Abstract
The characteristics of patient arrivals and service utilization are the theoretical foundation for modeling and simulating healthcare service systems. However, some commonly acknowledged characteristics of outpatient departments (e.g., the Gaussian distribution of the patient numbers, or the exponential distribution of diagnosis time) may be doubted because many outpatients make prior appointment before they come to a hospital in recent years. In this study, we aim to discover the characteristics of patient arrivals and service utilization in five outpatient departments in a big and heavy load hospital in Chongqing, China. Based on the outpatient registration data from 2016 to 2017, we have the following interesting findings: (1) the variation of outpatient arrival numbers in each day is non-linear and can be characterized as pink noise; (2) the distribution of daily arrivals follows a bimodal distribution; (3) the outpatient arrivals in distinct departments exhibit different seasonal patterns; (4) the registration intervals of outpatient arrivals and the doctors’ diagnosis time in all the departments except the Geriatrics department exhibit a power law with cutoff distribution. These empirical findings provide some new insights into the dynamics of patient arrivals and service utilization in outpatient departments and thus enable us to make more reasonable assumptions when modeling the behavior of outpatient departments.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Kim, S.H., Whitt, W., Cha, W.C.: A data-driven model of an appointment-generated arrival process at an outpatient clinic. INFORMS J. Comput. 30(1), 181–199 (2018)
Biswas, S., Arora, H., et al.: On an application of geiger-muller counter model (type-ii) for optimization relating to hospital administration. Acta Med. Int. 4(2), 16 (2017)
Peter, P.O., Sivasamy, R.: Queueing theory techniques and its real applications to health care systems-outpatient visits. Int. J. Healthcare Manag. 1–9 (2019)
Vass, H., Szabo, Z.K.: Application of queuing model to patient flow in emergency department. case study. Proc. Econ. Financ. 32, 479–487 (2015)
Ghamsari, B.N.: Modeling and Improving Patient flow at an Emergency Department in a Local Hospital Using Discrete Event Simulation. Ph.D. thesis, University of Minnesota (2017)
Yang, P.C., et al.: Features of online hospital appointment systems in Taiwan: a nationwide survey. Int. J. Environ. Res. Public Health 16(2), 171 (2019)
Zhang, M., Zhang, C., Sun, Q., Cai, Q., Yang, H., Zhang, Y.: Questionnaire survey about use of an online appointment booking system in one large tertiary public hospital outpatient service center in china. BMC Med. Inform. Decis. Making 14(1), 49 (2014)
Zhang, L., Liu, Z.: Empirical analysis of nonlinear characteristics on the patient flows. J. Syst. Manag. 25(3), 527–531 (2016)
D’amato, G., et al.: Climate change and air pollution: effects on respiratory allergy. Allergy Asthma Immunol. Res. 8(5), 391–395 (2016)
Kelly, F.J., Fussell, J.C.: Air pollution and public health: emerging hazards and improved understanding of risk. Environ. Geochem. Health 37(4), 631–649 (2015)
Strosnider, H.M., Chang, H.H., Darrow, L.A., Liu, Y., Vaidyanathan, A., Strickland, M.J.: Age-specific associations of ozone and fine particulate matter with respiratory emergency department visits in the united states. Am. J. Respir. Critical Care Med. 199(7), 882–890 (2019)
Bao, X., Tian, X., Yang, C., Li, Y., Hu, Y.: Association between ambient air pollution and hospital admission for epilepsy in Eastern China. Epilepsy Res. 152, 52 (2019)
Mukamal, K.J., Wellenius, G.A., Suh, H.H., Mittleman, M.A.: Weather and air pollution as triggers of severe headaches. Neurology 72(10), 922–927 (2009)
Ren, J., Wang, W.X., Yan, G., Wang, B.H.: Emergence of cooperation induced by preferential learning. arXiv preprint physics/0603007 (2006)
Lalwani, A.: Long-range correlations in air quality time series: effect of differencing and shuffling. Aerosol Air Qual. Res. 16(9), 2302–2313 (2016)
Welch, P.: The use of fast fourier transform for the estimation of power spectra: a method based on time averaging over short, modified periodograms. IEEE Trans. Audio Electroacoust. 15(2), 70–73 (1967)
Alstott, J., Bullmore, E., Plenz, D.: Powerlaw: a python package for analysis of heavy-tailed distributions. PloS One 9(1), e85777 (2014)
Acknowledgment
This work is supported by Fundamental Research Funds for the Central Universities (XDJK2018C045 and XDJK2019D018).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
He, Y., Chen, B., Li, Y., Wang, C., Zhang, Z., Tao, L. (2019). Characteristics of Patient Arrivals and Service Utilization in Outpatient Departments. In: Jin, H., Lin, X., Cheng, X., Shi, X., Xiao, N., Huang, Y. (eds) Big Data. BigData 2019. Communications in Computer and Information Science, vol 1120. Springer, Singapore. https://doi.org/10.1007/978-981-15-1899-7_24
Download citation
DOI: https://doi.org/10.1007/978-981-15-1899-7_24
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-15-1898-0
Online ISBN: 978-981-15-1899-7
eBook Packages: Computer ScienceComputer Science (R0)
