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Using machine learning to predict subsequent events after EMS non-conveyance decisions.

Jani PaulinAkseli ReunamoJouni KurolaHans MoenSanna SalanteraHeikki RiihimäkiTero VesanenMari KoivistoTimo Iirola
Published in: BMC medical informatics and decision making (2022)
Machine learning can be used to predict subsequent events after EMS non-conveyance missions. From the patient safety perspective, it is notable that subsequent event does not necessarily mean that patient safety is compromised. There were a number of subsequent visits to primary health care or EDs, which were planned before by EMS. This demonstrates the appropriate use of limited resources to avoid unnecessary conveyance to the ED. However, further studies are needed without planned subsequent events to find out the harmful subsequent events, where EMS non-conveyance puts patient safety at risk.
Keyphrases
  • patient safety
  • quality improvement
  • machine learning
  • emergency department
  • big data