Showing 3 results for Waiting Time
Mahnaz Samadbeik , Dr Maryam Ahmadi, Mehdi Birjandi ,
Volume 13, Issue 1 (6-2011)
Abstract
Admission department controls the input and output of the system in any healthcare organization and using some management techniques such as process analysis plays an important role in identifying problems of this unit. The present research was done to study the inpatient admission unit condition in Khorramabad teaching hospitals affiliated to Lorestan university of medical sciences in 2009.
Materials and Methods: This research is a descriptive cross-sectional study. Data were collected using researcher made check-lists based on inpatient admission department standards, and by observation and interview with process owners. The validity and reliability of the checklists were evaluated by content validity and test-retest respectively. The inpatient admission unit process analysis was also done in all the above-mentioned hospitals and data were analyzed by analysis limit, descriptive statistic indices, and SPSS software. The collected information was prepared as statistical tables.
Results: The inpatient admission unit process was similar in foresaid hospitals and only the cash desk, among the units involving in this process was locally centeralized. Mean of waiting time for inpatient admission was 19/10±20/50 minutes.The desirability degree of physical facilities, space, staff, task process approaches, policies, equipment and mechanized system of inpatient admission department in the foresaid hospitals with 35.5% score percentage was average, and the highest percentage correspondence with standard belonged to equipment condition (43.3%) , while the lowest one ( 30%) related to physical facilities and space.
Conclusion: The condition of the investigated admission departments was evaluated as average. To improve admission process, some solutions should be taken into consideration including: preparing and supplying special strategies of inpatient admission department, employing professional and interested staff, holding postgraduation courses, ideal allotting of resources and space, regular evaluation of the admission department function and implementing process improvement procedures.
Peyman Astaraki, Shima Hashemi, Ali Garavand, Farzad Ebrahimzadeh, Maryam Ahadi, Mahnaz Samadbeik,
Volume 22, Issue 1 (4-2020)
Abstract
Background: One of the most significant indicators of the evaluation of emergency centers is the calculation of waiting time for patients to receive diagnostic and therapeutic services. The aim of the present study was to determine the waiting time for the provision of services in the emergency departments of teaching hospitals in Khorramabad.
Materials and Methods: This research was a cross-sectional study conducted in 2017. The study population consisted of all the patients referred to the emergency departments of educational hospitals with an emergency department in Khorramabad. Sampling was randomly carried out through multistage stratified sampling. A valid and reliable checklist was used to collect data, and the data were analyzed by SPSS- 19 by related descriptive and analytical statistical tests.
Results: The three investigated hospitals had a total of 166 emergency beds. 70.6% (573 patients) of the patients had attended the emergency departments with one of their companions, and the greatest frequency of consulation was related to internal medicine specialists (44.5%, 361 people). The gaps between the triage and the first visit, the first visit and the first diagnostic action, sending the first diagnostic action and the medical consultation result, and finally the medical consultation and the outcome of the medical consultation were 8.37 minutes, 31.27 minutes, 9.6 hour, and 7.38 hour respectively.
Conclusion: Regarding the results of this study, it is suggested that the number of emergency department staff and related para-clinical sections increase, thereby reducing the waiting time of people to receive emergency services. Moreover, the authorities are recommended to increase the number of the staff of the night shift in the emergency departments.
Amin Beyranvand, Emad Roghanian, Ahmad Shoja,
Volume 22, Issue 4 (1-2021)
Abstract
Background: Since the emergency department is considered as a vital and important department of any hospital, so the study of service delivery processes in the emergency department has a significant role in patient satisfaction. The purpose of this study is to identify the factors affecting the performance of the emergency department and determine the existing bottlenecks and provide appropriate strategies to improve performance and reduce patient waiting time using a simulation approach.
Materials and Methods: This research is descriptive-analytical. The statistical population of this study was all patients referred to the emergency department of Khorramabad Nomadic Martyrs Educational and Medical Center in a period of three months, which was performed cross-sectionally on 200 patients. First, the processes of the emergency department were identified and then the time of patients' arrival and the time of providing services of the emergency department processes in a quarterly interval were randomly measured in three shifts of morning, evening and night. Then the current situation was designed and simulated using Arena software. By implementing the simulated model, bottlenecks in the emergency department were identified and 6 scenarios were designed and implemented to clear the bottlenecks, improve emergency performance and reduce patient waiting time, and the results were compared and analyzed.
Results: Based on the output of the simulated model, laboratory processes, patient discharge and ultrasound-radiology processes with an average of 174, 71 and 27 minutes of waiting queue were identified as the main bottlenecks. Based on this, 6 scenarios were designed and implemented in the simulation model. According to the simulation results, scenario F with an average decrease of 1.8 hours had the highest decrease in average waiting time and scenario C with a decrease in waiting time of 0.6 hours had the lowest decrease in average patient waiting time compared to other scenarios. Also, Scenario B had the lowest and Scenario F had the highest patient output compared to other scenarios. However, scenario C, which had the least decrease in patient waiting time, has an increase of 11.67% in patient output compared to the current situation.
Conclusion: Scenario F, E and A have better results than other scenarios, respectively, and due to resource and cost constraints in scenarios F and E, the implementation of Scenario A (adding 2 laboratory experts) leads to a reduction in the average waiting time of patients for 1.43 hours compared to the current situation, is recommended.
