
Predicting Patient Wait Times in the Phlebotomy Unit
Author(s) -
Dilek Orbatu,
O. Yildirim,
Eminullah Yaşar,
Ali Rıza Şişman,
Süleyman Sevinç
Publication year - 2020
Publication title -
global journal of medical research
Language(s) - English
Resource type - Journals
eISSN - 2249-4618
pISSN - 0975-5888
DOI - 10.34257/gjmrkvol20is1pg1
Subject(s) - phlebotomy , medicine , blood collection , emergency medicine , surgery
Patients frequently complain of long waiting times in phlebotomy units. Patients try topredict how long they will stay in the phlebotomy unit according to the number of patients in front of them. If it is not known how fast the queue is progressing, it is not possible to predict how long a patient will wait. The number of prior patients who will come to the phlebotomy unit is another important factor that changes the waiting time prediction.We developed an artificial intelligence (AI)-based system that predicts patient waiting time in the phlebotomy unit. The system can predict the waiting time with high accuracy by considering all the variables that may affect the waiting time. In this study, the blood collection performance of phlebotomists, the duration of the phlebotomy in front of the patient, and the number of prior patients who could come to the phlebotomy unit was determined as the main parameters affecting the waiting time. For two months, actual wait times and predicted wait times were compared. The wait time for 95 percent of the patients was predicted with a variance of ± 2 minutes. An AI-based system helps patients make predictions with high accuracy, and patient satisfaction can be increased.