Proceedings of the International Conference on Public Organization (ICONPO 2021)

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Artificial Intelligence on Queue Patients of Madiun City’s Regional Public

Authors
Ismudoko Ismudoko1, *, Maidi Maidi1, maididoktorut2020@gmail.com, Susanti Susanti2, susanti@ecampus.ut.ac.id
1Student of Public Administration Doctoral Program, Universitas Terbuka
2Lecturer at The Department of Administration, Universitas Terbuka
*Corresponding author. Email: ismudoko@gmail.com
Corresponding Author
Ismudoko Ismudoko
Available Online 1 March 2022.
DOI
10.2991/aebmr.k.220209.010How to use a DOI?
Keywords
Artificial Intelligence; Efficiency of Visit; Outpatient; Patient Queues; Queue Brokers
Abstract

The patients ‘ main objection was the application of public services in a queue of patients online and offline in the RSUD Madiun City, East Java, Indonesia. The number online is generally lower than on site, when services are merged hence all hospital patients are offline. Over 90% of outpatients are public health insurance (BPJS Kesehatan) participants. On-site queues with restrictions on the number of patients at a doctor must queue 4 - 7 hours before the service opens so that brokers queue up. This study aims to develop artificial intelligence in an integrated patient queuing system between BPJS Kesehatan, doctors, clinics, medical records, and pharmacies; for service time efficiency. This study uses a soft system methodology.

The RSUD Madiun medical records show that over 55% of outpatients aged 54 years have minimal internet access and gadgets. The Covid-19 Pandemic requires innovation to prevent crowds, so chronic outpatients are provided with a queue list facility by clinic staff after completing the doctor’s examination for the next month. The clinic staff monitor displays the remaining medication, date of referral, planned visit, queue number, and future service hours. Visits were efficient, chronic outpatient treatment at that time, and getting the queue number for the next visit. Artificial intelligence innovation that integrates offline and online patient queue numbers appropriately compromises visiting services’ efficiency to minimise patient complaints.

Copyright
© 2022 The Authors. Published by Atlantis Press International B.V.
Open Access
This is an open access article under the CC BY-NC license.

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Volume Title
Proceedings of the International Conference on Public Organization (ICONPO 2021)
Series
Advances in Economics, Business and Management Research
Publication Date
1 March 2022
ISBN
10.2991/aebmr.k.220209.010
ISSN
2352-5428
DOI
10.2991/aebmr.k.220209.010How to use a DOI?
Copyright
© 2022 The Authors. Published by Atlantis Press International B.V.
Open Access
This is an open access article under the CC BY-NC license.

Cite this article

risenwbib
TY  - CONF
AU  - Ismudoko Ismudoko
AU  - Maidi Maidi
AU  - Susanti Susanti
PY  - 2022
DA  - 2022/03/01
TI  - Artificial Intelligence on Queue Patients of Madiun City’s Regional Public
BT  - Proceedings of the International Conference on Public Organization (ICONPO 2021)
PB  - Atlantis Press
SP  - 68
EP  - 73
SN  - 2352-5428
UR  - https://doi.org/10.2991/aebmr.k.220209.010
DO  - 10.2991/aebmr.k.220209.010
ID  - Ismudoko2022
ER  -