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no more long waits at the phlebotomy unit

thanks to Artificial Intelligence

waiting times reduced to 3 minutes

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errors prevented

by Artificial Intelligence

no more identification errors or pre-analytical errors

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Artificial Intelligence

predicts patient waiting times

prioritizes patients, optimizes resources

SCAN YOUR BARCODE

or

engage by CELL PHONE

have a seat and relax until called

WALK TOWARDS PHLEBOTOMIST

when called by

LCD or CELL PHONE

walk towards phlebotomist

WHEN FINISHED

"LIKE" your institution

get your test results

on your cell phone, free

phlerobo® at the phlebotomy unit:

  • Prioritizes and smoothens patient flow.
  • Records exact blood collection times in wards, prevents identification errors.
  • Tracks staff performance, computes human resources required.
  • NESLİ® 4.0 robotic phlebotomy assistant optional.
  • Ensures transparency, responsibility and accountability.

100

Successful Projects

5000000

Happy Patients

2500

Appreciations

20000

Hours Worked

Phlerobo® Benefits

phlerobo is a phlebotomy unit managements system based on AI and Robotics; PHLEbotmy + ROBOtics = PHLEROBO

Patient Waiting Lines

No more patient waiting lines, patents prioritized

Errors and Performance

No more identification or tube errors. All stages recorded. Performance tracked. OGTT timings achieved.

AI-based Prediction

Patient waiting times predicted and given to patients at the time of check in. Human resources required predicted. Number of patients and waiting space are reduced, significantly.

Phlerobo In Wards

Blood collection time recorded exactly in hospital wards, identification and tube errors prevented. On-line / off-line modes ensure work-flow continuity.

Cell Phone

Cell phone based check in to phlebotomy unit. Complimentary access to test results by cell phone. Patient feedback through cell phone.

NESLİ® 4.0 Phlebotomy Assistant

NESLİ® 4.0 Phlebotomy Assistant is a collaborative robot designed to take load off the phlebotomist.

Phlerobo in Media

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Anatolia News Agency

'Artificial Intelligence' reduced patient waiting time.

At Izmir Tepecik Research and Training Hospital's phlebotomy unit patient waiting times reduced to a few minutes, virtually, ...

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Milliyet

"Artificial Intelligence" reduced patient waiting times.

... Prof. Dr. Akbulut:"When patients arrive at the phlebotomy unit they scan a barcode then they just have a seat and wait. Nothing else is needed to be done by the patients. An algorithm runs the entire system, manages the whole unit very smoothly ....

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Haberler.com

"Artificial Intelligence" Reduced Patient Waiting Times.

Tepecik Hospital, one of the largest in Izmir, has put in use and Artificially Intelligent system and reduced patient waiting times to a few minutes at its phlebotomy unit ....

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Haberturk

Artificial Intelligence in Izmir hospital reduced waiting times at phlebotomy unit significantly.

Tepecik Hospital, one of the largest in Izmir region, removed the need for patient lines at its phlebotomy unit ..

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Vatan

Artifcial Intelligence Ended Laboratory Test Lines.

Tepecik Research and Training Hospital reduced waiting times to just 8 minutes using an Artificially Intelligent managements system. people wait comfortably for a short period of time. Patient satisfaction has jumped by 122%....

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TGRT Haber

'Artificial Intelligence' reduced patient waiting times.

... "Patients would wait first for tubes then for phlebotomists for tens of minutes prior to implementation of the system" said Prof. Akbulut and continued "we tried many ways to fix this problem but had failed ...

Scientific Research About Phlerobo

Some of the scientific publications about Phlerobo®.

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Use of Artificial Intelligence in Phlebotomy Unit

Orbatu, D., Yıldırım, O.

Turkish Journal of Biochemistry, Volume 43, Issue Supplement, Pages 22–29, ISSN (Online) 1303-829X, ISSN (Print) 0250-4685, DOI: https://doi.org/10.1515/tjb-2018-43s144.

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

Javadifard H., Sevinç S., Orbatu D., Yıldırım O., Yaşar E.

http://asyu.inista.org/

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PHLEROBO (AI Based Phlebotomy)

Sakaoğlu, H.H.

Artificial Intelligence & Health, H2020 Calls, September 16-17, Auditorium Moser, The Research Council of Norway, Drammensveien 288, Oslo, Norway

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Digitalization and Artificial Intelligence in Laboratory Medicine

Şişman A.R.

Uluslararası KBUD Kongre & LAB EXPO 2019 Ulusal 2. Kalıtsal Metabolik Hastalıklar Laboratuvarı Sempozyumu 2 – 5 Ekim 2019, Sapanca.

There used to be long waiting lines, it would take almost the whole day to give blood sample, now it takes only a few seconds, which is a very good thing.

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Interview with a patient

Anatolian News Agency

Waiting times reduced, patient satisfaction jumped. I think this is a best practive case in application of AI to routine medical services.

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Prof. Dr. Gökhan Akbulut

TGRT News

There were problems in our phlebotomy unit, we had access to very limited data. This user-friendly and effective system increased patient and employee satisfaction and provided data that made our phlebotomy unit manageable. This reflected itself very positively on our laboratory processes, as a laboratory professional, i am really very happy about this.

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Assoc. Prof. Banu İşbilen Başok (MD)

SBU Tepecik EAH, Biochemistry

Of the past or present, tracking of patient activity and staff performance statistics are made available objectively and without personal bias.

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Bilgen Ulamış, Phlebotomist

Manager of Phlebotomy Unit

Phlerobo® in Scientific Meetings

Phlerobo® was discussed in the following scientific meetings as a successful application.

Phlerobo® how it works ?

  • Patient scans barcode, then simply sits and waits comfortably.
  • Alternatively, patient uses cell phone to register by one touch.
  • Patient directed to a phlebotomist using audio-visual means or by cell phone.
  • Patient may choose to receive lab results by cell phone and without any message costs.
  • OGTT timing is managed by the system.
  • Patients may provide feedback using their cell phones.

PHLEROBO DIFFERENCE BY NUMBERS

A study is conducted at a large public hospital. Observations were made and recorded for three days about patient flow. Averages taken. After Phlerobo implementation, a similar day was selected randomly from the database and compared.

After Phlerobo implementation

  • ⓘ Number of phlebotomists remained the same
  • ⓘ Number of secretaries remained the same
  • ✔ Maximum number of patients waiting decreased by 78 (83%)
  • ⓘ Number of patients increased by 111
  • ✔ Maximum waiting time decreased by 48 minutes
  • ✔ Average waiting time decreased by 16 minutes (10 fold)
  • ⓘ Prioritized patient number increased by 92
  • ✔ (Prioritised) Maximum waiting time decreased by 35 minutes
  • ✔ (Prioritised) Average waiting time decreased by 16 minutes (19.4 fold)
  • ⓘ Number of patients without priority increased by 19
  • ✔ (Non-Prioritised) Maximum waiting time decreased by 52 minutes
  • ✔ (Non-Prioritised) Average waiting time decreased by 16 minutes (8.3 fold)
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  • Despite an increase in number of patients, waiting times are observed to have been reduced dignificantly after Phlerobo implementation.
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