Patient flow in the “outpatient-emergency+inpatient” mode: A conceptual model and data analysis

• Main Authors: Xin-li Zhang, Ting Zhu, Li Luo, Chang-zheng He, Zi Liu, Wen-wu Shen
• Format: Conference Proceeding
• Language: English
• Subjects: Analytical models; conceptual model; Correlation; Data analysis; Data models; Hospitals; outpatient-emergency + inpatient; Patient flow; Statistical analysis
• ISSN: 2161-1890
• DOI: 10.1109/ICSSSM.2014.6874144

Patient flow, on one hand, represents the progression of a patient's health status; on the other hand, can be thought of the transferring of patients through multiple hospital units within a hospital or among different hospitals. Furthermore, patient flow, in the aggregate, is equivalent to the demand for health care services. Thus, patient flow management is of great importance to monitor and control health care service demand. As the attributes of patient flow involve an entrance, an exit, a path connecting the entrance and the exit, the stochastic characteristics, patient flows can be classified into outpatient flow (not hospitalized) and inpatient flow considering the exit attribute, and into "emergency + inpatient", "elective surgical/outpatient + inpatient" or "outpatient-emergency + inpatient" considering the entrance attribute. Recent studies mainly focus on "emergency + inpatient" because patients are mainly from emergency department abroad, which is completely different from the "outpatient-emergency + inpatient" mode in China. According to the aforementioned Chinese "outpatient-emergency + inpatient" mode, this paper firstly creates a conceptual model of patient flow network of a typical Chinese hospital; subsequently, chooses inputs of the model as research subject, by using empirical data analysis to excavate the attribute characteristics of patient flow. Ultimately, according to the case study at the admission service centre of a typical Chinese hospital, the statistical analyses on the attribute characteristics of patient flow are actually of great significance on finding managerial measurements for health care service management goals.