COMPARISON OF THE EFFECTIVENESS ONLINE AND OFFLINE REGISTRATION SYSTEM ON PATIENT WAITING TIME IN PRIMARY HEALTH CARE SEMARANG USING QUEUING THEORY
Keywords: Online Registration, Waiting Time, Queuing Theory
The online registration system at Semarang's Primary Health Care has been implemented in 2018, but online registration users are still small. The purpose of this study was to compare the effectiveness of online and offline registration at waiting times using variables in queuing theory. Research at 3 health centers in the city of Semarang. By observing the time of arrival and time of admission to the patient's clinic then the patient is also given a registration service satisfaction questionnaire sheet. The data were processed using queuing theory variables as well as descriptive and inferential statistical analysis. The number of online registrants is only 12% while 88% registered offline. The total number of online registrant patient arrivals per hour is 0.85 patients and offline registrants are 6.38 patients per hour where many patients arrive at the first 105 minutes to open the Puskesmas. The utility of the online registrant registration server is 7%, while 48% offline is classified as low and the patient queue is only about 1 patient so there is no need for an additional registration server to speed up service. There was a difference between online and offline registration waiting times (p = 0.00) where online patients waited 4.91 minutes while offline patients waited 8.84 minutes. There is an effect of waiting time in the system on patient satisfaction (p = 0.00) so that to increase patient satisfaction, it is hoped that patients will register online.
Aziati, A. H. N., Tun, U., Onn, H., Salsabilah, N., & Hamdan, B. (2018). Application Of Queuing Theory Model And Simulation To Patient Flow At The Outpatient Department. Proceedings of the International Conference on Industrial Engineering and Operations Management Bandung, Indonesia, March 6-8, 2018, (December 2019).
Cao, W., Wan, Y., Tu, H., Shang, F., Liu, D., Tan, Z., … Xu, Y. (2011). A web-based appointment system to reduce waiting for outpatients: A retrospective study. BMC Health Services Research, 11. https://doi.org/10.1186/1472-6963-11-318
Chu, H., Westbrook, R. A., Njue-Marendes, S., Giordano, T. P., & Dang, B. N. (2019). The psychology of the wait time experience - What clinics can do to manage the waiting experience for patients: A longitudinal, qualitative study. BMC Health Services Research, 19(1), 1–10. https://doi.org/10.1186/s12913-019-4301-0
Dharmawirya, M., & Adi, E. (2012). Case Study for Restaurant Queuing Model. SSRN Electronic Journal, 6, 52–55. https://doi.org/10.2139/ssrn.2014470
Glogovac, G., Kennedy, M. E., Weisgerber, M. R., Kakazu, R., & Grawe, B. M. (2020). Wait Times in Musculoskeletal Patients: What Contributes to Patient Satisfaction. Journal of Patient Experience, 7(4), 549–553. https://doi.org/10.1177/2374373519864828
Health office Semarang. (2018). Pustaka, now check to Primary Health Care no need to queue!
Kagedan, D. J., Edge, S. B., & Takabe, K. (2021). Behind the clock: elucidating factors contributing to longer clinic appointment duration and patient wait time. BMC Health Services Research, 21(1), 1–9. https://doi.org/10.1186/s12913-021-06079-y
Kreitz, T. M., Winters, B. S., & Pedowitz, D. I. (2016). The Influence of Wait Time on Patient Satisfaction in the Orthopedic Clinic. Journal of Patient Experience, 3(2), 39–42. https://doi.org/10.1177/2374373516652253
Masniah. (2015). An Implementation of Outpatient Online Registration Information System of Mutiara Bunda Hospital. (IJARAI) International Journal of Advanced Research in Artificial Intelligence, 4(12), 9–16.
Oostrom, T., Einav, L., & Finkelstein, A. (2017). Outpatient office wait times and quality of care for medicaid patients. Health Affairs, 36(5), 826–832. https://doi.org/10.1377/hlthaff.2016.1478
Samadbeik, M., Saremian, M., Garavand, A., Hasanvandi, N., Sanaeinasab, S., & Tahmasebi, H. (2018). Assessing the online outpatient booking system. Shiraz E Medical Journal, 19(4). https://doi.org/10.5812/semj.60249
Saremi A, Jula P, ElMekkawy T, W. G. (2015). Bi-criteria appointment scheduling of patients with heterogeneous service sequences. Expert Syst Appl, 42(8).
Shen, X., Yang, W., & Sun, S. (2019). Analysis of the impact of China’s hierarchical medical system and online appointment diagnosis system on the sustainable development of public health: A case study of Shanghai. Sustainability (Switzerland), 11(23). https://doi.org/10.3390/su11236564
Supriyadi, S., Alfarisi, S., Karno, R., & Cahyadi, D. (2019). Queue Design of Bank Teller Service in Banten, Indonesia. 165–171. https://doi.org/10.4108/eai.24-10-2018.2280631
Xavier, G., Crane, J., Follen, M., Wilcox, W., Pulitzer, S., & Noon, C. (2018). Using Poisson Modeling and Queuing Theory to Optimize Staffing and Decrease Patient Wait Time in the Emergency Department. Open Journal of Emergency Medicine, 06(03), 54–72. https://doi.org/10.4236/ojem.2018.63008
Xie, Z., & Or, C. (2017). Associations between waiting times, service times, and patient satisfaction in an endocrinology outpatient department: A time study and questionnaire survey. Inquiry (United States), 54. https://doi.org/10.1177/0046958017739527
Yaduvanshi, D., Sharma, A., & More, P. V. (2019). Application of queuing theory to optimize waiting-time in hospital operations. Operations and Supply Chain Management, 12(3), 165–174. https://doi.org/10.31387/oscm0380240
Yakubu, A., & Najim, U. (2014). An Application of Queuing Theory to ATM Service Optimization: A Case Study. Mathematical Theory and Modeling, 4(6), 11–24.
Abstract viewed = 21 times
PDF downloaded = 23 times
Copyright (c) 2021 Evina Widianawati, Faik Agiwahyuanto
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Jurnal Riset informatika uses the rule of law to access digital electronic articles under the Creative Commons Attribution-NonCommercial 4.0 International License, which means that all content is available free of charge to users or their institutions. You can remix, tweak, and work on non-commercial works, and although new works must also acknowledge the creators and be non-commercial, you don't need to license derivative works under the same terms.