Patient Queue Systems in Hospital Using Patient Treatment Time Prediction Algorithm

Dwi Putri Handayani; Mustafid Mustafid; Bayu Surarso

doi:10.22219/kinetik.v5i1.1001

Issue

Vol. 5, No. 1, February 2020

Issue Published : Feb 6, 2020

Patient Queue Systems in Hospital Using Patient Treatment Time Prediction Algorithm

https://doi.org/10.22219/kinetik.v5i1.1001

Dwi Putri Handayani

Universitas Diponegoro

Mustafid Mustafid

Universitas Diponegoro

Bayu Surarso

Universitas Diponegoro

Corresponding Author(s) : Dwi Putri Handayani

dwiputrihan@gmail.com

Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control, Vol. 5, No. 1, February 2020
Article Published : Feb 6, 2020

Abstract

Patient Treatment Time Prediction Algorithm was very important to build an outpatient queue system at the hospital. This study aims to build a system of outpatient queues to predict the waiting time of outpatients in the eye clinic at one of Cirebon hospitals. Patient Treatment Time Prediction algorithm was calculated based on historical data or medical records of patients in the hospital with 120 patient data. The Patient Treatment Time Prediction algorithm was trained by improved Random Forest algorithm for each service and a waiting time for each service. Prediction of waiting time for each patient service was obtained by calculating the consumption of patient care time based on patient characteristics. The waiting time for each service predicted by the trained Patient Treatment Time Prediction algorithm is the total waiting time of patients in the queue for each service. This research resulted in a system that can show the time taken by patients in every service available in the eye clinic. Patient time consumption in each service produced varies according to the patient's condition, in this case based on the patient's gender and age. This research provides benefits in terms of improving performance in each department involved, optimizing human resources, and increasing patient satisfaction. This research can be developed for each department in the hospital.

Keywords

Patient Time Prediction Random Forest Waiting Time Patient Queue Management

Handayani, D. P., Mustafid, M., & Surarso, B. (2020). Patient Queue Systems in Hospital Using Patient Treatment Time Prediction Algorithm. Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control, 5(1), 45-54. https://doi.org/10.22219/kinetik.v5i1.1001

