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Characteristics of Patient Arrivals and Service Utilization in Outpatient Departments

  • Yonghou He
  • Bo Chen
  • Yuanxi Li
  • Chunqing Wang
  • Zili Zhang
  • Li TaoEmail author
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 1120)

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.

Keywords

Characteristics of outpatient arrivals Service utilization Statistical analysis Power spectrum analysis 

Notes

Acknowledgment

This work is supported by Fundamental Research Funds for the Central Universities (XDJK2018C045 and XDJK2019D018).

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Yonghou He
    • 1
  • Bo Chen
    • 2
  • Yuanxi Li
    • 3
  • Chunqing Wang
    • 1
  • Zili Zhang
    • 1
  • Li Tao
    • 1
    Email author
  1. 1.School of Computer and Information ScienceSouthwest UniversityChongqingChina
  2. 2.The First Affiliated Hospital of Chongqing Medical UniversityChongqingChina
  3. 3.Department of Computer ScienceHong Kong Baptist UniversityKowloon TongChina

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