Estimating how many flebotomists are required in the flebotomy unit: An artificial intelligence study

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Dilek Orbatu
Oktay Yıldırım
Ahu Pakdemirli
Eminullah Yaşar
Demet Alaygut
Süleyman Sevinç
Ali Rıza Şişman

Abstract

Objective: In this study, after the examination, most patients apply to phlebotomy units to perform the necessary examinations. Sufficient plebotomists should be taken to the phlebotomy unit to serve a large number of patients. The aim of this study is to determine the reguired number of phlebotomists in blood center using the artificial intelligence.


Material and Methods: This study was conducted in the Health Sciences University  Tepecik Training and Research Hospital Blood center between the September-November 2019 . The required number of phlebotomists in the unit was determined with an artificial intelligence-based method. With this system, the number of patients coming to the phlebotomy unit is estimated in real time and considering the past performance of the working phlebotomists, how many phlebotomists are needed in real time is calculated.


Results: The number of phlebotomists who both serve patients as quickly as possible and use the personnel resources of hospital efficiently needs to be optimized. In order to solve this problem, an AI-based system has been developed. With this system, the number of patients coming to phlebotomy unit is estimated in real time and considering the past performances of the working phlebotomists, it calculates how many phlebotomists are needed in real time


Conclusion: The suggestions made by this AI-based system have made a great contribution to the management of the phlebotomy unit. Managers used hospital staff resources in the most efficient way and at the same time, they were able to ensure that patients receive phlebotomy service by following the system's recommendations.

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How to Cite
OrbatuD., YıldırımO., PakdemirliA., YaşarE., AlaygutD., SevinçS., & ŞişmanA. R. (2020). Estimating how many flebotomists are required in the flebotomy unit: An artificial intelligence study. Medical Science and Discovery, 7(5), 489-493. https://doi.org/10.36472/msd.v7i5.379
Section
Research Article

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