  • Excel

Authors

Derek Long

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Using existing Emergency Department data from the National Hospital Ambulatory Medical Care Survey (NHAMCS) to predict future triage waiting times from patient information.

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