Traffic Intensity of Patients and Physicians in the Emergency Department: A Queueing Approach for Physician Utilization

Chung Hsien Chaou, Hsiu Hsi Chen, Petrus Tang, Amy Ming Fang Yen, Kuan Han Wu, Cheng Ting Hsiao, Te Fa Chiu

研究成果: 雜誌貢獻文章

摘要

Background: The unpredictable nature of patient visits poses considerable challenges to the staffing of emergency department (ED) medical personnel. There is a lack of common physician usage parameters at present. Objective: The aim of this study was to quantify the ED traffic intensity of patients and physicians using a queueing model approach. Methods: A retrospective administrative electronic data analysis was conducted in a tertiary medical center. All patients who registered at the ED in 2013 were included. Precisely recorded patient waiting time, service time, and disposition time were obtained. An M/M/s (Markovian patient arrival, Markovian patient service, s servers) queueing model was used, while taking account of the actual physician number and number of patients managed simultaneously. Physician utilization and performance indicators were measured. Results: A total of 148,581 patients were analyzed after exclusion. The overall mean waiting time, service time, and disposition time were 0.23 (standard deviation [SD] = 0.24), 2.31 (SD = 3.89), and 2.54 (SD = 3.90) hours, respectively. Hourly physician utilization (ρ), stratified by different patient entities, was ρ = 0.75 ± 0.17 for adult non-trauma, ρ = 0.75 ± 0.28 for pediatric, and ρ = 0.53 ± 0.18 for trauma (p = 0.0004). There was a surge of utility for pediatric non-trauma patients in the late evening (ρ = 1.4 at 11 PM). The distribution of number of patients in the system was derived and compared by different patient entities and time points. Conclusions: A queueing model was built to model traffic intensity of physicians and patients, the physician utility trend disclosed the fluctuation of manpower utility. The estimated parameters serve as important factors for developing tailored staffing policies for minimizing ED waiting and improving ED crowding.
原文英語
頁(從 - 到)718-725
頁數8
期刊Journal of Emergency Medicine
55
發行號5
DOIs
出版狀態已發佈 - 十一月 1 2018

指紋

Hospital Emergency Service
Physicians
Pediatrics

ASJC Scopus subject areas

  • Emergency Medicine

引用此文

Traffic Intensity of Patients and Physicians in the Emergency Department : A Queueing Approach for Physician Utilization. / Chaou, Chung Hsien; Chen, Hsiu Hsi; Tang, Petrus; Yen, Amy Ming Fang; Wu, Kuan Han; Hsiao, Cheng Ting; Chiu, Te Fa.

於: Journal of Emergency Medicine, 卷 55, 編號 5, 01.11.2018, p. 718-725.

研究成果: 雜誌貢獻文章

Chaou, Chung Hsien ; Chen, Hsiu Hsi ; Tang, Petrus ; Yen, Amy Ming Fang ; Wu, Kuan Han ; Hsiao, Cheng Ting ; Chiu, Te Fa. / Traffic Intensity of Patients and Physicians in the Emergency Department : A Queueing Approach for Physician Utilization. 於: Journal of Emergency Medicine. 2018 ; 卷 55, 編號 5. 頁 718-725.
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abstract = "Background: The unpredictable nature of patient visits poses considerable challenges to the staffing of emergency department (ED) medical personnel. There is a lack of common physician usage parameters at present. Objective: The aim of this study was to quantify the ED traffic intensity of patients and physicians using a queueing model approach. Methods: A retrospective administrative electronic data analysis was conducted in a tertiary medical center. All patients who registered at the ED in 2013 were included. Precisely recorded patient waiting time, service time, and disposition time were obtained. An M/M/s (Markovian patient arrival, Markovian patient service, s servers) queueing model was used, while taking account of the actual physician number and number of patients managed simultaneously. Physician utilization and performance indicators were measured. Results: A total of 148,581 patients were analyzed after exclusion. The overall mean waiting time, service time, and disposition time were 0.23 (standard deviation [SD] = 0.24), 2.31 (SD = 3.89), and 2.54 (SD = 3.90) hours, respectively. Hourly physician utilization (ρ), stratified by different patient entities, was ρ = 0.75 ± 0.17 for adult non-trauma, ρ = 0.75 ± 0.28 for pediatric, and ρ = 0.53 ± 0.18 for trauma (p = 0.0004). There was a surge of utility for pediatric non-trauma patients in the late evening (ρ = 1.4 at 11 PM). The distribution of number of patients in the system was derived and compared by different patient entities and time points. Conclusions: A queueing model was built to model traffic intensity of physicians and patients, the physician utility trend disclosed the fluctuation of manpower utility. The estimated parameters serve as important factors for developing tailored staffing policies for minimizing ED waiting and improving ED crowding.",
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T1 - Traffic Intensity of Patients and Physicians in the Emergency Department

T2 - A Queueing Approach for Physician Utilization

AU - Chaou, Chung Hsien

AU - Chen, Hsiu Hsi

AU - Tang, Petrus

AU - Yen, Amy Ming Fang

AU - Wu, Kuan Han

AU - Hsiao, Cheng Ting

AU - Chiu, Te Fa

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AB - Background: The unpredictable nature of patient visits poses considerable challenges to the staffing of emergency department (ED) medical personnel. There is a lack of common physician usage parameters at present. Objective: The aim of this study was to quantify the ED traffic intensity of patients and physicians using a queueing model approach. Methods: A retrospective administrative electronic data analysis was conducted in a tertiary medical center. All patients who registered at the ED in 2013 were included. Precisely recorded patient waiting time, service time, and disposition time were obtained. An M/M/s (Markovian patient arrival, Markovian patient service, s servers) queueing model was used, while taking account of the actual physician number and number of patients managed simultaneously. Physician utilization and performance indicators were measured. Results: A total of 148,581 patients were analyzed after exclusion. The overall mean waiting time, service time, and disposition time were 0.23 (standard deviation [SD] = 0.24), 2.31 (SD = 3.89), and 2.54 (SD = 3.90) hours, respectively. Hourly physician utilization (ρ), stratified by different patient entities, was ρ = 0.75 ± 0.17 for adult non-trauma, ρ = 0.75 ± 0.28 for pediatric, and ρ = 0.53 ± 0.18 for trauma (p = 0.0004). There was a surge of utility for pediatric non-trauma patients in the late evening (ρ = 1.4 at 11 PM). The distribution of number of patients in the system was derived and compared by different patient entities and time points. Conclusions: A queueing model was built to model traffic intensity of physicians and patients, the physician utility trend disclosed the fluctuation of manpower utility. The estimated parameters serve as important factors for developing tailored staffing policies for minimizing ED waiting and improving ED crowding.

KW - crowding

KW - emergency department

KW - physician utilization

KW - queueing model

KW - service time

KW - staffing policy

KW - traffic intensity

KW - waiting time

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