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Predicting Patient Wait Times by Using Highly Deidentified Data in Mental Health Care: Enhanced Machine Learning Approach.

Amir RastpourCarolyn McGregor
Published in: JMIR mental health (2022)
The random forest method, enhanced with the system's knowledge, provided reliable wait time predictions for new outpatients, regardless of low utility of the highly deidentified input data and the high variation in wait times across different clinics and patient types. The priority system was identified as a factor that contributed to long wait times, and a fast-track system was suggested as a potential solution.
Keyphrases
  • machine learning
  • big data
  • case report
  • electronic health record
  • healthcare
  • primary care
  • climate change
  • artificial intelligence
  • data analysis
  • deep learning