Predicting Patient Waiting Time in Phlebotomy Units Using a Deep Learning Method

Javadifard H., Sevinc S., YILDIRIM O., Orbatu D., Yasar E., Sisman A.

Innovations in Intelligent Systems and Applications Conference (ASYU), İzmir, Türkiye, 31 Ekim - 02 Kasım 2019, ss.436-439 identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Doi Numarası: 10.1109/asyu48272.2019.8946380
  • Basıldığı Şehir: İzmir
  • Basıldığı Ülke: Türkiye
  • Sayfa Sayıları: ss.436-439
  • Anahtar Kelimeler: Waiting Time, Phlebotomy, Artificial Neural Network, Deep Learning, Predicting
  • Dokuz Eylül Üniversitesi Adresli: Evet

Özet

Phlebotomy units are one of the places with the highest patient density in a hospital. Because the patients from different outpatient clinics of the hospital come to the phlebotomy units to have phlebotomies performed on them. Accurately predicting waiting times can increase patient satisfaction and enable staff members to more accurately evaluate and respond to patient flow. In this study, we examined the applicability of a machine learning model to estimate waiting times in a phlebotomy unit. We used the waiting times in the Phlebotomy Unit of Izmir University of Health Sciences Tepecik Training And Research Hospital as our data set. In our study, our model predicted patient waiting times using an artificial Neural Network algorithm. As a result, we succeeded in predicting how long the patient would wait in the waiting room with 88% accuracy.