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References

R. Manivannan, “PTTP Algorithm And Its Benefits In Hospital Queuing Recommendation System,” vol. 6, no. 7, pp. 29–39, 2018.
M. Ngorsed and P. Suesaowaluk, “Hospital Service Queue Management System 1 Introduction 2 Literature Review,” pp. 550–559, 2016.
F. Mahmoodian, R. Eqtesadi, and A. Ghareghani, “Waiting Times in Emergency Department after Using the Emergency Severity index Triage Tool,” Arch. Trauma Res., vol. 3, no. 4, pp. 3–7, 2014. https://dx.doi.org/10.5812/atr.19507
Z. Xie and C. Or, “Associations between waiting times, service times, and patient satisfaction in an endocrinology outpatient department: A time study and questionnaire survey,” Inq. (United States), vol. 54, 2017. https://doi.org/10.1177%2F0046958017739527
X. Pan, N. Geng, X. Xie, and J. Wen, “Managing appointments with waiting time targets and random walk-ins,” Omega (United Kingdom), 2019. https://doi.org/10.1016/j.omega.2019.04.005
V. Babashov et al., “Reducing Patient Waiting Times for Radiation Therapy and Improving the Treatment Planning Process: a Discrete-event Simulation Model (Radiation Treatment Planning),” Clin. Oncol., vol. 29, no. 6, pp. 385–391, 2017. https://doi.org/10.1016/j.clon.2017.01.039
O. S. Pianykh and D. I. Rosenthal, “Can We Predict Patient Wait Time?,” J. Am. Coll. Radiol., vol. 12, no. 10, pp. 1058–1066, 2015. https://doi.org/10.1016/j.jacr.2015.04.010
C. Bleustein, D. B. Rothschild, A. Valen, E. Valaitis, L. Schweitzer, and R. Jones, “Wait times, patient satisfaction scores, and the perception of care,” Am. J. Manag. Care, vol. 20, no. 5, pp. 393–400, 2014.
J. Sun et al., “Reducing waiting time and raising outpatient satisfaction in a Chinese public tertiary general hospital-an interrupted time series study,” BMC Public Health, vol. 17, no. 1, pp. 1–11, 2017. https://doi.org/10.1186/s12889-017-4667-z
C. Curtis, C. Liu, T. J. Bollerman, and O. S. Pianykh, “Machine Learning for Predicting Patient Wait Times and Appointment Delays,” J. Am. Coll. Radiol., vol. 15, no. 9, pp. 1310–1316, 2018. https://doi.org/10.1016/j.jacr.2017.08.021
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A. Sayah, L. Rogers, K. Devarajan, L. Kingsley-Rocker, and L. F. Lobon, “Minimizing ED Waiting Times and Improving Patient Flow and Experience of Care,” Emerg. Med. Int., vol. 2014, no. January 2005, pp. 1–8, 2014. https://doi.org/10.1155/2014/981472
M. Michael, S. D. Schaffer, P. L. Egan, B. B. Little, and P. S. Pritchard, “Improving wait times and patient satisfaction in primary care.,” J. Healthc. Qual., vol. 35, no. 2, pp. 50–60, 2013. https://doi.org/10.1111/jhq.12004
Q. J. Nottingham, D. M. Johnson, and R. S. Russell, “The effect of waiting time on patient perceptions of care quality,” Qual. Manag. J., vol. 25, no. 1, pp. 32–45, 2018. https://doi.org/10.1080/10686967.2018.1404368
E. N. Weiss and C. Tucker, “Queue management: Elimination, expectation, and enhancement,” Bus. Horiz., vol. 61, no. 5, pp. 671–678, 2018. https://doi.org/10.1016/j.bushor.2018.05.002
D. A. Hapsari, A. E. Permanasari, S. Fauziati, and I. Fitriana, “Management information systems development for veterinary hospital patient registration using first in first out algorithm,” Proc. 2016 1st Int. Conf. Biomed. Eng. Empower. Biomed. Technol. Better Futur. IBIOMED 2016, pp. 0–4, 2017. https://doi.org/10.1109/IBIOMED.2016.7869829
J. Chen, K. Li, Z. Tang, K. Bilal, and K. Li, “A parallel patient treatment time prediction algorithm and its applications in hospital queuing-recommendation in a big data environment,” IEEE Access, vol. 4, pp. 1767–1783, 2016. https://doi.org/10.1109/ACCESS.2016.2558199
S. S. Savanth and K. N. R. M. Babu, “Hospital queuing-recommendation system based on patient treatment time,” Proc. 2017 Int. Conf. Intell. Comput. Control Syst. ICICCS 2017, vol. 2018-Janua, pp. 953–958, 2017. https://doi.org/10.1109/ICCONS.2017.8250606
Y. T. Eja and B. S. Udhakar, “Implementation of Hospital Queue Recommendation System using Parallel Patient Treatment Mechanism with Improved Random Forest Algorithm,” vol. 05, no. 05, pp. 750–753, 2017.
P. Borse, S. Raut, A. Shingade, and P. Girolla, “A Parallel Patient Treatment Time Prediction Algorithm and Its,” vol. 6, no. 11, pp. 1791–1797, 2017.

References

R. Manivannan, “PTTP Algorithm And Its Benefits In Hospital Queuing Recommendation System,” vol. 6, no. 7, pp. 29–39, 2018.

M. Ngorsed and P. Suesaowaluk, “Hospital Service Queue Management System 1 Introduction 2 Literature Review,” pp. 550–559, 2016.

F. Mahmoodian, R. Eqtesadi, and A. Ghareghani, “Waiting Times in Emergency Department after Using the Emergency Severity index Triage Tool,” Arch. Trauma Res., vol. 3, no. 4, pp. 3–7, 2014. https://dx.doi.org/10.5812/atr.19507

Z. Xie and C. Or, “Associations between waiting times, service times, and patient satisfaction in an endocrinology outpatient department: A time study and questionnaire survey,” Inq. (United States), vol. 54, 2017. https://doi.org/10.1177%2F0046958017739527

X. Pan, N. Geng, X. Xie, and J. Wen, “Managing appointments with waiting time targets and random walk-ins,” Omega (United Kingdom), 2019. https://doi.org/10.1016/j.omega.2019.04.005

V. Babashov et al., “Reducing Patient Waiting Times for Radiation Therapy and Improving the Treatment Planning Process: a Discrete-event Simulation Model (Radiation Treatment Planning),” Clin. Oncol., vol. 29, no. 6, pp. 385–391, 2017. https://doi.org/10.1016/j.clon.2017.01.039

O. S. Pianykh and D. I. Rosenthal, “Can We Predict Patient Wait Time?,” J. Am. Coll. Radiol., vol. 12, no. 10, pp. 1058–1066, 2015. https://doi.org/10.1016/j.jacr.2015.04.010

C. Bleustein, D. B. Rothschild, A. Valen, E. Valaitis, L. Schweitzer, and R. Jones, “Wait times, patient satisfaction scores, and the perception of care,” Am. J. Manag. Care, vol. 20, no. 5, pp. 393–400, 2014.

J. Sun et al., “Reducing waiting time and raising outpatient satisfaction in a Chinese public tertiary general hospital-an interrupted time series study,” BMC Public Health, vol. 17, no. 1, pp. 1–11, 2017. https://doi.org/10.1186/s12889-017-4667-z

C. Curtis, C. Liu, T. J. Bollerman, and O. S. Pianykh, “Machine Learning for Predicting Patient Wait Times and Appointment Delays,” J. Am. Coll. Radiol., vol. 15, no. 9, pp. 1310–1316, 2018. https://doi.org/10.1016/j.jacr.2017.08.021

S. A. K. Hemaya and T. E. Locker, “How accurate are predicted waiting times, determined upon a patient’s arrival in the Emergency Department?,” Emerg. Med. J., vol. 29, no. 4, pp. 316–318, 2012. https://doi.org/10.1136/emj.2010.106534

A. Sayah, L. Rogers, K. Devarajan, L. Kingsley-Rocker, and L. F. Lobon, “Minimizing ED Waiting Times and Improving Patient Flow and Experience of Care,” Emerg. Med. Int., vol. 2014, no. January 2005, pp. 1–8, 2014. https://doi.org/10.1155/2014/981472

M. Michael, S. D. Schaffer, P. L. Egan, B. B. Little, and P. S. Pritchard, “Improving wait times and patient satisfaction in primary care.,” J. Healthc. Qual., vol. 35, no. 2, pp. 50–60, 2013. https://doi.org/10.1111/jhq.12004

Q. J. Nottingham, D. M. Johnson, and R. S. Russell, “The effect of waiting time on patient perceptions of care quality,” Qual. Manag. J., vol. 25, no. 1, pp. 32–45, 2018. https://doi.org/10.1080/10686967.2018.1404368

E. N. Weiss and C. Tucker, “Queue management: Elimination, expectation, and enhancement,” Bus. Horiz., vol. 61, no. 5, pp. 671–678, 2018. https://doi.org/10.1016/j.bushor.2018.05.002

D. A. Hapsari, A. E. Permanasari, S. Fauziati, and I. Fitriana, “Management information systems development for veterinary hospital patient registration using first in first out algorithm,” Proc. 2016 1st Int. Conf. Biomed. Eng. Empower. Biomed. Technol. Better Futur. IBIOMED 2016, pp. 0–4, 2017. https://doi.org/10.1109/IBIOMED.2016.7869829

J. Chen, K. Li, Z. Tang, K. Bilal, and K. Li, “A parallel patient treatment time prediction algorithm and its applications in hospital queuing-recommendation in a big data environment,” IEEE Access, vol. 4, pp. 1767–1783, 2016. https://doi.org/10.1109/ACCESS.2016.2558199

S. S. Savanth and K. N. R. M. Babu, “Hospital queuing-recommendation system based on patient treatment time,” Proc. 2017 Int. Conf. Intell. Comput. Control Syst. ICICCS 2017, vol. 2018-Janua, pp. 953–958, 2017. https://doi.org/10.1109/ICCONS.2017.8250606

Y. T. Eja and B. S. Udhakar, “Implementation of Hospital Queue Recommendation System using Parallel Patient Treatment Mechanism with Improved Random Forest Algorithm,” vol. 05, no. 05, pp. 750–753, 2017.

P. Borse, S. Raut, A. Shingade, and P. Girolla, “A Parallel Patient Treatment Time Prediction Algorithm and Its,” vol. 6, no. 11, pp. 1791–1797, 2017.

Issue

Vol. 5, No. 1, February 2020

Patient Queue Systems in Hospital Using Patient Treatment Time Prediction Algorithm

Corresponding Author(s) : Dwi Putri Handayani

Abstract

Keywords

Download Citation

References

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